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- Member of: ASU Regents' Professors Open Access Works
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Description
Background
This study investigated the number of pedometer assessment occasions required to establish habitual physical activity in African American adults.
Methods
African American adults (mean age 59.9 ± 0.60 years; 59 % female) enrolled in the Diet and Physical Activity Substudy of the Jackson Heart Study wore Yamax pedometers during 3-day monitoring periods, assessed on two to three distinct occasions, each separated by approximately one month. The stability of pedometer measured PA was described as differences in mean steps/day across time, as intraclass correlation coefficients (ICC) by sex, age, and body mass index (BMI) category, and as percent of participants changing steps/day quartiles across time.
Results
Valid data were obtained for 270 participants on either two or three different assessment occasions. Mean steps/day were not significantly different across assessment occasions (p values > 0.456). The overall ICCs for steps/day assessed on either two or three occasions were 0.57 and 0.76, respectively. In addition, 85 % (two assessment occasions) and 76 % (three assessment occasions) of all participants remained in the same steps/day quartile or changed one quartile over time.
Conclusion
The current study shows that an overall mean steps/day estimate based on a 3-day monitoring period did not differ significantly over 4 – 6 months. The findings were robust to differences in sex, age, and BMI categories. A single 3-day monitoring period is sufficient to capture habitual physical activity in African American adults.
This study investigated the number of pedometer assessment occasions required to establish habitual physical activity in African American adults.
Methods
African American adults (mean age 59.9 ± 0.60 years; 59 % female) enrolled in the Diet and Physical Activity Substudy of the Jackson Heart Study wore Yamax pedometers during 3-day monitoring periods, assessed on two to three distinct occasions, each separated by approximately one month. The stability of pedometer measured PA was described as differences in mean steps/day across time, as intraclass correlation coefficients (ICC) by sex, age, and body mass index (BMI) category, and as percent of participants changing steps/day quartiles across time.
Results
Valid data were obtained for 270 participants on either two or three different assessment occasions. Mean steps/day were not significantly different across assessment occasions (p values > 0.456). The overall ICCs for steps/day assessed on either two or three occasions were 0.57 and 0.76, respectively. In addition, 85 % (two assessment occasions) and 76 % (three assessment occasions) of all participants remained in the same steps/day quartile or changed one quartile over time.
Conclusion
The current study shows that an overall mean steps/day estimate based on a 3-day monitoring period did not differ significantly over 4 – 6 months. The findings were robust to differences in sex, age, and BMI categories. A single 3-day monitoring period is sufficient to capture habitual physical activity in African American adults.
ContributorsNewton, Robert L. (Author) / Han, Hongmei (Author) / Dubbert, Patricia M. (Author) / Johnson, William D. (Author) / Hickson, DeMarc A. (Author) / Ainsworth, Barbara (Author) / Carithers, Teresa (Author) / Taylor, Herman (Author) / Wyatt, Sharon (Author) / Tudor-Locke, Catrine (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2012-04-18
Description
Background
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.
Methods
A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.
Results
A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.
Conclusions
Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.
Neighborhood environment studies of physical activity (PA) have been mainly single-country focused. The International Prevalence Study (IPS) presented a rare opportunity to examine neighborhood features across countries. The purpose of this analysis was to: 1) detect international neighborhood typologies based on participants’ response patterns to an environment survey and 2) to estimate associations between neighborhood environment patterns and PA.
Methods
A Latent Class Analysis (LCA) was conducted on pooled IPS adults (N=11,541) aged 18 to 64 years old (mean=37.5 ±12.8 yrs; 55.6% women) from 11 countries including Belgium, Brazil, Canada, Colombia, Hong Kong, Japan, Lithuania, New Zealand, Norway, Sweden, and the U.S. This subset used the Physical Activity Neighborhood Environment Survey (PANES) that briefly assessed 7 attributes within 10–15 minutes walk of participants’ residences, including residential density, access to shops/services, recreational facilities, public transit facilities, presence of sidewalks and bike paths, and personal safety. LCA derived meaningful subgroups from participants’ response patterns to PANES items, and participants were assigned to neighborhood types. The validated short-form International Physical Activity Questionnaire (IPAQ) measured likelihood of meeting the 150 minutes/week PA guideline. To validate derived classes, meeting the guideline either by walking or total PA was regressed on neighborhood types using a weighted generalized linear regression model, adjusting for gender, age and country.
Results
A 5-subgroup solution fitted the dataset and was interpretable. Neighborhood types were labeled, “Overall Activity Supportive (52% of sample)”, “High Walkable and Unsafe with Few Recreation Facilities (16%)”, “Safe with Active Transport Facilities (12%)”, “Transit and Shops Dense with Few Amenities (15%)”, and “Safe but Activity Unsupportive (5%)”. Country representation differed by type (e.g., U.S. disproportionally represented “Safe but Activity Unsupportive”). Compared to the Safe but Activity Unsupportive, two types showed greater odds of meeting PA guideline for walking outcome (High Walkable and Unsafe with Few Recreation Facilities, OR= 2.26 (95% CI 1.18-4.31); Overall Activity Supportive, OR= 1.90 (95% CI 1.13-3.21). Significant but smaller odds ratios were also found for total PA.
