Intramolecular conflict : conformation and self-assembly of architecturally complex macromolecules in solution

The solution behavior of linear polymer chains is well understood, having been the subject of intense study throughout the previous century. As plastics have become ubiquitous in everyday life, polymer science has grown into a major field of study. The conformation of a polymer in solution depends on the molecular architecture and its interactions with the surroundings. Developments in synthetic techniques have led to the creation of precision-tailored polymeric materials with varied topologies and functionalities. In order to design materials with the desired properties, it is imperative to understand the relationships between polymer architecture and their conformation and behavior. To meet that need, this thesis investigates the conformation and self-assembly of three architecturally complex macromolecular systems with rich and varied behaviors driven by the resolution of intramolecular conflicts. First we describe the development of a robust and facile synthetic approach to reproducible bottlebrush polymers (Chapter 2). The method was used to produce homologous series of bottlebrush polymers with polynorbornene backbones, which revealed the effect of side-chain and backbone length on the overall conformation in both good and theta solvent conditions (Chapter 3). The side-chain conformation was obtained from a series of SANS experiments and determined to be indistinguishable from the behavior of free linear polymer chains. Using deuterium-labeled bottlebrushes, we were able for the first time to directly observe the backbone conformation of a bottlebrush polymer which showed self-avoiding walk behavior. Secondly, a series of SANS experiments was conducted on a homologous series of Side Group Liquid Crystalline Polymers (SGLCPs) in a perdeuterated small molecule liquid crystal (5CB). Monodomain, aligned, dilute samples of SGLCP-b-PS block copolymers were seen to self-assemble into complex micellar structures with mutually orthogonally oriented anisotropies at different length scales (Chapter 4). Finally, we present the results from the first scattering experiments on a set of fuel-soluble, associating telechelic polymers. We observed the formation of supramolecular aggregates in dilute (≤0.5wt%) solutions of telechelic polymers and determined that the choice of solvent has a significant effect on the strength of association and the size of the supramolecules (Chapter 5). A method was developed for the direct estimation of supramolecular aggregation number from SANS data. The insight into structure-property relationships obtained from this work will enable the more targeted development of these molecular architectures for their respective applications.

Latent variable models for neural data analysis

The brain is perhaps the most complex system to have ever been subjected to rigorous scientific investigation. The scale is staggering: over 10^11 neurons, each making an average of 10^3 synapses, with computation occurring on scales ranging from a single dendritic spine, to an entire cortical area. Slowly, we are beginning to acquire experimental tools that can gather the massive amounts of data needed to characterize this system. However, to understand and interpret these data will also require substantial strides in inferential and statistical techniques. This dissertation attempts to meet this need, extending and applying the modern tools of latent variable modeling to problems in neural data analysis.

It is divided into two parts. The first begins with an exposition of the general techniques of latent variable modeling. A new, extremely general, optimization algorithm is proposed - called Relaxation Expectation Maximization (REM) - that may be used to learn the optimal parameter values of arbitrary latent variable models. This algorithm appears to alleviate the common problem of convergence to local, sub-optimal, likelihood maxima. REM leads to a natural framework for model size selection; in combination with standard model selection techniques the quality of fits may be further improved, while the appropriate model size is automatically and efficiently determined. Next, a new latent variable model, the mixture of sparse hidden Markov models, is introduced, and approximate inference and learning algorithms are derived for it. This model is applied in the second part of the thesis.

The second part brings the technology of part I to bear on two important problems in experimental neuroscience. The first is known as spike sorting; this is the problem of separating the spikes from different neurons embedded within an extracellular recording. The dissertation offers the first thorough statistical analysis of this problem, which then yields the first powerful probabilistic solution. The second problem addressed is that of characterizing the distribution of spike trains recorded from the same neuron under identical experimental conditions. A latent variable model is proposed. Inference and learning in this model leads to new principled algorithms for smoothing and clustering of spike data.

Synthesis and biological activity of anticoagulant heparan sulfate glycopolymers

Heparin has been used as an anticoagulant drug for more than 70 years. The global distribution of contaminated heparin in 2007, which resulted in adverse clinical effects and over 100 deaths, emphasizes the necessity for safer alternatives to animal-sourced heparin. The structural complexity and heterogeneity of animal-sourced heparin not only impedes safe access to these biologically active molecules, but also hinders investigations on the significance of structural constituents at a molecular level. Efficient methods for preparing new synthetic heparins with targeted biological activity are necessary not only to ensure clinical safety, but to optimize derivative design to minimize potential side effects. Low molecular weight heparins have become a reliable alternative to heparin, due to their predictable dosages, long half-lives, and reduced side effects. However, heparin oligosaccharide synthesis is a challenging endeavor due to the necessity for complex protecting group manipulation and stereoselective glycosidic linkage chemistry, which often result in lengthy synthetic routes and low yields. Recently, chemoenzymatic syntheses have produced targeted ultralow molecular weight heparins with high-efficiency, but continue to be restricted by the substrate specificities of enzymes.

