Indiana University-Purdue University Indianapolis (IUPUI) / The post genomic era has propelled us to the view that the biological systems are complex network of interacting genes, proteins and small molecules that give rise to biological form and function. The past decade has seen the advent of number of new technologies designed to study the biological systems on a genome wide scale. These new technologies offers an insight in to the activity of thousands of genes and proteins in cell thereby changed the conventional reductionist view of the systems. However the deluge of data surpasses the analytical and critical abilities of the researches and thereby demands the development of new computational methods. The challenge no longer lies in the acquisition of expression profiles, but rather in the interpretation for the results to gain insights into biological mechanisms. In three different case studies, we applied various system biology techniques on publicly available and in-house genomics and proteomics data set to identify sub-network signatures. In First study, we integrated prior knowledge from gene signatures, GSEA and gene/protein network modeling to identify pathways involved in colorectal cancer, while in second, we identified plasma based network signatures for Alzheimer's disease by combining various feature selection and classification approach. In final study, we did an integrated miRNA-mRNA analysis to identify the role of Myeloid Derived Stem Cells (MDSCs) in T-Cell suppression.

Single-Cell Proteomics (SCP) can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. In addition to achieving in-depth proteome coverage from single cells, higher throughput measurements enable large-scale and statistically significant features within single cell populations. This dissertation focuses on method development to improve the sensitivity and throughput of SCP based on the nanoPOTS (nanodroplet Processing in One pot for Trace Samples) platform. The methods discussed here include miniaturization of bottom-up proteome sample preparation and liquid chromatography (LC) separations, implementation of an ultrasensitive latest-generation mass spectrometer, development of automated sample handling workflow, and combination of isotopic and isobaric labeling for higher order multiplexing. The miniaturization of sample preparation largely reduced protein loss during sample preparation and enabled in-depth single-cell proteomics. The sensitivity was further improved using a 20-μm-i.d. in-house-packed nanoLC column and the latest generation Orbitrap Eclipse Tribrid mass spectrometer. A >70% increase in proteome coverage was observed for single cells relative to previous efforts using a 30-μm-i.d. LC columns coupled to a previous-generation Orbitrap Fusion Lumos mass spectrometer. To make SCP and low-input proteome profiling accessible to more proteomics laboratories, a fully automated platform termed autoPOTS (automated Preparation in One pot for Trace Samples) was developed using only commercially available instrumentation for sample processing and analysis. AutoPOTS can be used to analyze 1–500 cells with a modest reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to the nanoliter preparation. To improve the throughput of SCP, a hyperplexing sample preparation and analysis method for Single-Cell Proteomics (hyperSCP) was developed using a combination of isotopic and isobaric labeling. This method can improve the throughput by at least 28 times with the same gradient compared to the label-free proteomics and can double or triple the throughput of standard tandem mass tag multiplexing.