Conclusions
Meaningful neighborhood patterns generalized across countries and explained practical differences in PA. These observational results support WHO/UN recommendations for programs and policies targeted to improve features of the neighborhood environment for PA.
ContributorsAdams, Marc (Author) / Ding, Ding (Author) / Sallis, James F. (Author) / Bowles, Heather R. (Author) / Ainsworth, Barbara (Author) / Bergman, Patrick (Author) / Bull, Fiona C. (Author) / Carr, Harriette (Author) / Craig, Cora L. (Author) / De Bourdeaudhuij, Ilse (Author) / Fernando Gomez, Luis (Author) / Hagstromer, Maria (Author) / Klasson-Heggebo, Lena (Author) / Inoue, Shigeru (Author) / Lefevre, Johan (Author) / Macfarlane, Duncan J. (Author) / Matsudo, Sandra (Author) / Matsudo, Victor (Author) / McLean, Grant (Author) / Murase, Norio (Author) / Sjostrom, Michael (Author) / Tomten, Heidi (Author) / Volbekiene, Vida (Author) / Bauman, Adrian (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-03-07
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 School of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Background
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2013-12-03
Description
Diacylglycerol kinase catalyses the ATP-dependent conversion of diacylglycerol to phosphatidic acid in the plasma membrane of Escherichia coli. The small size of this integral membrane trimer, which has 121 residues per subunit, means that available protein must be used economically to craft three catalytic and substrate-binding sites centred about the membrane/cytosol interface. How nature has accomplished this extraordinary feat is revealed here in a crystal structure of the kinase captured as a ternary complex with bound lipid substrate and an ATP analogue. Residues, identified as essential for activity by mutagenesis, decorate the active site and are rationalized by the ternary structure. The γ-phosphate of the ATP analogue is positioned for direct transfer to the primary hydroxyl of the lipid whose acyl chain is in the membrane. A catalytic mechanism for this unique enzyme is proposed. The active site architecture shows clear evidence of having arisen by convergent evolution.
ContributorsLi, Dianfan (Author) / Stansfeld, Phillip J. (Author) / Sansom, Mark S. P. (Author) / Keogh, Aaron (Author) / Vogeley, Lutz (Author) / Howe, Nicole (Author) / Lyons, Joseph A. (Author) / Aragao, David (Author) / Fromme, Petra (Author) / Fromme, Raimund (Author) / Basu, Shibom (Author) / Grotjohann, Ingo (Author) / Kupitz, Christopher (Author) / Rendek, Kimberley (Author) / Weierstall, Uwe (Author) / Zatsepin, Nadia (Author) / Cherezov, Vadim (Author) / Liu, Wei (Author) / Bandaru, Sateesh (Author) / English, Niall J. (Author) / Gati, Cornelius (Author) / Barty, Anton (Author) / Yefanov, Oleksandr (Author) / Chapman, Henry N. (Author) / Diederichs, Kay (Author) / Messerschmidt, Marc (Author) / Boutet, Sebastien (Author) / Williams, Garth J. (Author) / Seibert, M. Marvin (Author) / Caffrey, Martin (Author) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / Department of Physics (Contributor)
Created2015-12-17
Description
Large quantities of sodic and alkaline bauxite residue are produced globally as a by-product from alumina refineries. Ecological stoichiometry of key elements [nitrogen (N) and phosphorus (P)] plays a critical role in establishing vegetation cover in bauxite residue sand (BRS). Here we examined how changes in soil chemical properties over time in rehabilitated sodic and alkaline BRS affected leaf N to P stoichiometry of native species used for rehabilitation. Both Ca and soil pH influenced the shifts in leaf N:P ratios of the study species as supported by consistently significant positive relationships (P < 0.001) between these soil indices and leaf N:P ratios. Shifts from N to P limitation were evident for N-fixing species, while N limitation was consistently experienced by non-N-fixing plant species. In older rehabilitated BRS embankments, soil and plant indices (Ca, Na, pH, EC, ESP and leaf N:P ratios) tended to align with those of the natural ecosystem, suggesting improved rehabilitation performance. These findings highlight that leaf N:P stoichiometry can effectively provide a meaningful assessment on understanding nutrient limitation and productivity of native species used for vegetating highly sodic and alkaline BRS, and is a crucial indicator for assessing ecological rehabilitation performance.
ContributorsGoloran, Johnvie B. (Author) / Chen, Chengrong (Author) / Phillips, Ian R. (Author) / Elser, James (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-10-07
Description
Phytochromes are a family of photoreceptors that control light responses of plants, fungi and bacteria. A sequence of structural changes, which is not yet fully understood, leads to activation of an output domain. Time-resolved serial femtosecond crystallography (SFX) can potentially shine light on these conformational changes. Here we report the room temperature crystal structure of the chromophore-binding domains of the Deinococcus radiodurans phytochrome at 2.1 Å resolution. The structure was obtained by serial femtosecond X-ray crystallography from microcrystals at an X-ray free electron laser. We find overall good agreement compared to a crystal structure at 1.35 Å resolution derived from conventional crystallography at cryogenic temperatures, which we also report here. The thioether linkage between chromophore and protein is subject to positional ambiguity at the synchrotron, but is fully resolved with SFX. The study paves the way for time-resolved structural investigations of the phytochrome photocycle with time-resolved SFX.
