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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
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
Description
Background
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
ContributorsLou, Dianne I. (Author) / McBee, Ross M. (Author) / Le, Uyen Q. (Author) / Stone, Anne (Author) / Wilkerson, Gregory K. (Author) / Demogines, Ann M. (Author) / Sawyer, Sara L. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2014-07-11
Description
Background
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
ContributorsGraham, Allie M. (Author) / Munday, Michael D. (Author) / Kaftanoglu, Osman (Author) / Page, Robert (Author) / Amdam, Gro (Author) / Rueppell, Olav (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2011-04-13
Description
Background:
Iron is an essential micronutrient for all organisms because it is a component of enzyme cofactors that catalyze redox reactions in fundamental metabolic processes. Even though iron is abundant on earth, it is often present in the insoluble ferric [Fe (III)] state, leaving many surface environments Fe-limited. The haploid green alga Chlamydomonas reinhardtii is used as a model organism for studying eukaryotic photosynthesis. This study explores structural and functional changes in PSI-LHCI supercomplexes under Fe deficiency as the eukaryotic photosynthetic apparatus adapts to Fe deficiency.
Results:
77K emission spectra and sucrose density gradient data show that PSI and LHCI subunits are affected under iron deficiency conditions. The visible circular dichroism (CD) spectra associated with strongly-coupled chlorophyll dimers increases in intensity. The change in CD signals of pigments originates from the modification of interactions between pigment molecules. Evidence from sucrose gradients and non-denaturing (green) gels indicates that PSI-LHCI levels were reduced after cells were grown for 72 h in Fe-deficient medium. Ultrafast fluorescence spectroscopy suggests that red-shifted pigments in the PSI-LHCI antenna were lost during Fe stress. Further, denaturing gel electrophoresis and immunoblot analysis reveals that levels of the PSI subunits PsaC and PsaD decreased, while PsaE was completely absent after Fe stress. The light harvesting complexes were also susceptible to iron deficiency, with Lhca1 and Lhca9 showing the most dramatic decreases. These changes in the number and composition of PSI-LHCI supercomplexes may be caused by reactive oxygen species, which increase under Fe deficiency conditions.
Conclusions:
Fe deficiency induces rapid reduction of the levels of photosynthetic pigments due to a decrease in chlorophyll synthesis. Chlorophyll is important not only as a light-harvesting pigment, but also has a structural role, particularly in the pigment-rich LHCI subunits. The reduced level of chlorophyll molecules inhibits the formation of large PSI-LHCI supercomplexes, further decreasing the photosynthetic efficiency.
ContributorsYadavalli, Venkateswarlu (Author) / Jolley, Craig (Author) / Malleda, Chandramouli (Author) / Thangaraj, Balakumar (Author) / Fromme, Petra (Author) / Subramanyam, Rajagopal (Author) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Center for Bioenergy and Photosynthesis (Contributor)
Created2012-04-13
Description
Viral protein U (Vpu) is a type-III integral membrane protein encoded by Human Immunodeficiency Virus-1 (HIV- 1). It is expressed in infected host cells and plays several roles in viral progeny escape from infected cells, including down-regulation of CD4 receptors. But key structure/function questions remain regarding the mechanisms by which the Vpu protein contributes to HIV-1 pathogenesis. Here we describe expression of Vpu in bacteria, its purification and characterization. We report the successful expression of PelB-Vpu in Escherichia coli using the leader peptide pectate lyase B (PelB) from Erwinia carotovora. The protein was detergent extractable and could be isolated in a very pure form. We demonstrate that the PelB signal peptide successfully targets Vpu to the cell membranes and inserts it as a type I membrane protein. PelB-Vpu was biophysically characterized by circular dichroism and dynamic light scattering experiments and was shown to be an excellent candidate for elucidating structural models.
ContributorsDeb, Arpan (Author) / Johnson, William (Author) / Kline, Alexander (Author) / Scott, Boston (Author) / Meador, Lydia (Author) / Srinivas, Dustin (Author) / Martin Garcia, Jose Manuel (Author) / Dorner, Katerina (Author) / Borges, Chad (Author) / Misra, Rajeev (Author) / Hogue, Brenda (Author) / Fromme, Petra (Author) / Mor, Tsafrir (Author) / ASU Biodesign Center Immunotherapy, Vaccines and Virotherapy (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Biodesign Institute (Contributor) / School of Molecular Sciences (Contributor) / Applied Structural Discovery (Contributor) / Personalized Diagnostics (Contributor)
Created2017-02-22
ContributorsLuca, Michael (Author) / Yan, Hao (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Blattman, Joseph (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / School of Molecular Sciences (Contributor)
Created2024-05
Description
Cell immunotherapies have revolutionized clinical oncology. While CAR T cell therapy has been very effective in clinical studies, off-target immune toxicity limits eligible patients. Thus, NK cells have been approached with the same therapy design since NK cells have a more favorable safety profile. Therefore, the purpose of this research project is to explore DNA nanotech-based NK cell engagers (NKCEs) that force an immunological synapse between the NK cell and the cancer cell, leading to cancer death. DNA tetrabody (TB) and DNA tetrahedron (TDN) are fabricated and armed with HER2 affibody for tight adhesion to HER2+ cancer cell lines like SKBR3. Overall, relationship between TB-NK treatment and cancer cell apoptosis is still unclear. TB-NK treatment induces an apoptotic profile similar to PMA/IO stimulation. Pilot cell assay needs to be replicated with additional controls and a shortened treatment window. For DNA TDN fabrication, HER2 affibody polishing with Ni-NTA affinity chromatography achieves high purity with 20% to 100% high-imidazole elution gradient. ssDNA-HER2 affibody conjugation is optimal when ssDNA is treated with 40-fold excess sulfo-SMCC for 4 hours. In conclusion, the manufacturing of DNA-based NKCEs is rapid and streamlined, which gives these NKCEs the potential to become a ready to use immunotherapy.
ContributorsLuca, Michael (Author) / Yan, Hao (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Blattman, Joseph (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / School of Molecular Sciences (Contributor)
Created2024-05
Description
Alzheimer’s disease (AD) is projected to increase, and understanding risk and protective factors could help mitigate this increase. Deficits in Choline, a B-like vitamin, intake or issues with endogenous choline production can lead to an increased risk for AD development. To better understand the effects of endogenous choline through the lifespan in the context of Alzheimer pathology, Male and Female 3xTg-AD and NonTg mice, were aged to 16.81 ± 0.13 months. Body weight, food consumption data, and blood plasma samples were collected across the lifespan. A behavioral battery, that consisted of Rotarod, Elevated Plus Maze, and Intellicage, was performed to assess differences across a range of tasks. Hippocampal and cortical tissue were collected to assess pathology. Overall, 3xTg-AD mice had lower choline levels than NonTg at multiple timepoints and Males had higher choline than Females. Furthermore, 3xTg-AD Females had higher levels of both Aβ and Tau pathology than their Male counterparts. In the Intellicage, Females made fewer Percent of Correct Responses during Place Preference. Together these findings show that choline levels through the lifespan, impact the severity of pathology between Males and Female 3xTg-AD mice and behavioral differences between the 3xTg-AD and NonTg mouse models.
ContributorsMistry, Faizan (Author) / Velazquez, Ramon (Thesis director) / Judd, Jessica (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / School of Life Sciences (Contributor)
Created2024-05
ContributorsLuca, Michael (Author) / Yan, Hao (Thesis director) / Stephanopoulos, Nicholas (Committee member) / Blattman, Joseph (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / School of Molecular Sciences (Contributor)
Created2024-05