To address the need for access to homogeneous, complex glycosaminoglycan structures, we have synthesized novel heparan sulfate glycopolymers with well-defined carbohydrate structures and tunable chain length through ring-opening metathesis polymerization chemistry. These polymers recapitulate the key features of anticoagulant heparan sulfate by displaying the sulfation pattern responsible for heparin’s anticoagulant activity. The use of polymerization chemistry greatly simplifies the synthesis of complex glycosaminoglycan structures, providing a facile method to generate homogeneous macromolecules with tunable biological and chemical properties. Through the use of in vitro chromogenic substrate assays and ex vivo clotting assays, we found that the HS glycopolymers exhibited anticoagulant activity in a sulfation pattern and length-dependent manner. Compared to heparin standards, our short polymers did not display any activity. However, our longer polymers were able to incorporate in vitro and ex vivo characteristics of both low-molecular-weight heparin derivatives and heparin, displaying hybrid anticoagulant properties. These studies emphasize the significance of sulfation pattern specificity in specific carbohydrate-protein interactions, and demonstrate the effectiveness of multivalent molecules in recapitulating the activity of natural polysaccharides.

Molecular mechanism of sulfated carbohydrate recognition: structural and biochemical studies of the cysteine-rich domain of mannose receptor

Mannose receptor (MR) is widely expressed on macrophages, immature dendritic cells, and a variety of epithelial and endothelial cells. It is a 180 kD type I transmembrane receptor whose extracellular region consists of three parts: the amino-terminal cysteine-rich domain (Cys-MR); a fibronectin type II-like domain; and a series of eight tandem C-type lectin carbohydrate recognition domains (CRDs). Two portions of MR have distinct carbohydrate recognition properties: Cys-MR recognizes sulfated carbohydrates and the tandem CRD region binds terminal mannose, fucose, and N-acetyl-glucosamine (GlcNAc). The dual carbohydrate binding specificity allows MR to interact with sulfated and nonsulfated polysaccharide chains, and thereby facilitating the involvement of MR in immunological and physiological processes. The immunological functions of MR include antigen capturing (through binding non-sulfated carbohydrates) and antigen targeting (through binding sulfated carbohydrates), and the physiological roles include rapid clearance of circulatory luteinizing hormone (LH), which bears polysaccharide chains terminating with sulfated and non-sulfated carbohydrates.

We have crystallized and determined the X-ray structures of unliganded Cys-MR (2.0 Å) and Cys-MR complexed with different ligands, including Hepes (1.7 Å), 4SO_4-N-Acetylgalactosamine (4SO_4-GalNAc; 2.2 Å), 3SO_4-Lewis^x (2.2 Å), 3S04-Lewis^a (1.9 Å), and 6SO_4-GalNAc (2.5 Å). The overall structure of Cys-MR consists of 12 anti-parallel β-strands arranged in three lobes with approximate three fold internal symmetry. The structure contains three disulfide bonds, formed by the six cysteines in the Cys-MR sequence. The ligand-binding site is located in a neutral pocket within the third lobe, in which the sulfate group of ligand is buried. Our results show that optimal binding is achieved by a carbohydrate ligand with a sulfate group that anchors the ligand by forming numerous hydrogen bonds and a sugar ring that makes ring-stacking interactions with Trpll7 of CysMR. Using a fluorescence-based assay, we characterized the binding affinities between CysMR and its ligands, and rationalized the derived affinities based upon the crystal structures. These studies reveal the mechanism of sulfated carbohydrate recognition by Cys-MR and facilitate our understanding of the role of Cys-MR in MR recognition of its ligands.

Biophysical and network mechanisms of high frequency extracellular potentials in the rat hippocampus

A fundamental question in neuroscience is how distributed networks of neurons communicate and coordinate dynamically and specifically. Several models propose that oscillating local networks can transiently couple to each other through phase-locked firing. Coherent local field potentials (LFP) between synaptically connected regions is often presented as evidence for such coupling. The physiological correlates of LFP signals depend on many anatomical and physiological factors, however, and how the underlying neural processes collectively generate features of different spatiotemporal scales is poorly understood. High frequency oscillations in the hippocampus, including gamma rhythms (30-100 Hz) that are organized by the theta oscillations (5-10 Hz) during active exploration and REM sleep, as well as sharp wave-ripples (SWRs, 140-200 Hz) during immobility or slow wave sleep, have each been associated with various aspects of learning and memory. Deciphering their physiology and functional consequences is crucial to understanding the operation of the hippocampal network.

