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Use of large, immunosignature databases to pose new questions about infection and health status

Description

Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases.

Immunosignature is a technology that retrieves information from the immune system. The technology is based on microarrays with peptides chosen from random sequence space. My thesis focuses on improving the Immunosignature platform and using Immunosignatures to improve diagnosis for diseases. I first contributed to the optimization of the immunosignature platform by introducing scoring metrics to select optimal parameters, considering performance as well as practicality. Next, I primarily worked on identifying a signature shared across various pathogens that can distinguish them from the healthy population. I further retrieved consensus epitopes from the disease common signature and proposed that most pathogens could share the signature by studying the enrichment of the common signature in the pathogen proteomes. Following this, I worked on studying cancer samples from different stages and correlated the immune response with whether the epitope presented by tumor is similar to the pathogen proteome. An effective immune response is defined as an antibody titer increasing followed by decrease, suggesting elimination of the epitope. I found that an effective immune response usually correlates with epitopes that are more similar to pathogens. This suggests that the immune system might occupy a limited space and can be effective against only certain epitopes that have similarity with pathogens. I then participated in the attempt to solve the antibiotic resistance problem by developing a classification algorithm that can distinguish bacterial versus viral infection. This algorithm outperforms other currently available classification methods. Finally, I worked on the concept of deriving a single number to represent all the data on the immunosignature platform. This is in resemblance to the concept of temperature, which is an approximate measurement of whether an individual is healthy. The measure of Immune Entropy was found to work best as a single measurement to describe the immune system information derived from the immunosignature. Entropy is relatively invariant in healthy population, but shows significant differences when comparing healthy donors with patients either infected with a pathogen or have cancer.

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Agent

Created

Date Created
2018

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Pathway Analysis Reveals Sex Differences in Human Hepatocellular Carcinoma

Description

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide and exhibits a male-bias in occurrence and mortality. Previous studies have provided insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide and exhibits a male-bias in occurrence and mortality. Previous studies have provided insight into the role of inherited genetic regulation of transcription in modulating sex-differences in HCC etiology and mortality. This study uses pathway analysis to add insight into the biological processes that drive sex-differences in HCC etiology as well as a provide additional framework for future studies on sex-biased cancers. Gene expression data from normal, tumor adjacent, and HCC liver tissue were used to calculate pathway scores using a tool called PathOlogist that not only takes into consideration the molecules in a biological pathway, but also the interaction type and directionality of the signaling pathways. Analysis of the pathway scores uncovered etiologically relevant pathways differentiating male and female HCC. In normal and tumor adjacent liver tissue, males showed higher activity of pathways related to translation factors and signaling. Females did not show higher activity of any pathways compared to males in normal and tumor adjacent liver tissue. Work suggest biologic processes that underlie sex-biases in HCC occurrence and mortality. Both males and females differed in the activation of pathways related apoptosis, cell cycle, signaling, and metabolism in HCC. These results identify clinically relevant pathways for future research and therapeutic targeting.

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Created

Date Created
2021

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Systematic Analysis of the Factors Contributing to the Variation and Change of the Microbiome

Description

Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a

Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications, citations, funding, collaborations, and other explanatory variables or contextual factors. What is observed in the microbiome, or any historical evolution of a scientific field or scientific knowledge, is that these changes are related to changes in knowledge, but what is not understood is how to measure and track changes in knowledge. This investigation highlights how contextual factors from the language and social context of the microbiome are related to changes in the usage, meaning, and scientific knowledge on the microbiome. Two interconnected studies integrating qualitative and quantitative evidence examine the variation and change of the microbiome evidence are presented. First, the concepts microbiome, metagenome, and metabolome are compared to determine the boundaries of the microbiome concept in relation to other concepts where the conceptual boundaries have been cited as overlapping. A collection of publications for each concept or corpus is presented, with a focus on how to create, collect, curate, and analyze large data collections. This study concludes with suggestions on how to analyze biomedical concepts using a hybrid approach that combines results from the larger language context and individual words. Second, the results of a systematic review that describes the variation and change of microbiome research, funding, and knowledge are examined. A corpus of approximately 28,000 articles on the microbiome are characterized, and a spectrum of microbiome interpretations are suggested based on differences related to context. The collective results suggest the microbiome is a separate concept from the metagenome and metabolome, and the variation and change to the microbiome concept was influenced by contextual factors. These results provide insight into how concepts with extensive resources behave within biomedicine and suggest the microbiome is possibly representative of conceptual change or a preview of new dynamics within science that are expected in the future.

