Using immunology and resistant sheep to beat the fly

New methods for controlling blowfly strike will be needed when mulesing is phased out and the availability or efficacy of insecticides for control of fly strike decreases. The Australian Sheep Industry CRC has pursued two approaches for the development of new methods to help control blowfly strike. In the first, genetic resistance of sheep to survival and growth of blowfly larvae was examined. Resistance to growth of larvae was heritable (0.29 ± 0.22). The trait was not associated with resistance to internal parasites, nor was it influenced by wool characteristics such as fibre diameter or coefficient of variation of fibre diameter. This new trait differs from resistance to fly strike associated with resistance to fleece rot. Because measurement of the trait is labour intensive, gene markers or correlated measures are needed before it will be suitable for industry adoption. The second approach examined the impact of larval products on the immmune system of the sheep. Larvae suppress the sheep immune system and thereby limit the ability of the sheep to reject the larvae. The immunosuppresive agent is being purified and strategies to abolish its activity are being explored. Abolition of immunosuppression would create opportunities for the development of new vaccines againts blowfly strike.

Human Torque teno virus: epidemiology, cell biology and immunology

Torque teno virus (TTV) was discovered in 1997 in the serum of a Japanese patient who had a post-transfusion hepatitis of unknown etiology. It is a small virus containing a circular single-stranded DNA genome which is unique among human viruses. Within a few years after its discovery, the TTVs were noted to form a large family of viruses with numerous genotypes. TTV is highly prevalent among the general population throughout the world, and persistent infections and co-infections with several genotypes occur frequently. However, the pathogenicity and the mechanism for the sustained occurrence of the virus in blood are at present unclear. To determine the prevalence of TTV in Finland, we set up PCR methods and examined the sera of asymptomatic subjects for the presence of TTV DNA and for genotype-6 DNA. TTV was found to be highly prevalent also in Finland; 85% of adults harbored TTV in their blood, and 4% were infected with genotype-6. In addition, TTV DNA was detected in a number of different tissues, with no tissue-type or symptom specificity. Most cell-biological events during TTV infections are at the moment unknown. Replicating TTV DNA has, however, been detected in liver and the hematopoietic compartment, and three mRNAs are known to be generated. To characterize TTV cell biology in more detail, we cloned in full length the genome of TTV genotype 6. We showed that in human kidney-derived cells TTV produces altogether six proteins with distinct subcellular localizations. TTV mRNA transcription was detected in all cell lines transfected with the full-length clone, and TTV DNA replicated in several of them, including those of erythroid, kidney, and hepatic origin. Furthermore, the viral DNA replication was shown to utilize the cellular DNA polymerases. Diagnoses of TTV infections have been based almost solely on PCR, whereas serological tests, measuring antibody responses, would give more information on many aspects of these infections. To investigate the TTV immunology in more detail, we produced all six TTV proteins for use as antigens in serological tests. We detected in human sera IgM and IgG antibodies to occur simultaneously with TTV DNA, and observed appearance of TTV DNA regardless of pre-existing antibodies, and disappearance of TTV DNA after antibody appearance. The genotype-6 nucleotide sequence remained stable for years within the infected subjects, suggesting that some mechanism other than mutations is used by this minute virus to evade our immune system and to establish chronic infections in immunocompetent subjects.

Concise review: Humanized models of tumor immunology in the 21st century: Convergence of cancer research and tissue engineering

Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

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.

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.

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.

Immunology-based subspace detectors for anomaly detection

A key problem in high dimensional anomaly detection is that the time spent in constructing detectors by the means of generateand-test is tolerable. In fact, due to the high sparsity. of the data, it is ineffective to construct detectors in the whole data space. Previous investigations have shown that most essentIal patterns can be discovered in different subspaces. This inspires us to construct detectors in signIficant subspaces only for anomaly detection. We first use ENCLUS-based method to discover all significant subspaces and .then use a greedy-growth algorithm to construct detectors in each subspace. The elements used to constItute a detector are gods Instead of data points, which makes the time-consumption irrelevant to the size of the nonnal data. We test the effectiveness and efficiency of our method on both synthetic and benchmark datasets. The results reveal that our method is particularly useful in anomaly detection in high dimensional data spaces.