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The first numerical predictions of the dynamical diquark model of multiquark exotic hadrons are presented. Using Born-Oppenheimer potentials calculated from lattice QCD and phenomenological diquark(triquark) masses, mass eigenvalues that are degenerate in spin and isospin are computed from numerical solutions to both coupled and uncoupled Schroedinger equations. Assuming reasonable estimates of the fine-structure splittings, we find that the band structure of our mass spectra agrees well with the experimentally observed spectrum of charmonium-like states. Using our best fits, we predict a number of unobserved states, such as pentaquark states that lie below the charmonium-plus-nucleon threshold.
ContributorsPeterson, Curtis Taylor Taylor (Author) / Lebed, Richard (Thesis director) / Belitsky, Andrei (Committee member) / Department of Physics (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Background
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
ContributorsZhang, Wenlu (Author) / Feng, Daming (Author) / Li, Rongjian (Author) / Chernikov, Andrey (Author) / Chrisochoides, Nikos (Author) / Osgood, Christopher (Author) / Konikoff, Charlotte (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ji, Shuiwang (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2013-12-28
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
In the development of personalized medicine and many other clinical studies, biospecimen integrity serves as the prerequisite for not only the accurate derivation of patient- and disease-specific molecular data from biological specimens but the meaningful downstream validation of biomarkers. However, a large number of preanalytical variables may influence the quality of biospecimens in an undesired way and ultimately render the samples unsuitable for molecular analysis. The limited ability to directly reduce discrepancies caused by preanalytical variables gives rise to the need for development and retrospective application of appropriate tests for assessment of biospecimen integrity. Nevertheless, the most standard approaches to assessing biospecimen integrity involve nontrivial procedures. Thus, the need for quality control tools or tests that are readily applicable and can produce results in a straightforward way becomes critical. As one of the major ex vivo biomolecular degradation mechanisms, oxidation that occurs when blood plasma and serum samples are exposed to thawed states during storage and processing is hard to forestall and detect. In an attempt to easily detect and monitor the degree of oxidation, the technique of Fluorescence Resonance Energy Transfer (FRET) was examined to determine whether this concept could be employed to monitor exposure of samples to thawed conditions when controlled by spontaneous oxidative disulfide bonding. The intended mode of usage was envisioned as a fluorescence liquid being stored in a separate compartment but within the same test tube as archived plasma and serum samples. This would allow the assessment of sample integrity by direct visualization of fluorescence under a hand-held black light. The fluorescent dynamic range as well as kinetic control of the reaction were studied. While the addition of Cu(II) proved to facilitate excellent dynamic range with regard to fluorescence quenching, the kinetics of the reaction were too rapid for practical use. Further investigation revealed that the fluorescence quenching mechanism might have actually occurred via Intramolecular Charge Transfer (ICT) rather than FRET mediated by oxidative disulfide bond formation. Introduction of Cu(II) via copper metal slowed fluorescence quenching to the point of practical utility; facilitating demonstration that storing at room temperature, refrigerating or freezing the samples delayed fluorescence quenching to different extents. To establish better kinetic control, future works will focus on establishing controlled, thoroughly understood kinetic release of Cu(II) from copper metal.