We investigated the origins and coordination of high frequency LFPs in the hippocampo-entorhinal network using both biophysical models and analyses of large-scale recordings in behaving and sleeping rats. We found that the synchronization of pyramidal cell spikes substantially shapes, or even dominates, the electrical signature of SWRs in area CA1 of the hippocampus. The precise mechanisms coordinating this synchrony are still unresolved, but they appear to also affect CA1 activity during theta oscillations. The input to CA1, which often arrives in the form of gamma-frequency waves of activity from area CA3 and layer 3 of entorhinal cortex (EC3), did not strongly influence the timing of CA1 pyramidal cells. Rather, our data are more consistent with local network interactions governing pyramidal cells' spike timing during the integration of their inputs. Furthermore, the relative timing of input from EC3 and CA3 during the theta cycle matched that found in previous work to engage mechanisms for synapse modification and active dendritic processes. Our work demonstrates how local networks interact with upstream inputs to generate a coordinated hippocampal output during behavior and sleep, in the form of theta-gamma coupling and SWRs.

Self-assembly of brush polymers

The unique structure and properties of brush polymers have led to increased interest in them within the scientific community. This thesis describes studies on the self-assembly of these brush polymers.

Chapter 2 describes a study on the rapid self-assembly of brush block copolymers into nanostructures with photonic bandgaps spanning the entire visible spectrum, from ultraviolet to near infrared. Linear relationships are observed between the peak wavelengths of reflection and polymer molecular weights. This work enables "bottom-up" fabrication of photonic crystals with application-tailored bandgaps, through synthetic control of the polymer molecular weight and the method of self-assembly.

Chapter 3 details the analysis of the self-assembly of symmetrical brush block copolymers in bulk and thin films. Highly ordered lamellae with domain spacing ranging from 20 to 240 nm are obtained by varying molecular weight of the backbone. The relationship between degree of polymerization and the domain spacing is reported, and evidence is provided for how rapidly the brush block copolymers self-assemble and achieve thermodynamic equilibrium.

Chapter 4 describes investigations into where morphology transitions take place as the volume fraction of each block is varied in asymmetrical brush block copolymers. Imaging techniques are used to observe a transition from lamellar to a cylindrical morphology as the volume fraction of one of the blocks exceeds 70%. It is also shown that the asymmetric brush block copolymers can be kinetically trapped into undulating lamellar structures by drop casting the samples.

Chapter 5 explores the capability of macromolecules to interdigitate into densely grafted molecular brush copolymers using stereocomplex formation as a driving force. The stereocomplex formation between complementary linear polymers and brush copolymers is demonstrated, while the stereocomplex formation between complementary brush copolymers is shown to be restricted.

Contribution of the temporoammonic pathway to hippocampal processing

The temporoammonic (TA) pathway is the direct, monosynaptic projection from layer III of entorhinal cortex to the distal dendritic region of area CA1 of the hippo­ campus. Although this pathway has been implicated in various functions, such as memory encoding and retrieval, spatial navigation, generation of oscillatory activity, and control of hippocampal excitability, the details of its physiology are not well understood. In this thesis, I examine the contribution of the TA pathway to hippocampal processing. I find that, as has been previously reported, the TA pathway includes both excitatory, glutamatergic components and inhibitory, GABAergic components. Several new discoveries are reported in this thesis. I show that the TA pathway is subject to forms of short-term activity-dependent regulation, including paired-pulse and frequency­ dependent plasticity, similar to other hippocampal pathways such as the Schaffer collateral (SC) input from CA3 to CA1. The TA pathway provides a strongly excitatory input to stratum radiatum giant cells of CA1. The excitatory component of the TA pathway undergoes a long-lasting decrease in synaptic strength following low-frequency stimulation in a manner partially dependent on the activation of NMDA receptors. High­ frequency activation of the TA pathway recruits a feedforward inhibition that can prevent CA1 pyramidal cells from spiking in response to SC input; this spike-blocking effect shows that the TA pathway can act to regulate information flow through the hippocampal trisynaptic pathway.

High resolution electron microscope studies of chromosomal fibers

Techniques are described for mounting and visualizing biological macromolecules for high resolution electron microscopy. Standard techniques are included in a discussion of new methods designed to provide the highest structural resolution. Methods are also discussed for handling samples on the grid, for making accurate size measurements at the 20 Å level, and for photographically enhancing image contrast.

