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Polymers, which many people think refer only to plastic, are actually a large group of natural and man-made materials. They have many uses in industry and as consumer products. Some of these include the super-absorbant polymers used in disposable diapers, the heat-stable materials used for non-stick cookware, and the fiber spandex, used for stretchy clothing like athletic wear and foundation garments. The research group of Associate Professor Kevin Dorfman (Chemical Engineering and Materials Science) is using MSI for research into the structures and dynamics of polymers, especially DNA. On the engineering side, understanding the dynamics of DNA has many important applications in genomics. On the scientific side, DNA is a model system for investigating the basic physical properties of semiflexible polymers. The Dorfman group is using several computer-simulation techniques, including Metropolis and chain growth Monte Carlo methods.
Professor Dorfman and graduate student Douglas Tree, along with their colleague Yanwei Wang (Soochow University, China), recently published research in Physical Review Letters concerning DNA confinement in nanochannels. DNA confinement is becoming an important tool for genomics research. It also provides researchers a platform for testing theories concerning confined wormlike polymers. The classical theories for polymer chains in confinement only work in cases where the nanochannels are very small or very large compared to the polymer. The Dorfman group has investigated an intermediate case between the two models. In the graphic above, the Odijk theory applies to DNA in small channels and the Flory-de Gennes theory works for large channels. The newly proposed regime of behavior, called the “Gauss-de Gennes” regime by the researchers, works for the intermediate channel sizes that have been typically used in genomic devices. The researchers propose that this regime applies to the general class of semiflexible polymers, which includes DNA as a special case.
The article can be read on the American Physical Society website: “Extension of DNA in a Nanochannel as a Rod-to-Coil Transition,” DR Tree, Y Wang, DK Dorfman, Physical Review Letters, 110:208103, DOI:10.1103/PhysRevLett.110.208103 (2013).
Image description: Illustration of the analogy between free solution and confined configurations of a wormlike chain. The classical theories renormalize the chain into a series of subchains, where these subchains are either rodlike (Odijk) or excluded-volume blobs (de Gennes). (For clarity, the authors refer to the classic de Gennes regime as the “Flory-de Gennes” regime.) The middle drawing illustrates a universal Gauss-de Gennes regime in confinement that is an intermediate step between the two classical ones. © 2013 American Physical Society
Posted on September 11, 2013.
In the course of the history of agriculture, humans have tried to change the properties of the crops they raise. Maize (corn) is a very valuable and widely grown crop, and researchers are able to trace how modern maize has been developed from its wild ancestor, a plant called teosinte (Zea mays ssp. parviglumis).
Three MSI Principal Investigators – Assistant Professor Chad Myers (Computer Science and Engineering), Associate Professor Peter Tiffin (Plant Biology), and Professor Nathan Springer (Plant Biology) - were co-authors on a paper published last year in the Proceedings of the National Academy of Sciences (“Reshaping of the Maize Transcriptome by Domestication,” R Swanson-Wagner, R Briskine, R Schaefer, MH Hufford, J Ross-Ibarra, C Myers, P Tiffin, NM Springer, PNAS, 109(29):11878, DOI: 10.1073/pnas.1201961109 (2012)), that reveals changes in the maize transcriptome after it was domesticated. The transcriptome is the set of all RNA molecules in a set of cells. For this paper, the researchers used expression profiling to determine that over 600 genes have altered expression levels in maize compared with teosinte. They studied over 18,000 genes for 38 maize genotypes and 24 teosinte genotypes. The domestication process from teosinte to modern maize is a model for studying how complex traits in plants can be changed over time. The researchers used software and user support available at MSI to help with the data analysis.
Professor Myers uses MSI resources to analyze large-scale genetic interaction networks. Professor Tiffin is involved in several projects related to the evolutionary history of species and connecting genotype (genetic makeup) to phenotype (composite of observable traits or characteristics). Professor Springer uses MSI to study epigenetic variation in maize. (Epigenetics is the study of heritable variation that is not solely attributable to genetic changes.)
Image Description: The scatterplot in the left image shows the correlation between all gene pairs in maize (x axis) relative to the correlation for the same gene pair in teosinte (y axis). The relative density of data points in the left image was compared with the average for 1,000 bootstrap coexpression networks in the image at right. Blue regions indicate fewer observed correlations relative to the bootstrap networks, whereas red coloration indicates an excess of actual observations, providing evidence for an enrichment of gene pairs with varying correlations in maize and teosinte. Image and description © 2012 by National Academy of Sciences.
Posted on August 28, 2013.
The research group of Professor Carrie Wilmot in the Department of Biochemistry, Molecular Biology, and Biophysics concentrates on understanding the synthesis and function of novel organic, organometallic, and metal-ion cofactors in proteins. (A cofactor is a chemically reactive protein modification or bound non-protein compound that is necessary for the biological activity of a protein, many of which are enzymes.) The ultimate goal of the research is to provide a basis for the development of new and better drugs, for engineering proteins for applications in biotechnology, and for designing simpler industrial catalysts. The researchers’ primary tool is macromolecular X-ray crystallography and mass spectrometry.