<p>In this work, I present four studies across the range of 'omics data types - a Genome- Wide Association Study for gene-by-sex interaction of obesity traits, computational models for transcription start site classification, an assessment of reference-based mapping methods for RNA-Seq data from non-model organisms, and a statistical model for open-platform proteomics data alignment.</p><p>Obesity is an increasingly prevalent and severe health concern with a substantial heritable component, and marked sex differences. We sought to determine if the effect of genetic variants also differed by sex by performing a genome-wide association study modeling the effect of genotype-by-sex interaction on obesity phenotypes. Genotype data from individuals in the Framingham Heart Study Offspring cohort were analyzed across five exams. Although no variants showed genome-wide significant gene-by-sex interaction in any individual exam, four polymorphisms displayed a consistent BMI association (P-values .00186 to .00010) across all five exams. These variants were clustered downstream of LYPLAL1, which encodes a lipase/esterase expressed in adipose tissue, a locus previously identified as having sex-specific effects on central obesity. Primary effects in males were in the opposite direction as females and were replicated in Framingham Generation 3. Our data support a sex-influenced association between genetic variation at the LYPLAL1 locus and obesity-related traits.</p><p>The application of deep sequencing to map 5' capped transcripts has confirmed the existence of at least two distinct promoter classes in metazoans: focused promot- ers with transcription start sites (TSSs) that occur in a narrowly defined genomic span and dispersed promoters with TSSs that are spread over a larger window. Pre- vious studies have explored the presence of genomic features, such as CpG islands and sequence motifs, in these promoter classes, and our collaborators recently inves- tigated the relationship with chromatin features. It was found that promoter classes are significantly differentiated by nucleosome organization and chromatin structure. Here, we present computational models supporting the stronger contribution of chro- matin features to the definition of dispersed promoters compared to focused start sites. Specifically, dispersed promoters display enrichment for well-positioned nucleosomes downstream of the TSS and a more clearly defined nucleosome free region upstream, while focused promoters have a less organized nucleosome structure, yet higher presence of RNA polymerase II. These differences extend to histone vari- ants (H2A.Z) and marks (H3K4 methylation), as well as insulator binding (such as CTCF), independent of the expression levels of affected genes.</p><p>The application of next-generation sequencing technology to gene expression quantification analysis, namely, RNA-Sequencing, has transformed the way in which gene expression studies are conducted and analyzed. These advances are of partic- ular interest to researchers studying non-model organisms, as the need for knowl- edge of sequence information is overcome. De novo assembly methods have gained widespread acceptance in the RNA-Seq community for non-model organisms with no true reference genome or transcriptome. While such methods have tremendous utility, computational complexity is still a significant challenge for organisms with large and complex genomes. Here we present a comparison of four reference-based mapping methods for non-human primate data. We explore mapping efficacy, correlation between computed expression values, and utility for differential expression analyses. We show that reference-based mapping methods indeed have utility in RNA-Seq analysis of mammalian data with no true reference, and that the details of mapping methods should be carefully considered when doing so. We find that shorter seed sequences, allowance of mismatches, and allowance of gapped alignments, in addition to splice junction gaps result in more sensitive alignments of non-human primate RNA-Seq data.</p><p>Open-platform proteomics experiments seek to quantify and identify the proteins present in biological samples. Much like differential gene expression analyses, it is often of interest to determine how protein abundance differs in various physiological conditions. Label free LC-MS/MS enables the rapid measurement of thousands of proteins, providing a wealth of peptide intensity information for differential analysis. However, the processing of raw proteomics data poses significant challenges that must be overcome prior to analysis. We specifically address the matching of peptide measurements across samples - an essential pre-processing step in every proteomics experiment. Presented here is a novel method for open-platform proteomics data alignment with the ability to incorporate previously unused aspects of the data, particularly ion mobility drift times and product ion data. Our results suggest that the inclusion of additional data results in higher numbers of more confident matches, without increasing the number of mismatches. We also show that the incorporation of product ion data can improve results dramatically. Based on these results, we argue that the incorporation of ion mobility drift times and product ion information are worthy pursuits. In addition, alignment methods should be flexible enough to utilize all available data, particularly with recent advancements in experimental separation methods. The addition of drift times and/or high energy to alignment methods and accurate mass and time (AMT) tag databases can greatly improve experimenters ability to identify measured peptides, reducing analysis costs and potentially the need to run additional experiments.</p> / Dissertation

