Matching Items (130)
Description
Single particle diffractive imaging data from Rice Dwarf Virus (RDV) were recorded using the Coherent X-ray Imaging (CXI) instrument at the Linac Coherent Light Source (LCLS). RDV was chosen as it is a well-characterized model system, useful for proof-of-principle experiments, system optimization and algorithm development. RDV, an icosahedral virus of about 70 nm in diameter, was aerosolized and injected into the approximately 0.1 μm diameter focused hard X-ray beam at the CXI instrument of LCLS. Diffraction patterns from RDV with signal to 5.9 Ångström were recorded. The diffraction data are available through the Coherent X-ray Imaging Data Bank (CXIDB) as a resource for algorithm development, the contents of which are described here.
ContributorsMunke, Anna (Author) / Andreasson, Jakob (Author) / Aquila, Andrew (Author) / Awel, Salah (Author) / Ayyer, Kartik (Author) / Barty, Anton (Author) / Bean, Richard J. (Author) / Berntsen, Peter (Author) / Bielecki, Johan (Author) / Boutet, Sebastien (Author) / Bucher, Maximilian (Author) / Chapman, Henry N. (Author) / Daurer, Benedikt J. (Author) / DeMirci, Hasan (Author) / Elser, Veit (Author) / Fromme, Petra (Author) / Hajdu, Janos (Author) / Hantke, Max F. (Author) / Higashiura, Akifumi (Author) / Hogue, Brenda (Author) / Hosseinizadeh, Ahmad (Author) / Kim, Yoonhee (Author) / Kirian, Richard (Author) / Reddy, Hemanth K. N. (Author) / Lan, Ti-Yen (Author) / Larsson, Daniel S. D. (Author) / Liu, Haiguang (Author) / Loh, N. Duane (Author) / Maia, Filipe R. N. C. (Author) / Mancuso, Adrian P. (Author) / Muhlig, Kerstin (Author) / Nakagawa, Atsushi (Author) / Nam, Daewoong (Author) / Nelson, Garrett (Author) / Nettelblad, Carl (Author) / Okamoto, Kenta (Author) / Ourmazd, Abbas (Author) / Rose, Max (Author) / van der Schot, Gijs (Author) / Schwander, Peter (Author) / Seibert, M. Marvin (Author) / Sellberg, Jonas A. (Author) / Sierra, Raymond G. (Author) / Song, Changyong (Author) / Svenda, Martin (Author) / Timneanu, Nicusor (Author) / Vartanyants, Ivan A. (Author) / Westphal, Daniel (Author) / Wiedom, Max O. (Author) / Williams, Garth J. (Author) / Xavier, Paulraj Lourdu (Author) / Soon, Chun Hong (Author) / Zook, James (Author) / College of Liberal Arts and Sciences (Contributor, Contributor) / School of Molecular Sciences (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / School of Life Sciences (Contributor) / Infectious Diseases and Vaccinology (Contributor) / Department of Physics (Contributor)
Created2016-08-01
Description
Serial femtosecond X-ray crystallography (SFX) using an X-ray free electron laser (XFEL) is a recent advancement in structural biology for solving crystal structures of challenging membrane proteins, including G-protein coupled receptors (GPCRs), which often only produce microcrystals. An XFEL delivers highly intense X-ray pulses of femtosecond duration short enough to enable the collection of single diffraction images before significant radiation damage to crystals sets in. Here we report the deposition of the XFEL data and provide further details on crystallization, XFEL data collection and analysis, structure determination, and the validation of the structural model. The rhodopsin-arrestin crystal structure solved with SFX represents the first near-atomic resolution structure of a GPCR-arrestin complex, provides structural insights into understanding of arrestin-mediated GPCR signaling, and demonstrates the great potential of this SFX-XFEL technology for accelerating crystal structure determination of challenging proteins and protein complexes.
ContributorsZhou, X. Edward (Author) / Gao, Xiang (Author) / Barty, Anton (Author) / Kang, Yanyong (Author) / He, Yuanzheng (Author) / Liu, Wei (Author) / Ishchenko, Andrii (Author) / White, Thomas A. (Author) / Yefanov, Oleksandr (Author) / Han, Gye Won (Author) / Xu, Qingping (Author) / de Waal, Parker W. (Author) / Suino-Powell, Kelly M. (Author) / Boutet, Sebastien (Author) / Williams, Garth J. (Author) / Wang, Meitian (Author) / Li, Dianfan (Author) / Caffrey, Martin (Author) / Chapman, Henry N. (Author) / Spence, John (Author) / Fromme, Petra (Author) / Weierstall, Uwe (Author) / Stevens, Raymond C. (Author) / Cherezov, Vadim (Author) / Melcher, Karsten (Author) / Xu, H. Eric (Author) / College of Liberal Arts and Sciences (Contributor) / School of Molecular Sciences (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / Department of Physics (Contributor)
Created2016-04-12
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
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
Serial femtosecond crystallography (SFX) using X-ray free-electron laser sources is an emerging method with considerable potential for time-resolved pump-probe experiments. Here we present a lipidic cubic phase SFX structure of the light-driven proton pump bacteriorhodopsin (bR) to 2.3 Å resolution and a method to investigate protein dynamics with modest sample requirement. Time-resolved SFX (TR-SFX) with a pump-probe delay of 1 ms yields difference Fourier maps compatible with the dark to M state transition of bR. Importantly, the method is very sample efficient and reduces sample consumption to about 1 mg per collected time point. Accumulation of M intermediate within the crystal lattice is confirmed by time-resolved visible absorption spectroscopy. This study provides an important step towards characterizing the complete photocycle dynamics of retinal proteins and demonstrates the feasibility of a sample efficient viscous medium jet for TR-SFX.