The Wilmot group recently published a paper in the Proceedings of the National Academy of Sciences, U.S.A. that describes the actions of the enzyme MauG to catalyze the formation of a tryptophan tryptophylquinone (TTQ) cofactor to activate the enzyme methylamine dehydrogenase (MADH) (“Diradical Intermediate Within the Context of Tryptophan Tryptophylquinone Biosynthesis,” ET Yuki, FG Liu, J Krzystek, S Shin, LMR Jensen, VL Davidson, CM Wilmot, AM Liu, PNAS, 110(1):4569, DOI: 10.1073/pnas.1215011110 (2013)). The oxidation process that results in the formation of tryptophan tryptophylquinone has three distinct steps; the researchers have been able to figure out the progression of the oxidation and identify the structures of the intermediate steps. The computer work was done at MSI’s BSCL. The image above shows the various steps of the process.
Image description: (A) Electron density for the precursor TTQ site in MauG–precursor MADH crystals of different ages. Electron density maps (blue) for the crystals aged for 10, 40, 50, and 130 days were generated from the respective refined structures. The 50- and 130-day electron density images were calculated using the refined 50-day model (cross-linked precursor TTQ) to enable visualization of the positive-difference electron density (green) for the appearance of the second oxygen. (B) The observed rotation in βTrp57-OH during cross-link formation. The figure was produced using PyMOL (www.pymol.org). Image and description © 2013 by National Academy of Sciences, USA.
posted on August 14, 2013
Lazarina Gyoneva is a graduate student in the research group of Professor Victor Barocas (MSI Fellow; Biomedical Engineering). She came to the University of Minnesota as a grad student in 2010 and started using MSI resources in the spring of 2011. Ms. Gyoneva was a finalist in the poster competition at the 2013 MSI Research Exhibition with her poster, “Role of Lateral Interactions in Collagen IV Network Mechanics.” Other MSI PIs who were co-authors on this poster are Yoav Segal (Medicine) and Kevin Dorfman (Chemical Engineering and Materials Science). Ms. Gyoneva sat down with MSI recently to discuss her work.
MSI: What do you use MSI for?
Lazarina Gyoneva: On the computational side, I use mostly the different C++ compilers and MATLAB, and on the analytical side, I use statistical and graphical packages like GraphPad Prism and SAS. I use them through the labs.
MSI: Your poster describes type IV collagen. Can you explain the difference between collagen IV and the kind of collagen we’ve all heard about in the skin?
LG: There are actually over 20 different types of collagen, all products of different genes. The collagen found in skin is type I. Type IV collagen is the type that’s present in basement membranes – the part of the extracellular matrix on which epithelial cells are attached. Type IV collagen is slightly different from type I collagen in its molecular structure and organization. Because of their differences in molecular structure and processing, type I collagen is able to form thick strong fibers while type IV collagen molecules can’t be packed closely enough to form fibers and they self-organize into planar networks.
There are three known kinds of collagen IV. The two most common ones are the so-called “major” and “minor” kinds, and even between them there are differences based on primary and secondary structures of the proteins.
MSI: What are you trying to do in this poster?
LG: We are looking at the role of lateral interactions on the mechanical properties of type IV collagen networks. The two different types of collagen IV, the major and the minor, are believed to have different abilities to form lateral interactions, therefore they can form slightly different networks. The minor chains also have the ability to wind around each other, forming “supercoils,” which probably changes the structure of the network as well as the mechanical properties of the network.
So, we already see that they have some structural differences, and we wanted to know how these structural differences could affect the mechanical properties. The reason we’re interested in that is because, clinically, we know that the minor chains are vital for the proper functioning of the collagen networks of the kidneys and the lens of the eye. When the minor chains are missing from those locations [Ed: a condition called Alport Syndrome], the collagen networks cannot perform their mechanical functions in those locations. We want to know what properties of the minor chains make them so vital.
MSI: How did you use MSI?
LG: We generated networks in MATLAB that represent the major and minor collagen networks. The generated networks have the same connectivity and relative concentrations as the physiological collagen IV networks. We introduced lateral interactions in the minor chain networks constraining the networks a little bit more. In some places, we created “supercoils,” to which we assigned double the stiffness and double the cross-sectional area of normal chains. We then took the generated networks and simulated their mechanical deformation to obtain their stress-strain response. The mechanical simulations are done with a force-balance code in which the boundaries of the networks are stretched first, then all internal segments are allowed to move around until they are in a position at which the sum of the forces on each chain is zero. From the force calculations, we can also calculate the stresses that are applied to these networks.
We generated two different networks, one (kidney) with a higher percentage of minor chains, and another (lens) with a lower percentage of minor chains and we tested what happens when we increase the connectivity of the minor chains.
MSI: Does this research have immediate applications, or is it more basic science?