Exosomes are small lipid membrane bound vesicles formed as part of the endosomal pathway and released into the extracellular space following fusion of late endosomes with the plasma membrane. Exosomes have been shown to have a variety of biological roles and may represent a novel source of disease biomarkers. The objectives of this project were to develop a panel of techniques for identifying exosomes in human urine then establish an in vitro model to determine whether exosomes change with cellular activation. We then used the techniques developed with human urine to determine whether human cerebrospinal fluid (CSF) contains exosomes and applied a mass spectrometry based approach to characterise the exosomal proteome. We used western blot for three exosomal markers (tsg101, CD24 and flotillin- 1), isopycnic centrifugation on a sucrose density gradient and direct visualisation using transmission electron microscopy (TEM) to verify the presence of exosomes. Using GeLC-MS/MS, 88 proteins were identified in the urinary exosomes. Several of these proteins could be linked to diseases and specific sections of the nephron. A murine cortical collecting duct cell line was used to model exosome release into the urine. Firstly, exosome release was verified using the approach developed in the urine. Stimulation of the cells with desmopressin caused an increase in the presence of aquaporin 2 in the exosomes. This increase reflected a similar change in the cells and occurred over a similar time course. This supports the hypothesis that the exosomes reflect the state of the kidney cells. In contrast, stimulation with cisplatin did not alter the presence of Fetuin-A, a proposed biomarker of cisplatin-induced acute kidney injury, in exosomes and this was consistent with no change in Fetuin- A expression in the cells. The released exosomes may act as mediators of communication to other cells. Following incubation of mCCD cells with AQP2 containing exosomes AQP2 in the cell lysate was increased indicating interaction between the cells and exosomes and potentially internalisation. Exosomes have been shown to be released by neuronal cells in vitro. We identified exosomes in the CSF of humans using western blot for known exosomal markers, density determination and direct visualisation with TEM and Immuno-TEM using an antibody specific for the exosomal marker flotillin-1. Label-free quantitative mass spectrometry was used to compare multiple CSF samples. On a whole protein analysis 86% of the proteins identified varied by less than 2-fold in comparison to the average across samples. On a tryptic peptide analysis 75% of the peptides identified varied by less than 2-fold in comparison with the average across samples. We have demonstrated exosomes are present in urine, CSF and mCCD cell conditioned media. In the mCCD cell derived exosomes we have demonstrated that following stimulation the proteome of the exosomes changes and that this change reflects the change seen in the cells. For the urinary and CSF exosomes we have characterised their proteomes using GeLC-MS/MS. These findings are consistent with the hypothesis that exosomes are a rich source of information, including biomarkers, on their cells of origin.

The influenza virus has a large impact on global health; however, it is difficult to formulate vaccines and influenza therapies that are effective against influenza. The influenza virus mutates rapidly, has the ability to emerge as novel strains with pandemic potential and can quickly become resistant to any given drug. Therefore, the generation of novel anti-influenza therapeutics that are effective against multiple strains would be highly beneficial. To date, the majority of anti-influenza research has focused on targeting specific components of the virus in order to interfere with its replication. However, it has been proposed that host proteins and signaling pathways may be essential components to viral replication and could also become novel anti-influenza drug targets. Therefore, this study utilized a large proteomic screen to identify host proteins that were up- and down-regulated in response to influenza infection. Collectively, these proteins clustered into five specific cell pathways and processes including interferon signaling, purine metabolism, cell death, ubiquitin-like signaling and mitochondrial oxidoreductases. Overall, this project identified potential novel anti-influenza targets in primary airway epithelial cells. / May 2015

published_or_final_version / abstract / Surgery / Doctoral / Doctor of Philosophy

published_or_final_version / Biological Sciences / Doctoral / Doctor of Philosophy

Streptococcus pneumoniae is a highly diverse and adaptable opportunistic pathogen that can infect and colonise different niches within the human host to cause a wide range of invasive disease (sepsis and meningitis) and noninvasive disease (pneumonia, otitis media and sinusitis). The molecular mechanisms that contribute to the different patterns of pneumococcal infection remain largely unknown. This thesis aims to determine the physiological and proteomic responses that allow the pneumococcus to survive and adapt to invasive and non-invasive sites. The comparative proteomic analyses of clinical S. pneumoniae isolates recovered from blood cultures (classified as invasive site isolates) and mucosal surfaces such as sputum, skin and ear swabs (classified as non-invasive site isolates) was initiated. The pneumococci were grown in vitro under standard conditions and the total cellular bacterial proteins extracted and analysed using both gel based and non-gel based proteomic approaches. Analysis of the pneumococcal isolates by two-dimensional polyacrylamide gel electrophoresis (2DGE) revealed that a high degree of heterogeneity existed between the pneumococcal isolates particularly among isolates in the invasive site isolates. Differential patterns of protein synthesis were observed that discriminated the pneumococcal isolates according to their sites of isolation. These were proposed to be associated with the bacterial adaptation to invasive and non-invasive sites of infection. Mass spectrometry was used to identify selected significant (ANOVA, p < 0.05) protein spots, which were further categorised into functional groups by Gene Ontology analysis. An extension of the 2DGE data using an integrated approach comprising bioinformatics, surfome analysis and a shotgun proteomic workflow provided a comprehensive qualitative and quantitative analyses of the pneumococcal intracellular and cell-surface proteomes. Proteins potentially involved in pneumococcal niche-specific adaptation and surface proteins with potential for further investigation and inclusion in the pipeline of vaccine candidates were identified. Quantitative regulation of proteins involved in energy metabolism, genetic competence, stress response, surface adhesion and virulence were considered important for pneumococcal adaptation to invasive and non-invasive sites. The anatomical sites colonised by the pneumococcus vary in their V availability for iron. The 2DGE method was also used on selected pneumococcal isolates from the two sites of infection to define the proteome variability linked to the effect of iron starvation that may contribute to the different disease outcomes associated with pneumococcal infections. The iron restricted condition was generated by cation depletion of the growth medium using Chelex-100. Quantitative differences in protein abundance were demonstrated that correlated with pneumococcal adaptation to iron restriction. The identification of selected significant spots by liquid chromatography-mass spectrometry and systems biology analysis of the identified proteins contributed to the elucidation of the molecular mechanisms underlying pneumococcal survival under iron limitation. The expression/repression of proteins functionally associated with metal ion binding, oxidative stress response, translation and virulence mainly constituted the pneumococcal adaptive responses to growth under conditions of limited iron availability. The data presented in this thesis extended our understanding of the molecular events underlying pneumococcal physiological adaptation and provide the basis of future work in this area.

