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Sirtuins are a group of seven compounds (SIRT1 - SIRT7) that are involved in a wide range of biological functions. Because of their role in gene regulation, researchers believe that sirtuin inhibitors may be useful as treatments for diseases. For example, drug designers believe that SIRT2 inhibition could be a useful treatment for Parkinson’s disease.
MSI Principal Investigator Liqiang Chen, an assistant professor in the Center for Drug Design in the Academic Health Center, and his colleagues recently published a paper discussing a method of creating SIRT2 inhibitors. The method uses fragments of other compounds that have characteristics that would be useful in the compound. The researchers combine the fragments in new ways, and then analyze their activity. One of these new compounds, dubbed “compound 64” by the researchers, showed particular promise as a SIRT2 inhibitor. It was also notable in that it was very selective in interacting with SIRT2 but not with its most similar sirtuins, SIRT1 or SIRT3.
Once the researchers had identified compound 64 as a likely candidate for further research, they used MSI resources to perform computational modeling to study how it attaches to SIRT2. While this research is preliminary, compound 64 shows promise as a possible treatment for the symptoms of Parkinson’s disease. Professor Chen and his colleagues are continuing their investigations into compound 64.
This research has been supported by the Center for Drug Design at the University of Minnesota. The group’s paper can be found on the Journal of Medicinal Chemistry website: Cui, Huaqing, Zeeshan Kamal, Teng Ai, Yanli Xu, Swati S. More, Daniel J. Wilson, and Liqiang Chen. 2014. Discovery of Potent and Selective Sirtuin 2 (SIRT2) Inhibitors Using a Fragment-Based Approach. Journal of Medicinal Chemistry 57 (20): 8340-57.
Image description: Potential binding modes and interactions of compound 64 docked into the crystal structure of SIRT2 (PDB entry 1j8f). (A) Two binding modes of compound 64 in the active site of SIRT2 (surface representation). (B) Potental interactions between compound 64 and SIRT2 in the first binding mode (magenta). (C) Potential interactions between compound 64 and SIRT2 in the second mode (green). Image and description, Cui, H. et al., J Med Chem 57 (20): 8340-57 (2014). ©2014 American Chemical Society.
posted on January 7, 2015
Most galaxies that we have observed contain at their centers a supermassive black hole. While scientists don’t know how these black holes were formed, they have surmised that they could be the remnants of supermassive stars that, at the end of their lives, collapsed to create the black holes. Researchers use computer modeling to study this process.
Recently, Dr. Ke-Jung (Ken) Chen, a former graduate student in the MSI research group of Associate Professor Alexander Heger (Physics and Astronomy, College of Science and Engineering), and his colleagues discovered that there seems to be a narrow range of mass where a supermassive star ends as a supernova instead of collapsing into a black hole. These stars are between 55,000 and 56,000 solar masses (one solar mass equals the mass of our sun). This is an exciting new development, since the supernovae may have resulted in the creation and dispersion of heavy elements (elements other than hydrogen and helium) throughout the cosmos. These elements would be the foundation of next generations of stars and be the basis of the composition of the current universe. Using advanced computer models, the researchers modeled how the stars behaved at the end of their lifespans.
Much of this work was completed while Dr. Chen was a graduate student using MSI resources. Other modeling was completed using resources at the National Energy Research Scientific Computing Center. The article can be read on the Astrophysical Journal website (KJ Chen, A Heger, S Woosley, A Almgren, DJ Whalen, JL Johnson. 2014. The general relativistic instability supernova of a supermassive population III star. Astrophysical Journal 790 (2) (AUG 1), 10.1088/0004-637X/790/2/162).
Dr. Chen is currently a post-doc at the University of California Santa Cruz. He was an active user of MSI while he was a grad student at the U. He was a finalist at the 2010 MSI Research Exhibition poster competition and was the Grand Prize winner at the 2011 competition. He was also awarded the 2013 Gruber Foundation Fellowship of the International Astronomical Union. Dr. Chen would especially like to recognize the support of the University of Minnesota’s School of Physics and Astronomy, headed by Professor Ron Poling and Professor Joe Kapusta, and the Minnesota Supercomputing Institute, headed by Professor Tom Jones (2008-10) and Professor Jorge Vinals (2010-present). The project was supported by the DOE SciDAC program under grants DOE-FC02-01ER41176, DOE-FC02-06ER41438, and DE-FC02-09ER41618, and by the US Department of Energy under grant DE-FG02-87ER40328.