ContributorsZhang, Zihan (Author) / Borges, Chad (Thesis director) / Emady, Heather (Committee member) / Williams, Peter (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Biomarkers are the cornerstone of modern-day medicine. They are defined as any biological substance in or outside the body that gives insight to the body's condition. Doctors and researchers can measure specific biomarkers to diagnose and treat patients, such as the concentration of hemoglobin Alc and its connection to diabetes. There are a variety of methods, or assays, to detect biomarkers, but the most common assay is enzyme-linked immunosorbent assay (ELISA). A new-generation assay termed mass spectrometric immunoassay (MSIA) can measure proteoforms, the different chemical variations of proteins, and their relative abundance. ELISA on the other hand measures the overall concentration of protein in the sample. Measuring each of the proteoforms of a protein is important because only one or two variations could be biologically significant and/or cause diseases. However, running MSIA is expensive. For this reason, an alternative plate-based MSIA technique was tested for its ability to detect the proteoforms of a protein called apolipoprotein C-III (ApoC-III). This technique combines the protein capturing procedure of ELISA to isolate the protein with detection in a mass spectrometer. A larger amount of ApoC-III present in the body indicates a considerable risk for coronary heart disease. The precision of the assay is determined on the coefficient of variation (CV). A CV value is the ratio of standard deviation in relation to the mean, represented as a percentage. The smaller the percentage, the less variation the assay has, and therefore the more ability it has to detect subtle changes in the biomarker. An accepted CV would be less than 10% for single-day tests (intra-day) and less than 15% for multi-day tests (inter-day). The plate-based MSIA was started by first coating a 96-well round bottom plate with 2.5 micrograms of ApoC-III antibody. Next, a series of steps were conducted: a buffer wash, then the sample incubation, followed by another buffer wash and two consecutive water washes. After the final wash, the wells were filled with a MALDI matrix, then spotted onto a gold plate to dry. The dry gold target was then placed into a MALDI-TOF mass spectrometer to produce mass spectra for each spot. The mass spectra were calibrated and the area underneath each of the four peaks representing the ApoC-III proteoforms was exported as an Excel file. The intra-day CV values were found by dividing the standard deviation by the average relative abundance of each peak. After repeating the same procedure for three more days, the inter-day CVs were found using the same method. After completing the experiment, the CV values were all within the acceptable guidelines. Therefore, the plate-based MSIA is a viable alternative for finding proteoforms than the more expensive MSIA tips. To further validate this, additional tests will need to be conducted with different proteins and number of samples to determine assay flexibility.
ContributorsTieu, Luc (Author) / Borges, Chad (Thesis director) / Nedelkov, Dobrin (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Brown adipose tissue (BAT) is thought to be important in combating obesity as it can expend energy in the form of heat, e.g. thermogenesis. The goal of this study was to study the effect of injected norepinephrine (NE) on the activation of BAT in rats that were fed a high fat diet (HFD). A dose of 0.25 mg/kg NE was used to elicit a temperature response that was measured using transponders inserted subcutaneously over the BAT and lower back and intraperitoneally to measure the core temperature. The results found that the thermic effect of the BAT increased after the transition from low fat diet to a high fat diet (LFD) yet, after prolonged exposure to the HFD, the effects resembled levels found with the LFD. This suggests that while a HFD may stimulate the effect of BAT, long term exposure may have adverse effects on BAT activity. This may be due to internal factors that will need to be examined further.
ContributorsSion, Paul William (Author) / Herman, Richard (Thesis director) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Coronaviruses are a significant group of viruses that cause enteric and respiratory infections in a variety of animals, including humans. Outbreaks of Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS) in the past 15 years has increased research into coronaviruses to gain an understanding of their structure and function so one day therapies and vaccines may be produced. These viruses have four main structural proteins: the spike, nucleocapsid, envelope, and membrane proteins. The envelope (E) protein is an integral membrane protein in the viral envelope that acts as a viroporin for transport of cations and plays an important role in pathogenesis and viral assembly. E contains a hydrophobic transmembrane domain with polar residues that is conserved across coronavirus species and may be significant to its function. This experiment looks at the possible role of one polar residue in assembly, the 15th residue glutamine, in the Mouse Hepatitis Virus (MHV) E protein. The glutamine 15 residue was mutated into positively charged residues lysine or arginine. Plasmids with these mutations were co-expressed with the membrane protein (M) gene to produce virus-like particles (VLPs). VLPs are produced when E and M are co-expressed together and model assembly of the coronavirus envelope, but they are not infectious as they do not contain the viral genome. Observing their production with the mutated E protein gives insight into the role the glutamine residue plays in assembly. The experiment showed that a changing glutamine 15 to positive charges does not appear to significantly affect the assembly of the VLPs, indicating that this specific residue may not have a large impact on viral assembly.