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Date Created
2018

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Comparative genomics and novel bioinformatics methodology applied to the green anole reveal unique sex chromosome evolution

Description

In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage

In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage compensation is a process whereby genes on the sex chromosomes achieve equal gene expression which prevents deleterious side effects from having too much or too little expression of genes on sex chromsomes. The green anole is part of a group of species that recently underwent an adaptive radiation. The green anole has XX/XY sex determination, but the content of the X chromosome and its evolution have not been described. Given its status as a model species, better understanding the green anole genome could reveal insights into other species. Genomic analyses are crucial for a comprehensive picture of sex chromosome differentiation and dosage compensation, in addition to understanding speciation.

In order to address this, multiple comparative genomics and bioinformatics analyses were conducted to elucidate patterns of evolution in the green anole and across multiple anole species. Comparative genomics analyses were used to infer additional X-linked loci in the green anole, RNAseq data from male and female samples were anayzed to quantify patterns of sex-biased gene expression across the genome, and the extent of dosage compensation on the anole X chromosome was characterized, providing evidence that the sex chromosomes in the green anole are dosage compensated.

In addition, X-linked genes have a lower ratio of nonsynonymous to synonymous substitution rates than the autosomes when compared to other Anolis species, and pairwise rates of evolution in genes across the anole genome were analyzed. To conduct this analysis a new pipeline was created for filtering alignments and performing batch calculations for whole genome coding sequences. This pipeline has been made publicly available.

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Agent

Created

Date Created
2016

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A search for parent-of-origin effects in the parasitoid jewel wasp Nasonia vitripennis

Description

In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes that show a pattern of monoallelic or biased-allele expression based

In most diploid cells, autosomal genes are equally expressed from the paternal and maternal alleles resulting in biallelic expression. However, as an exception, there exists a small number of genes that show a pattern of monoallelic or biased-allele expression based on the allele’s parent-of-origin. This phenomenon is termed genomic imprinting and is an evolutionary paradox. The best explanation for imprinting is David Haig's kinship theory, which hypothesizes that monoallelic gene expression is largely the result of evolutionary conflict between males and females over maternal involvement in their offspring. One previous RNAseq study has investigated the presence of parent-of-origin effects, or imprinting, in the parasitic jewel wasp Nasonia vitripennis (N. vitripennis) and its sister species Nasonia giraulti (N. giraulti) to test the predictions of kinship theory in a non-eusocial species for comparison to a eusocial one. In order to continue to tease apart the connection between social and eusocial Hymenoptera, this study proposed a similar RNAseq study that attempted to reproduce these results in unique samples of reciprocal F1 Nasonia hybrids. Building a pseudo N. giraulti reference genome, differences were observed when aligning RNAseq reads to a N. vitripennis reference genome compared to aligning reads to a pseudo N. giraulti reference. As well, no evidence for parent-of-origin or imprinting patterns in adult Nasonia were found. These results demonstrated a species-of-origin effect. Importantly, the study continued to build a repository of support with the aim to elucidate the mechanisms behind imprinting in an excellent epigenetic model species, as it can also help with understanding the phenomenon of imprinting in complex human diseases.

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Agent

Created

Date Created
2019

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Pathways of Distinction Analysis of Liver Cancer Data: Genetic Differences Between Males and Females

Description

The Pathways of Distinction Analysis (PoDA) program calculates relationships between a given group of genes contained within a pathway, and a disease state. It was used here to investigate liver cancer, and to explore how genetic variability may contribute to

The Pathways of Distinction Analysis (PoDA) program calculates relationships between a given group of genes contained within a pathway, and a disease state. It was used here to investigate liver cancer, and to explore how genetic variability may contribute to the different rates of development of the disease in males and females. The goal of the study was to identify germline variation that differs by sex in hepatocellular carcinoma. Using the program, multiple pathways and genes were identified to have significant differences in their relationship to liver cancer in males and females. In animal studies, the genes which were identified using the PoDA analysis have been shown to impact liver cancer, often with different results for males and females. While these genes are often the focus in animal models, they are absent from current Genome Wide Association Studies (GWAS) catalogs for humans. By working to bridge the results of animal studies and human studies, the results help to identify the causes of liver cancer, and more specifically, the reason the disease affects males at much higher rates. The differences in pathways identified to be significant for the two sexes indicate the germline variance may play sex-specific roles in the development of hepatocellular carcinoma. Additionally, these results reinforce the capacity of the PoDA analysis to identify genes that may be missed by more traditional GWAS methods. This study lays the groundwork for further investigations into the identified genes and pathways, and how they behave differently within males and females.

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Agent

Created

Date Created
2021