ContributorsEdlund, Petra (Author) / Takala, Heikki (Author) / Claesson, Elin (Author) / Henry, Leocadie (Author) / Dods, Robert (Author) / Lehtivuori, Heli (Author) / Panman, Matthijs (Author) / Pande, Kanupriya (Author) / White, Thomas (Author) / Nakane, Takanori (Author) / Berntsson, Oskar (Author) / Gustavsson, Emil (Author) / Bath, Petra (Author) / Modi, Vaibhav (Author) / Roy Chowdhury, Shatabdi (Author) / Zook, James (Author) / Berntsen, Peter (Author) / Pandey, Suraj (Author) / Poudyal, Ishwor (Author) / Tenboer, Jason (Author) / Kupitz, Christopher (Author) / Barty, Anton (Author) / Fromme, Petra (Author) / Koralek, Jake D. (Author) / Tanaka, Tomoyuki (Author) / Spence, John (Author) / Liang, Mengning (Author) / Hunter, Mark S. (Author) / Boutet, Sebastien (Author) / Nango, Eriko (Author) / Moffat, Keith (Author) / Groenhof, Gerrit (Author) / Ihalainen, Janne (Author) / Stojkovic, Emina A. (Author) / Schmidt, Marius (Author) / Westenhoff, Sebastian (Author) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / Department of Physics (Contributor)
Created2016-10-19
Description
Antibodies are essential for structural determinations and functional studies of membrane proteins, but antibody generation is limited by the availability of properly-folded and purified antigen. We describe the first application of genetic immunization to a structurally diverse set of membrane proteins to show that immunization of mice with DNA alone produced antibodies against 71% (n = 17) of the bacterial and viral targets. Antibody production correlated with prior reports of target immunogenicity in host organisms, underscoring the efficiency of this DNA-gold micronanoplex approach. To generate each antigen for antibody characterization, we also developed a simple in vitro membrane protein expression and capture method. Antibody specificity was demonstrated upon identifying, for the first time, membrane-directed heterologous expression of the native sequences of the FopA and FTT1525 virulence determinants from the select agent Francisella tularensis SCHU S4. These approaches will accelerate future structural and functional investigations of therapeutically-relevant membrane proteins.
ContributorsHansen, Debra (Author) / Robida, Mark (Author) / Craciunescu, Felicia (Author) / Loskutov, Andrey (Author) / Dorner, Katerina (Author) / Rodenberry, John-Charles (Author) / Wang, Xiao (Author) / Olson, Tien (Author) / Patel, Hetal (Author) / Fromme, Petra (Author) / Sykes, Kathryn (Author) / Biodesign Institute (Contributor) / Innovations in Medicine (Contributor) / Applied Structural Discovery (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor)
Created2016-02-24
Description
Technologies capable of characterizing the full breadth of cellular systems need to be able to measure millions of proteins, isoforms, and complexes simultaneously. We describe an approach that fulfils this criterion: Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT). ADAPT employs an enriched library of single-stranded oligodeoxynucleotides (ssODNs) to profile complex biological samples, thus achieving an unprecedented coverage of system-wide, native biomolecules. We used ADAPT as a highly specific profiling tool that distinguishes women with or without breast cancer based on circulating exosomes in their blood. To develop ADAPT, we enriched a library of ~10[superscript 11] ssODNs for those associating with exosomes from breast cancer patients or controls. The resulting 10[superscript 6] enriched ssODNs were then profiled against plasma from independent groups of healthy and breast cancer-positive women. ssODN-mediated affinity purification and mass spectrometry identified low-abundance exosome-associated proteins and protein complexes, some with known significance in both normal homeostasis and disease. Sequencing of the recovered ssODNs provided quantitative measures that were used to build highly accurate multi-analyte signatures for patient classification. Probing plasma from 500 subjects with a smaller subset of 2000 resynthesized ssODNs stratified healthy, breast biopsy-negative, and -positive women. An AUC of 0.73 was obtained when comparing healthy donors with biopsy-positive patients.
ContributorsDomenyuk, Valeriy (Author) / Zhong, Zhenyu (Author) / Stark, Adam (Author) / Xiao, Nianqing (Author) / O'Neill, Heather A. (Author) / Wei, Xixi (Author) / Wang, Jie (Author) / Tinder, Teresa T. (Author) / Tonapi, Sonal (Author) / Duncan, Janet (Author) / Hornung, Tassilo (Author) / Hunter, Andrew (Author) / Miglarese, Mark R. (Author) / Schorr, Joachim (Author) / Halbert, David D. (Author) / Quackenbush, John (Author) / Poste, George (Author) / Berry, Donald A. (Author) / Mayer, Gunter (Author) / Famulok, Michael (Author) / Spetzler, David (Author) / Consortium for Biosocial Complex Systems (Contributor) / Complex Adaptive Systems Initiative (Contributor)
Created2017-02-20