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.

Why do firms acquire external technologies? Understanding the motivations for technology acquisitions

Why do firms acquire external technologies? Previous research indicates that there are a wide variety of motivations. These include the need to acquire valuable knowledge-based resources, to improve strategic flexibility, to experiment), to overcome organisational inertia, to mitigate risk and uncertainty, to reduce costs and development time in new product development, and the perception that the firm has the absorptive capacity to integrate acquisitions. In this paper we provide an in-depth literature review of the motivations for the acquisition of external technologies by firms. We find that these motivations can be broadly classed into four categories: (1) the development of technological capabilities, (2) the development of strategic options, (3) efficiency improvements, and (4) responses to the competitive environment. In light of this categorisation, we comment on how these different motivations connect to the wider issues of technology acquisition. © 2010 IEEE.

Why do nominal characteristics acquire status value? A minimal explanation for status construction.

Why do beliefs that attach different amounts of status to different categories of people become consensually held by the members of a society? We show that two microlevel mechanisms, in combination, imply a system-level tendency toward consensual status beliefs about a nominal characteristic. (1) Status belief diffusion: a person who has no status belief about a characteristic can acquire a status belief about that characteristic from interacting with one or more people who have that status belief. (2) Status belief loss: a person who has a status belief about a characteristic can lose that belief from interacting with one or more people who have the opposite status belief. These mechanisms imply that opposite status beliefs will tend to be lost at equal rates and will tend to be acquired at rates proportional to their prevalence. Therefore, if a status belief ever becomes more prevalent than its opposite, it will increase in prevalence until every person holds it.

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.

Monocyte-derived dendritic cells: a potential target for therapy in multiple sclerosis (MS)

Monocytes can differentiate into dendritic cells (DC), cells with a pivotal role in both protective immunity and tolerance. Defects in the maturation or function of DC may be important in the development of autoimmune disease. We sought to establish if there were differences in the cytokine (granulocyte-macrophage colony-stimulating factor and IL-4)-driven maturation of monocytes to DC in patients with MS and whether drugs used to treat MS affected this process in vitro. We have demonstrated that there is no defect in the ability of magnetic activated cell sorting (MACS)-purified monocytes from patients with MS to differentiate to DC, but equally they show no tendency to acquire a DC phenotype without exogenous cytokines. Interferon-beta1a prevents the acquisition of a full DC phenotype as determined by light and electron microscopy and by flow cytometry. Methylprednisolone not only prevents the development of monocyte-derived DC but totally redirects monocyte differentiation towards a macrophage phenotype. Evidence is evolving for a role for DC in central nervous system immunity, either within the brain or in cervical lymph nodes. The demonstrated effect of both drugs on monocyte differentiation may represent an important site for immune therapy in MS.

Inactivation of macrophage Rab7 by Burkholderia cenocepacia

Strains of the Burkholderia cepacia complex can survive within macrophages by arresting the maturation of phagocytic vacuoles. The bacteria preclude fusion of the phagosome with lysosomes by a process that is poorly understood. Using murine macrophages, we investigated the stage at which maturation is arrested and analyzed the underlying mechanism. Vacuoles containing B. cenocepacia strain J2315, an isolate of the transmissible ET12 clone, recruited Rab5 and synthesized phosphatidylinositol-3-phosphate, indicating progression to the early phagosomal stage. Despite the fact that the B. cenocepacia-containing vacuoles rarely fused with lysosomes, they could nevertheless acquire the late phagosomal markers CD63 and Rab7. Fluorescence recovery after photobleaching and use of a probe that detects Rab7-guanosine triphosphate indicated that activation of Rab7 was impaired by B. cenocepacia, accounting at least in part for the inability of the vacuole to merge with lysosomes. The Rab7 defect was not due to excessive cholesterol accumulation and was confined to the infected vacuoles. Jointly, these experiments indicate that B. cenocepacia express virulence factors capable of interfering with Rab7 function and thereby with membrane traffic.

Integrating nutrition and immunology: A new frontier

Nutrition is critical to immune defence and parasite resistance, which not only affects individual organisms, but also has profound ecological and evolutionary consequences. Nutrition and immunity are complex traits that interact via multiple direct and indirect pathways, including the direct effects of nutrition on host immunity but also indirect effects mediated by the host's microbiota and pathogen populations. The challenge remains, however, to capture the complexity of the network of interactions that defines nutritional immunology. The aim of this paper is to discuss the recent findings in nutritional research in the context of immunological studies. By taking examples from the entomological literature, we argue that insects provide a powerful tool for examining the network of interactions between nutrition and immunity due to their tractability, short lifespan and ethical considerations. We describe the relationships between dietary composition, immunity, disease and microbiota in insects, and highlight the importance of adopting an integrative and multi-dimensional approach to nutritional immunology. 

Immunology taught by lung dendritic cells.

Dendritic cells (DCs) are leukocytes specialised in the uptake, processing, and presentation of antigen and fundamental in regulating both innate and adaptive immune functions. They are mainly localised at the interface between body surfaces and the environment, continuously scrutinising incoming antigen for the potential threat it may represent to the organism. In the respiratory tract, DCs constitute a tightly enmeshed network, with the most prominent populations localised in the epithelium of the conducting airways and lung parenchyma. Their unique localisation enables them to continuously assess inhaled antigen, either inducing tolerance to inoffensive substances, or initiating immunity against a potentially harmful pathogen. This immunological homeostasis requires stringent control mechanisms to protect the vital and fragile gaseous exchange barrier from unrestrained and damaging inflammation, or an exaggerated immune response to an innocuous allergen, such as in allergic asthma. During DC activation, there is upregulation of co-stimulatory molecules and maturation markers, enabling DC to activate naïve T cells. This activation is accompanied by chemokine and cytokine release that not only serves to amplify innate immune response, but also determines the type of effector T cell population generated. An increasing body of recent literature provides evidence that different DC subpopulations, such as myeloid DC (mDC) and plasmacytoid DC (pDC) in the lungs occupy a key position at the crossroads between tolerance and immunity. This review aims to provide the clinician and researcher with a summary of the latest insights into DC-mediated pulmonary immune regulation and its relevance for developing novel therapeutic strategies for various disease conditions such as infection, asthma, COPD, and fibrotic lung disease.