Image description: Mixing in 16O, 24Mg, 28Si, and 32S prior to shock breakout. Image and description, KJ Chen et al., Astrophysical Journal, 2014, 10.1088/0004-637X/790/2/162. © 2014, The American Astronomical Society.
posted on December 10, 2014
Application of Informatics to Transcription of Ancient Papyri
While computers can do many things, there are still a few areas in which humans excel such as the discriminatory power of the eye and the natural human ability to quickly classify objects. The visual ability of recognizing patterns is at the core of the Zooniverse (https://www.zooniverse.org/) citizen science project that Professor Lucy Fortson (School of Physics and Astronomy, College of Science and Engineering) has been involved with. It started with Galaxy Zoo in 2007 by simply asking the general public to help classify about a million scientific images of galaxies and since has grown to over 25 projects enlisting the help of the public to identify whales, lions, and even planets outside our solar system.
As part of an interdisciplinary team, MSI staff have been working with Professor Fortson and her Humanities colleagues at the University of Minnesota and Oxford University (UK) to help transcribe a collection of ancient papyri. The papyri are part of the Oxyrhynchus collection maintained by Oxford University and composed of over 500,000 fragments dating from the period 150 BCE to 650 CE and excavated from the ancient trash heap of the Egyptian town called Oxyrhynchus. Contributors to the Ancient Lives (http://www.ancientlives.org/) citizen science project, members of the general public, are asked to help transcribe the contents of these individual papyri. No ancient or foreign language skills are required as the project relies solely on visual pattern recognition. Volunteers are simply asked to match characters on the papyrus to corresponding characters on an electronic virtual keyboard by first clicking the letter on the papyrus image and then clicking the corresponding Greek letter. As every single papyrus will be transcribed by many different users, a consensus will emerge from the many transcriptions. As of November 2014, nearly ten million marks have been made on over 150,000 fragments by about a million volunteers worldwide.
This wealth of clicks needs to be turned into a data product useful to the Humanities researchers through the development of a data processing pipeline. This is where Professor Fortson’s background in astrophysics and the MSI team come in. While there are many steps in the pipeline, one of the most critical is the consensus algorithm. Applying kernel density estimation (KDE) methods to the volunteers’ contributed transcription data, MSI staff developed a workflow that converts clicks into computationally deducted consensus sequences, or text strings, and thus quickly enabled the transformation of physical documents into computationally searchable data.
To enable the organization of these data sets, MSI has also developed an editorial web tool (http://papyrus.msi.umn.edu/) to support the curation and metadata annotation efforts of these data sets by scholars of ancient texts. In a final step MSI staff and collaborators at Middle Tennessee State University are applying bioinformatics tools to identify words or text strings and similarities between papyri (e.g. copies of known texts).
With a 2013 award from the National Endowment for the Humanities, the team, now led by Drs. Philip Sellew and Nita Krevans, University of Minnesota professors in Classical and Near Eastern Studies, is applying a similar strategy to the transcription of ancient Coptic papyri.
A new initiative, Zooniverse@UMN, has recently been funded* to support University of Minnesota-affiliated projects. This effort is currently soliciting proposals for text-based projects that would benefit from hundreds of thousands of online volunteers transcribing or metadata tagging a digitally imaged collection. Researchers can download the Request for Proposals on the UM Zoomanities webpage. The proposal due date window is November 24 - December 15, 2014.
Publications by these researchers include:
Williams, A.C., Wallin, J.F., Yu. H, Carroll, H.D., Lamblin., A-F., Fortson, L., Obbink, D., Lintott, C.J. & Brusuelas, J.H. (2014). A Computational Pipeline For Crowdsourced Transcriptions of Ancient Greek Papyrus Fragments. (To Appear In) Proceedings of the 2nd Workshop on Big Humanities Data.
Williams, A.C., Carroll, H.D., Wallin, J.F., Brusuelas, J., Fortson, L., Lamblin., A-F., & Yu, H. (2014). Identification of Ancient Greek Papyrus Fragments Using Genetic Sequence Alignment Algorithms. (To Appear In) Proceedings of the 1st Workshop on Digital Humanities and e-Science.