The neuropathological process in Alzheimer's disease (AD) is characterized by both intra and extracellular Aβ42 aggregates. The neuropathological process of AD is complex and the exact cause of Aβ aggregation leading towards neuronal death is yet unknown. Several events are implicated towards the development of AD including changes within the proteome. With more than 30 million people currently affected with AD, there is still no cure for AD. In this project we seek to identify differential protein profiles by undertaking a comparative analysis of the intracellular and extracellular effects of Aβ on the human proteome using two cellular neuronal models: MC65 and SHSY5Y cells, to understand the biochemical pathology underlying AD. We also initiated a compound screening approach which not only identified several small molecules and peptides inhibiting the Aβ cytotoxicity, but also identified several known compounds from the LOPAC library acting as potential inhibitors of intra and extracellular Aβ42 cytotoxicity, thus highlighting the importance of drug repositioning to identify novel compounds in the therapeutic regime of AD which could be categorized as Aβ toxicity inhibitors. A comparative qualitative proteomics approach was undertaken using OFFGEL fractionation. The MS data was analysed through GO, biological pathway and protein interaction analysis using various databases such as UniProtKB, DAVID v6.7, KEGG and String 9.0 for the SHSY5Y cells treated with extracellular Aβ42 and MC65 cells which conditionally express intracellular C99, that is further cleaved to intracellular Aβ. This was followed by validation of 8 proteins by in-cell Western assay (ICW) undertaken using the LI-COR Infrared Imaging System for the cell lysates of control and Aβ42 treated SH-SY5Y as well as Aβ induced MC65 cells. We have also screened a library of 1280 LOPAC compounds on both the cell lines and 9 other compounds previously known as Aβ toxicity inhibitors on MC65 cells. The lead compounds were further characterized using MTT, LDH, ThT and ICW assays. The proteomics methodology undertaken through this project identified several novel proteins specific to intracellular and extracellular Aβ aggregation. The GO, biological pathway analysis and the functional interaction study helped to identify proteins associated from the proteasome pathway to be affected as an effect of Aβ aggregation for both the cells exposed with intra and extracellular Aβ aggregation. The compound screening study also identified several compounds as inhibitors of Aβ cytotoxicity. A-77636, a D1 dopamine receptor agonist was identified as a lead compound to reduce the extracellular Aβ42 cytotoxicity at nM concentration. Moreover, 1,3-Diethyl-8-phenylxanthine and Arecaidine propargyl ester hydrobromide also proved successful in attenuating the extracellular Aβ42 cytotoxicity. Apart from this; SEN1000, SEN304 and Scylloinositol were able to completely attenuate the intracellular Aβ cytotoxicity, whereas two other compounds, 1,3-Dipropyl-8-p-sulfophenylxanthine and 3-Bromo-7-nitroindazole from the LOPAC library proved effective in acting as partial inhibitors of intracellular Aβ aggregation induced cytotoxicity. The ADME profile for most of these compounds is acceptable, therefore these can be considered as therapeutic leads for AD in the future.

T V Gale