The application of these techniques to the study of the binding of DNA polymerase to DNA is described. It is shown that the electron micrographs of this material are in agreement with the model proposed by Dr. Arthur Kornberg. A model is described which locates several active sites on the enzyme.

The chromosomal material of the protozoan tetrahymena has been isolated and characterized by biochemical techniques and by electron microscopy. This material is shown to be typical of chromatin of higher creatures.

Comparison with other chromatins discloses that the genome of tetrahymena is highly template active and has a relatively simple genetic construction.

High resolution electron microscope procedures developed in this work have been combined with standard biochemical techniques to give a comprehensive picture of the structure of interphase chromosome fibers. The distribution of the chromosomal proteins along its DNA is discussed.

Firing Patterns of Cerebellar Purkinje Cells During Locomotion and Sleep

The cerebellum is a major supraspinal center involved in the coordination of movement. The principal neurons of the cerebellar cortex, Purkinje cells, receive excitatory synaptic input from two sources: the parallel and climbing fibers. These pathways have markedly different effects: the parallel fibers control the rate of simple sodium spikes, while the climbing fibers induce characteristic complex spike bursts, which are accompanied by dendritic calcium transients and play a key role in regulating synaptic plasticity. While many studies using a variety of species, behaviors, and cerebellar regions have documented modulation in Purkinje cell activity during movement, few have attempted to record from these neurons in unrestrained rodents. In this dissertation, we use chronic, multi-tetrode recording in freely-behaving rats to study simple and complex spike firing patterns during locomotion and sleep. Purkinje cells discharge rhythmically during stepping, but this activity is highly variable across steps. We show that behavioral variables systematically influence the step-locked firing rate in a step-phase-dependent way, revealing a functional clustering of Purkinje cells. Furthermore, we find a pronounced disassociation between patterns of variability driven by the parallel and climbing fibers, as well as functional differences between cerebellar lobules. These results suggest that Purkinje cell activity not only represents step phase within each cycle, but is also shaped by behavior across steps, facilitating control of movement under dynamic conditions. During sleep, we observe an attenuation of both simple and complex spiking, relative to awake behavior. Although firing rates during slow wave sleep (SWS) and rapid eye movement sleep (REM) are similar, simple spike activity is highly regular in SWS, while REM is characterized by phasic increases and pauses in simple spiking. This phasic activity in REM is associated with pontine waves, which propagate into the cerebellar cortex and modulate both simple and complex spiking. Such a temporal coincidence between parallel and climbing fiber activity is known to drive plasticity at parallel fiber synapses; consequently, pontocerebellar waves may provide a mechanism for tuning synaptic weights in the cerebellum during active sleep.

The Physiology and Computation of Pyramidal Neurons

A variety of neural signals have been measured as correlates to consciousness. In particular, late current sinks in layer 1, distributed activity across the cortex, and feedback processing have all been implicated. What are the physiological underpinnings of these signals? What computational role do they play in the brain? Why do they correlate to consciousness? This thesis begins to answer these questions by focusing on the pyramidal neuron. As the primary communicator of long-range feedforward and feedback signals in the cortex, the pyramidal neuron is set up to play an important role in establishing distributed representations. Additionally, the dendritic extent, reaching layer 1, is well situated to receive feedback inputs and contribute to current sinks in the upper layers. An investigation of pyramidal neuron physiology is therefore necessary to understand how the brain creates, and potentially uses, the neural correlates of consciousness. An important part of this thesis will be in establishing the computational role that dendritic physiology plays. In order to do this, a combined experimental and modeling approach is used.

This thesis beings with single-cell experiments in layer 5 and layer 2/3 pyramidal neurons. In both cases, dendritic nonlinearities are characterized and found to be integral regulators of neural output. Particular attention is paid to calcium spikes and NMDA spikes, which both exist in the apical dendrites, considerable distances from the spike initiation zone. These experiments are then used to create detailed multicompartmental models. These models are used to test hypothesis regarding spatial distribution of membrane channels, to quantify the effects of certain experimental manipulations, and to establish the computational properties of the single cell. We find that the pyramidal neuron physiology can carry out a coincidence detection mechanism. Further abstraction of these models reveals potential mechanisms for spike time control, frequency modulation, and tuning. Finally, a set of experiments are carried out to establish the effect of long-range feedback inputs onto the pyramidal neuron. A final discussion then explores a potential way in which the physiology of pyramidal neurons can establish distributed representations, and contribute to consciousness.