*Funding for Zooniverse@UMN is provided by the Office of the Vice President for Research, the University Libraries, the Colleges of Biological Sciences, Liberal Arts, and Science and Engineering, and the University of Minnesota Informatics Institute.
Figure descriptions: Left: a fragment from the Oxyrhynchus papyri. Right: an example of a transcribed fragment plotted on the image of the original fragment. Yellow characters are the consensus characters for the volunteers who transcribed the fragment, while the red characters are the transcription of a Greek expert. The expert characters have been shifted down a bit to provide better readability. All users’ transcriptions for the fragment are also kept in a text file for Greek scholars to review.
posted on November 26, 2014
photo credit: Bethany A. Stahl
Animals that move from surface habitats into caves exhibit evolutionally related changes in their new environments. Perhaps the most dramatic is eye loss, but there are also other changes, such as skin pigmentation and sleeping patterns. Researchers believe that studying how these changes occur and the genes involved could provide insights into some human conditions, such as degenerative eye diseases.
Assistant Professor Suzanne McGaugh, an MSI Principal Investigator from the Department of Ecology, Evolution, and Behavior (College of Biological Sciences) was the lead researcher on a recent paper that disclosed the first de novo genome assembly for the cavefish Astyanax mexicanus, the Mexican tetra fish. This discovery allows researchers to identify genes that may be involved with the evolution of traits specific to cave species. This will support further research into the mechanisms of evolutionary change and may help us to understand the underlying causes of various human diseases. The article was published online in Nature Communications on October 20, 2014. (McGaugh S.E. et al. The cavefish genome reveals candidate genes for eye loss. Nat. Commun. 5:5307 DOI: 10.1038/ncomms6307 (2014)).
Professor McGaugh uses MSI resources to perform large-scale genomic analyses, which require considerable computational power. Besides studies of cavefish, the McGaugh group is studying the transcriptomes of reptiles.
An article about this research also appeared on the University of Minnesota’s Discover blog.
Image description: a,b: surface fish; c,d: Pachón cavefish. Scale bar for a,c is 1 cm. Scale bar for b,d is 0.25 cm. (Image and description, McGaugh S.E. et al., The cavefish genome reveals candidate genes for eye loss. Nat. Commun. 5:5307 DOI: 10.1038/ncomms6307 (2014). ©Nature Publishing Group.
posted on November 12, 2014
Oral cancer is a virulent form of the disease, with a nearly 50 percent mortality rate. Early diagnosis is one of the keys to successful treatment; patients whose cancer is found and treated early have a much better survival rate. Unfortunately, the current method of diagnosing the disease, which involves excision and biopsy of tissue, is both invasive and expensive. It is also prone to errors because of under-sampling. A better method for diagnosing this disease would be a great benefit.
Two MSI Principal Investigators, Associate Professor Frank Ondrey (Director of Research and Clinical Trials, Otolaryngology - Medical School) and Associate Professor Timothy Griffin (Biochemistry, Molecular Biology, and Biophysics - Medical School and College of Biological Sciences), are co-authors with several colleagues from China and the University of Minnesota on a recent paper in PLos One that discusses a new, proteomics-based method of diagnosing oral cancer. Cells retrieved via a non-invasive oral brush biopsy were tested using mass spectrometry-based proteomics. The researchers found that the secretory leukocyte protease inhibitor (SLPI) was greatly reduced in samples from cancerous and pre-cancerous lesions, compared to normal tissue. This suggests that the reduction in SLPI could be a biomarker for oral cancer.
The paper can be read on the PLoS One website (Yang, Ya, Nelson L. Rhodus, Frank G. Ondrey, Beverly R. K. Wuertz, Xiaobing Chen, Yaqin Zhu, and Timothy J. Griffin. 2014. Quantitative proteomic analysis of oral brush biopsies identifies secretory leukocyte protease inhibitor as a promising, mechanism-based oral cancer biomarker. PLoS One 9 (4) (APR 18), 10.1371/journal.pone.0095389.). The authors used MSI software and hardware to perform data analysis.
Image description: A. Brush biopsy collection and sample preparation protocol. B. Experimental design for quantitative MSI-based proteomics experiments. One experiment used matched tissue from oral premalignant lesion tissue, and the second used matched tissue from oral squamous cell carcinoma. Image and description, Y Yang et al., 2014, PLoS One, 10.1371/journal.pone.0095389.
posted on October 29, 2014