ContributorsHaller, Sarah S. (Author) / Hogue, Brenda (Thesis director) / Liu, Wei (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor) / Biodesign Institute (Contributor)
Created2017-05
Description
Almost every form of cancer deregulates the expression and activity of anabolic glycosyltransferase (GT) enzymes, which incorporate particular monosaccharides in a donor acceptor as well as linkage- and anomer-specific manner to assemble complex and diverse glycans that significantly affect numerous cellular events, including tumorigenesis and metastasis. Because glycosylation is not template-driven, GT deregulation yields heterogeneous arrays of aberrant intact glycan products, some in undetectable quantities in clinical bio-fluids (e.g., blood plasma). Numerous glycan features (e.g., 6 sialylation, β-1,6-branching, and core fucosylation) stem from approximately 25 glycan “nodes:” unique linkage specific monosaccharides at particular glycan branch points that collectively confer distinguishing features upon glycan products. For each node, changes in normalized abundance (Figure 1) may serve as nearly 1:1 surrogate measure of activity for culpable GTs and may correlate with particular stages of carcinogenesis. Complementary to traditional top down glycomics, the novel bottom-up technique applied herein condenses each glycan node and feature into a single analytical signal, quantified by two GC-MS instruments: GCT (time-of-flight analyzer) and GCMSD (transmission quadrupole analyzers). Bottom-up analysis of stage 3 and 4 breast cancer cases revealed better overall precision for GCMSD yet comparable clinical performance of both GC MS instruments and identified two downregulated glycan nodes as excellent breast cancer biomarker candidates: t-Gal and 4,6-GlcNAc (ROC AUC ≈ 0.80, p < 0.05). Resulting from the activity of multiple GTs, t-Gal had the highest ROC AUC (0.88) and lowest ROC p‑value (0.001) among all analyzed nodes. Representing core-fucosylation, glycan node 4,6-GlcNAc is a nearly 1:1 molecular surrogate for the activity of α-(1,6)-fucosyltransferase—a potential target for cancer therapy. To validate these results, future projects can analyze larger sample sets, find correlations between breast cancer stage and changes in t-Gal and 4,6-GlcNAc levels, gauge the specificity of these nodes for breast cancer and their potential role in other cancer types, and develop clinical tests for reliable breast cancer diagnosis and treatment monitoring based on t-Gal and 4,6-GlcNAc.
ContributorsZaare, Sahba (Author) / Borges, Chad (Thesis director) / LaBaer, Joshua (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Aberrant glycosylation has been shown to be linked to specific cancers, and using this idea, it was proposed that the levels of glycans in the blood could predict stage I adenocarcinoma. To track this glycosylation, glycan were broken down into glycan nodes via methylation analysis. This analysis utilized information from N-, O-, and lipid linked glycans detected from gas chromatography-mass spectrometry. The resulting glycan node-ratios represent the initial quantitative data that were used in this experiment.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
ContributorsDe Jesus, Celine Spicer (Author) / Taylor, Thomas (Thesis director) / Borges, Chad (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Disturbances in the protein interactome often play a large role in cancer progression. Investigation of protein-protein interactions (PPI) can increase our understanding of cancer pathways and will disclose unknown targets involved in cancer disease biology. Although numerous methods are available to study protein interactions, most platforms suffer from drawbacks including high false positive rates, low throughput, and lack of quantification. Moreover, most methods are not compatible for use in a clinical setting. To address these limitations, we have developed a multiplexed, in-solution protein microarray (MISPA) platform with broad applications in proteomics. MISPA can be used to quantitatively profile PPIs and as a robust technology for early detection of cancers. This method utilizes unique DNA barcoding of individual proteins coupled with next generation sequencing to quantitatively assess interactions via barcode enrichment. We have tested the feasibility of this technology in the detection of patient immune responses to oropharyngeal carcinomas and in the discovery of novel PPIs in the B-cell receptor (BCR) pathway. To achieve this goal, 96 human papillomavirus (HPV) antigen genes were cloned into pJFT7-cHalo (99% success) and pJFT7-n3xFlag-Halo (100% success) expression vectors. These libraries were expressed via a cell-free in vitro transcription-translation system with 93% and 96% success, respectively. A small-scale study of patient serum interactions with barcoded HPV16 antigens was performed and a HPV proteome-wide study will follow using additional patient samples. In addition, 15 query proteins were cloned into pJFT7_nGST expression vectors, expressed, and purified with 93% success to probe a library of 100 BCR pathway proteins and detect novel PPIs.
ContributorsRinaldi, Capria Lakshmi (Author) / LaBaer, Joshua (Thesis director) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12