Alternative splicing in multiple sclerosis and other autoimmune diseases.

Alternative splicing is a general mechanism for regulating gene expression that affects the RNA products of more than 90% of human genes. Not surprisingly, alternative splicing is observed among gene products of metazoan immune systems, which have evolved to efficiently recognize pathogens and discriminate between "self" and "non-self", and thus need to be both diverse and flexible. In this review we focus on the specific interface between alternative splicing and autoimmune diseases, which result from a malfunctioning of the immune system and are characterized by the inappropriate reaction to self-antigens. Despite the widespread recognition of alternative splicing as one of the major regulators of gene expression, the connections between alternative splicing and autoimmunity have not been apparent. We summarize recent findings connecting splicing and autoimmune disease, and attempt to find common patterns of splicing regulation that may advance our understanding of autoimmune diseases and open new avenues for therapy.

Coding Strategies and Implementations of Compressive Sensing

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others.

This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system.

Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity.

Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Molecular Insights of CD4+ T Cell Differentiation, Effector Formation and Helper Function

CD4+ T cells play a crucial in the adaptive immune system. They function as the central hub to orchestrate the rest of immunity: CD4+ T cells are essential governing machinery in antibacterial and antiviral responses by facilitating B cell affinity maturation and coordinating the innate and adaptive immune systems to boost the overall immune outcome; on the contrary, hyperactivation of the inflammatory lineages of CD4+ T cells, as well as the impairments of suppressive CD4+ regulatory T cells, are the etiology of various autoimmunity and inflammatory diseases. The broad role of CD4+ T cells in both physiological and pathological contexts prompted me to explore the modulation of CD4+ T cells on the molecular level.

microRNAs (miRNAs) are small RNA molecules capable of regulating gene expression post-transcriptionally. miRNAs have been shown to exert substantial regulatory effects on CD4+ T cell activation, differentiation and helper function. Specifically, my lab has previously established the function of the miR-17-92 cluster in Th1 differentiation and anti-tumor responses. Here, I further analyzed the role of this miRNA cluster in Th17 differentiation, specifically, in the context of autoimmune diseases. Using both gain- and loss-of-function approaches, I demonstrated that miRNAs in miR-17-92, specifically, miR-17 and miR-19b in this cluster, is a crucial promoter of Th17 differentiation. Consequently, loss of miR-17-92 expression in T cells mitigated the progression of experimental autoimmune encephalomyelitis and T cell-induced colitis. In combination with my previous data, the molecular dissection of this cluster establishes that miR-19b and miR-17 play a comprehensive role in promoting multiple aspects of inflammatory T cell responses, which underscore them as potential targets for oligonucleotide-based therapy in treating autoimmune diseases.

To systematically study miRNA regulation in effector CD4+ T cells, I devised a large-scale miRNAome profiling to track in vivo miRNA changes in antigen-specific CD4+ T cells activated by Listeria challenge. From this screening, I identified that miR-23a expression tightly correlates with CD4+ effector expansion. Ectopic expression and genetic deletion strategies validated that miR-23a was required for antigen-stimulated effector CD4+ T cell survival in vitro and in vivo. I further determined that miR-23a targets Ppif, a gatekeeper of mitochondrial reactive oxygen species (ROS) release that protects CD4+ T cells from necrosis. Necrosis is a type of cell death that provokes inflammation, and it is prominently triggered by ROS release and its consequent oxidative stress. My finding that miR-23a curbs ROS-mediated necrosis highlights the essential role of this miRNA in maintaining immune homeostasis.

A key feature of miRNAs is their ability to modulate different biological aspects in different cell populations. Previously, my lab found that miR-23a potently suppresses CD8+ T cell cytotoxicity by restricting BLIMP1 expression. Since BLIMP1 has been found to inhibit T follicular helper (Tfh) differentiation by antagonizing the master transcription factor BCL6, I investigated whether miR-23a is also involved in Tfh differentiation. However, I found that miR-23a does not target BLIMP1 in CD4+ T cells and loss of miR-23a even fostered Tfh differentiation. This data indicate that miR-23a may target other pathways in CD4+ T cells regarding the Tfh differentiation pathway.

