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.

Technology for Single Cell Protein Analysis in Immunology and Cancer Prognostics

The first chapter of this thesis deals with automating data gathering for single cell microfluidic tests. The programs developed saved significant amounts of time with no loss in accuracy. The technology from this chapter was applied to experiments in both Chapters 4 and 5.

The second chapter describes the use of statistical learning to prognose if an anti-angiogenic drug (Bevacizumab) would successfully treat a glioblastoma multiforme tumor. This was conducted by first measuring protein levels from 92 blood samples using the DNA-encoded antibody library platform. This allowed the measure of 35 different proteins per sample, with comparable sensitivity to ELISA. Two statistical learning models were developed in order to predict whether the treatment would succeed. The first, logistic regression, predicted with 85% accuracy and an AUC of 0.901 using a five protein panel. These five proteins were statistically significant predictors and gave insight into the mechanism behind anti-angiogenic success/failure. The second model, an ensemble model of logistic regression, kNN, and random forest, predicted with a slightly higher accuracy of 87%.

The third chapter details the development of a photocleavable conjugate that multiplexed cell surface detection in microfluidic devices. The method successfully detected streptavidin on coated beads with 92% positive predictive rate. Furthermore, chambers with 0, 1, 2, and 3+ beads were statistically distinguishable. The method was then used to detect CD3 on Jurkat T cells, yielding a positive predictive rate of 49% and false positive rate of 0%.

The fourth chapter talks about the use of measuring T cell polyfunctionality in order to predict whether a patient will succeed an adoptive T cells transfer therapy. In 15 patients, we measured 10 proteins from individual T cells (~300 cells per patient). The polyfunctional strength index was calculated, which was then correlated with the patient's progress free survival (PFS) time. 52 other parameters measured in the single cell test were correlated with the PFS. No statistical correlator has been determined, however, and more data is necessary to reach a conclusion.

Finally, the fifth chapter talks about the interactions between T cells and how that affects their protein secretion. It was observed that T cells in direct contact selectively enhance their protein secretion, in some cases by over 5 fold. This occurred for Granzyme B, Perforin, CCL4, TNFa, and IFNg. IL- 10 was shown to decrease slightly upon contact. This phenomenon held true for T cells from all patients tested (n=8). Using single cell data, the theoretical protein secretion frequency was calculated for two cells and then compared to the observed rate of secretion for both two cells not in contact, and two cells in contact. In over 90% of cases, the theoretical protein secretion rate matched that of two cells not in contact.

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.