LG: It’s definitely more on the theoretical side. The main reason we think it’s important to look at this is because not much is known about the mechanical role of the minor chains and what are the primary causes for the disturbances seen in Alport Syndrome when the minor chains are absent. We believe that Alport Syndrome may be caused by a loss of mechanical functionality, initiating a number of secondary biological responses. Current treatments have focused on the biological side but it’s very important to learn more about the primary causes so we can discover ways to treat the diseases earlier.
MSI: Will this eventually have applications for clinical treatment?
LG: I can’t speak yet of direct clinical applications, but what we are learning about the importance of network structure for mechanical properties could have applications not just for Alport Syndrome, but for material science in general. The ability to build biological or synthetic networks that can be easily modified to adjust their mechanical properties would be very desirable.
MSI: How much more needs to be done with this project?
LG: There are definitely a lot of unanswered questions in this area. The networks generated for the simulations are idealized representations. Ideally, we would like to have ultra-high resolution Scanning Electron Microscopy images of actual lens and glomerular basement membranes from which we can extract the exact topology of collagen IV networks. Then we can digitize the real networks and use them for the mechanical stretching simulations. There are some other things that we can look at. For example, we still don’t know how exactly the minor and major chains interact with each other, how they are distributed in basement membranes, if the higher number of cysteines really corresponds to a higher number of lateral interactions, or what is it about the minor chains that makes them form supercoils when the major chains don’t do that. Those are all basic questions that need to be answered.
MSI: Do you make the models using information that you got experimentally?
LG: Some of the parameters used in the computational model are taken from literature on collagen IV and collagen I. We did perform a set of experiments last year that were very informative in quantifying the importance of the minor chain network in contributing additional strength to the basement membrane of the ocular lens. One of the purposes for this computational project was to try to explain some of the experimental results where we used wild-type and Alport mutant mouse lenses and compared their distensibility. We saw that when the minor chains are missing, the lens is much more compliant. This computational study is now trying to explain what it is about the minor chain that gives them additional mechanical strength.
posted on July 31, 2013
With the recent appearance of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV), coronaviruses are once again in the news. These viruses are found worldwide and some of them can create serious illness in humans. SARS (severe acute respiratory syndrome), which is caused by a coronavirus, killed hundreds of people in 2002-2003.
Assistant Professor Fang Li, an MSI Principal Investigator from the Department of Pharmacology in the Medical School, uses structural biology to study diseases including viral infections. This research investigates the structural basis for the receptor recognition mechanisms of viruses. This includes studying the structures and functions of the receptor-binding proteins found on the surfaces of viruses, as well as how they interact with host receptors. These structural studies will allow researchers to develop therapy strategies to fight virus-caused diseases.
Recently, Professor Li and his colleagues determined the crystal structure of the spike protein N-terminal domains (NTDs) of bovine coronavirus (BCoV). This finding was published in the Journal of Biological Chemistry in December 2012 (“Crystal Structure of Bovine Coronavirus Spike Protein Lectin Domain,” GQ Peng, LQ Xu, YL Lin, L Chen, JR Pasquarella, KV Holmes, F Li, Journal of Biological Chemistry, 287:41931, DOI: 10.1074/jbc.M112.418210 (2012)). The research studied the differences in the structure of the NTDs of BCoV and another coronavirus, mouse hepatitis coronavirus (MHC). While both NTDs include a human galactose-binding lectin (galectin) in their NTD structures, the former binds to sugar and the latter to a protein, CEACAM1. The Li group’s studies of the crystal structure of the NTDs show subtle differences in the receptor-binding loops. These results indicate a possible evolution path where a coronavirus incorporated this galectin into its spike proteins, which was altered as the different modern coronaviruses evolved. The researchers used the BSCL for this research.
The Li group has also published additional papers related to their research using MSI. These include:
- “Structural basis for multifunctional roles of mammalian aminopeptidase N,” L Chen, YL Lin, GQ Peng, F Li, Proceedings of the National Academy of Sciences of the United States of America, 109:17966, DOI: 10.1073/pnas.1210123109 (2012)
- “Mechanisms of Host Receptor Adaptation by Severe Acute Respiratory Syndrome Coronavirus,” KL Wu, GQ Peng, M Wilken, RJ Geraghty, F Li, Journal of Biological Chemistry, 287:8904, DOI: 10.1074/jbc.M111.325803 (2012)
Image description: A. Overall structure of BCoV NTD. Two β-sheets of NTD core are colored green and magenta, respectively, and other parts of the NTD are color cyan. N*, N terminus; C*, C terminus. The β-sandwich core structure is indicated as “core.” The two potential sugar-binding pockets above and underneath the core structure are indicated as top and bottom, respectively. B. 2Fo – Fo electron density of a portion of BCoV NTD at 1.5σ. This region includes three of the critical sugar-binding residues. (Peng G et al., “Crystal Structure of Bovine Coronavirus Spike Protein Lectin Domain,” J. Biol. Chem., 287:41931 (2012); ©2012 by the American Society for Biochemistry and Molecular Biology.)
posted on July 17, 2013