ContributorsNogly, Przemyslaw (Author) / Panneels, Valerie (Author) / Nelson, Garrett (Author) / Gati, Cornelius (Author) / Kimura, Tetsunari (Author) / Milne, Christopher (Author) / Milathianaki, Despina (Author) / Kubo, Minoru (Author) / Wu, Wenting (Author) / Conrad, Chelsie (Author) / Coe, Jesse (Author) / Bean, Richard (Author) / Zhao, Yun (Author) / Bath, Petra (Author) / Dods, Robert (Author) / Harimoorthy, Rajiv (Author) / Beyerlein, Kenneth R. (Author) / Rheinberger, Jan (Author) / James, Daniel (Author) / Deponte, Daniel (Author) / Li, Chufeng (Author) / Sala, Leonardo (Author) / Williams, Garth J. (Author) / Hunter, Mark S. (Author) / Koglin, Jason E. (Author) / Berntsen, Peter (Author) / Nango, Eriko (Author) / Iwata, So (Author) / Chapman, Henry N. (Author) / Fromme, Petra (Author) / Frank, Matthias (Author) / Abela, Rafael (Author) / Boutet, Sebastien (Author) / Barty, Anton (Author) / White, Thomas A. (Author) / Weierstall, Uwe (Author) / Spence, John (Author) / Neutze, Richard (Author) / Schertler, Gebhard (Author) / Standfuss, Jorg (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Physics (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Biodesign Institute (Contributor) / Applied Structural Discovery (Contributor) / School of Molecular Sciences (Contributor)
Created2016-08-22
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
X-ray Free Electron Lasers (XFELs) are used for diffractive x-ray imaging of the structure of many biological particles, such as viruses and proteins. The ultimate goal for XFEL-based microscopy is atomic resolution images of non-crystalline particles. However, data collection efficiency as well as the limited amount of measurement time given annually to researchers, such high-resolution images are presently impossible to attain. Here, we consider two potential solutions to the single-particle hit rate problem; the first looks at applying static electric fields to existing aerodynamic particle injectors, and the second looks at the viability of using time-varying electric fields associated with ion traps to create high-density regions of particles. For the static solution, we looked at applying a constant electric potential to the nozzle, as well as applying a high voltage to a ring electrode in close proximity to a grounded nozzle. We considered the breakdown field strength of the helium gas used to determine how closely the ring electrode could be placed without creating an arc that could potentially destroy expensive equipment. Then, we considered the possibility of using electrodynamic ion traps to increase particle densities. We first characterized how charged particles behave in oscillating electric fields using a simple electrode geometry. Using the general results from this, we then constructed a rudimentary ion trap to test if our experiment agreed with the theory. Finally, we conducted a literature review to determine what particle densities other scientists have been able to measure using ion traps. We then compared existing ion traps to what we expect from the nozzle injectors to determine which method may be the better solution.
ContributorsBradshaw, Layne Nicholas (Author) / Kirian, Richard (Thesis director) / Weierstall, Uwe (Committee member) / Department of Physics (Contributor, Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Climate change is one of the most pressing issues affecting the world today. One of the impacts of climate change is on the transmission of mosquito-borne diseases (MBDs), such as West Nile Virus (WNV). Climate is known to influence vector and host demography as well as MBD transmission. This dissertation addresses the questions of how vector and host demography impact WNV dynamics, and how expected and likely climate change scenarios will affect demographic and epidemiological processes of WNV transmission. First, a data fusion method is developed that connects non-autonomous logistic model parameters to mosquito time series data. This method captures the inter-annual and intra-seasonal variation of mosquito populations within a geographical location. Next, a three-population WNV model between mosquito vectors, bird hosts, and human hosts with infection-age structure for the vector and bird host populations is introduced. A sensitivity analysis uncovers which parameters have the most influence on WNV outbreaks. Finally, the WNV model is extended to include the non-autonomous population model and temperature-dependent processes. Model parameterization using historical temperature and human WNV case data from the Greater Toronto Area (GTA) is conducted. Parameter fitting results are then used to analyze possible future WNV dynamics under two climate change scenarios. These results suggest that WNV risk for the GTA will substantially increase as temperature increases from climate change, even under the most conservative assumptions. This demonstrates the importance of ensuring that the warming of the planet is limited as much as possible.
ContributorsMancuso, Marina (Author) / Milner, Fabio A (Thesis advisor) / Kuang, Yang (Committee member) / Kostelich, Eric (Committee member) / Eikenberry, Steffen (Committee member) / Manore, Carrie (Committee member) / Arizona State University (Publisher)
Created2023