Although the lineage identity and regulatory networks for Tfh cells have been defined, the differentiation path of Tfh cells remains elusive. Two models have been proposed to explain the differentiation process of Tfh cells: in the parallel differentiation model, the Tfh lineage is segregated from other effector lineages at the early stage of antigen activation; alternatively, the sequential differentiation model suggests that naïve CD4+ T cells first differentiate into various effector lineages, then further program into Tfh cells. To address this question, I developed a novel in vitro co-culture system that employed antigen-specific CD4+ T cells, naïve B cells presenting cognate T cell antigen and BAFF-producing feeder cells to mimic germinal center. Using this system, I were able to robustly generate GC-like B cells. Notably, well-differentiated Th1 or Th2 effector cells also quickly acquired Tfh phenotype and function during in vitro co-culture, which suggested a sequential differentiation path for Tfh cells. To examine this path in vivo, under conditions of classical Th1- or Th2-type immunizations, I employed a TCRβ repertoire sequencing technique to track the clonotype origin of Tfh cells. Under both Th1- and Th2- immunization conditions, I observed profound repertoire overlaps between the Teff and Tfh populations, which strongly supports the proposed sequential differentiation model. Therefore, my studies establish a new platform to conveniently study Tfh-GC B cell interactions and provide insights into Tfh differentiation processes.

Similar T-cell immune responses induced by group M consensus env immunogens with wild-type or minimum consensus variable regions.

Consensus HIV-1 genes can decrease the genetic distances between candidate immunogens and field virus strains. To ensure the functionality and optimal presentation of immunologic epitopes, we generated two group-M consensus env genes that contain variable regions either from a wild-type B/C recombinant virus isolate (CON6) or minimal consensus elements (CON-S) in the V1, V2, V4, and V5 regions. C57BL/6 and BALB/c mice were primed twice with CON6, CON-S, and subtype control (92UG37_A and HXB2/Bal_B) DNA and boosted with recombinant vaccinia virus (rVV). Mean antibody titers against 92UG37_A, 89.6_B, 96ZM651_C, CON6, and CON-S Env protein were determined. Both CON6 and CON-S induced higher mean antibody titers against several of the proteins, as compared with the subtype controls. However, no significant differences were found in mean antibody titers in animals immunized with CON6 or CON-S. Cellular immune responses were measured by using five complete Env overlapping peptide sets: subtype A (92UG37_A), subtype B (MN_B, 89.6_B and SF162_B), and subtype C (Chn19_C). The intensity of the induced cellular responses was measured by using pooled Env peptides; T-cell epitopes were identified by using matrix peptide pools and individual peptides. No significant differences in T-cell immune-response intensities were noted between CON6 and CON-S immunized BALB/c and C57BL/6 mice. In BALB/c mice, 10 and eight nonoverlapping T-cell epitopes were identified in CON6 and CON-S, whereas eight epitopes were identified in 92UG37_A and HXB2/BAL_B. In C57BL/6 mice, nine and six nonoverlapping T-cell epitopes were identified after immunization with CON6 and CON-S, respectively, whereas only four and three were identified in 92UG37_A and HXB2/BAL_B, respectively. When combined together from both mouse strains, 18 epitopes were identified. The group M artificial consensus env genes, CON6 and CON-S, were equally immunogenic in breadth and intensity for inducing humoral and cellular immune responses.

The Multiscale Systems Immunology project: software for cell-based immunological simulation.

BACKGROUND: Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing. RESULTS: The Multiscale Systems Immunology (MSI) simulation framework is an object-oriented, modular simulation framework written in C++ and Python. The software implements a modular design that allows for flexible configuration of components and initialization of parameters, thus allowing simulations to be run that model processes occurring over different temporal and spatial scales. CONCLUSION: MSI addresses the need for a flexible and high-performing agent based model of the immune system.