Reactive oxygen and nitrogen species have been implicated in many biological processes and diseases, including immune responses, cardiovascular dysfunction, neurodegeneration, and cancer. These chemical species are short-lived in biological settings, and detecting them in these conditions and diseases requires the use of molecular probes that form stable, easily detectable, products. The chemical mechanisms and limitations of many of the currently used probes are not well-understood, hampering their effective applications. Boronates have emerged as a class of probes for the detection of nucleophilic two-electron oxidants. Here, we report the results of an oxygen-18–labeling MS study to identify the origin of oxygen atoms in the oxidation products of phenylboronate targeted to mitochondria. We demonstrate that boronate oxidation by hydrogen peroxide, peroxymonocarbonate, hypochlorite, or peroxynitrite involves the incorporation of oxygen atoms from these oxidants. We therefore conclude that boronates can be used as probes to track isotopically labeled oxidants. This suggests that the detection of specific products formed from these redox probes could enable precise identification of oxidants formed in biological systems. We discuss the implications of these results for understanding the mechanism of conversion of the boronate-based redox probes to oxidant-specific products.

Much of our current knowledge of biological chemistry is founded in the structure-function relationship, whereby sequence determines structure that determines function. Thus, the discovery that a large fraction of the proteome is intrinsically disordered, while being functional, has revolutionized our understanding of proteins and raised new and interesting questions. Many intrinsically disordered proteins (IDPs) have been determined to undergo a disorder-to-order transition when recognizing their physiological partners, suggesting that their mechanisms of folding are intrinsically different from those observed in globular proteins. However, IDPs also follow some of the classic paradigms established for globular proteins, pointing to important similarities in their behavior. In this review, we compare and contrast the folding mechanisms of globular proteins with the emerging features of binding-induced folding of intrinsically disordered proteins. Specifically, whereas disorder-to-order transitions of intrinsically disordered proteins appear to follow rules of globular protein folding, such as the cooperative nature of the reaction, their folding pathways are remarkably more malleable, due to the heterogeneous nature of their folding nuclei, as probed by analysis of linear free-energy relationship plots. These insights have led to a new model for the disorder-to-order transition in IDPs termed “templated folding,” whereby the binding partner dictates distinct structural transitions en route to product, while ensuring a cooperative folding.

23 April 2020

The project aims to identify the enablers and barriers to enhance data use by National Public Health Institutes (NPHIs), producing outputs that will facilitate strengthening of the role of NPHIs in monitoring potential public health threats, and in shaping and informing domestic policies on health security and preparedness.

Expert

pncRNA-D is an irradiation-induced 602-nt long noncoding RNA transcribed from the promoter region of the cyclin D1 (CCND1) gene. CCND1 expression is predicted to be inhibited through an interplay between pncRNA-D and RNA-binding protein TLS/FUS. Because the pncRNA-D–TLS interaction is essential for pncRNA-D–stimulated CCND1 inhibition, here we studied the possible role of RNA modification in this interaction in HeLa cells. We found that osmotic stress induces pncRNA-D by recruiting RNA polymerase II to its promoter. pncRNA-D was highly m6A-methylated in control cells, but osmotic stress reduced the methylation and also arginine methylation of TLS in the nucleus. Knockdown of the m6A modification enzyme methyltransferase-like 3 (METTL3) prolonged the half-life of pncRNA-D, and among the known m6A recognition proteins, YTH domain-containing 1 (YTHDC1) was responsible for binding m6A of pncRNA-D. Knockdown of METTL3 or YTHDC1 also enhanced the interaction of pncRNA-D with TLS, and results from RNA pulldown assays implicated YTHDC1 in the inhibitory effect on the TLS–pncRNA-D interaction. CRISPR/Cas9-mediated deletion of candidate m6A site decreased the m6A level in pncRNA-D and altered its interaction with the RNA-binding proteins. Of note, a reduction in the m6A modification arrested the cell cycle at the G0/G1 phase, and pncRNA-D knockdown partially reversed this arrest. Moreover, pncRNA-D induction in HeLa cells significantly suppressed cell growth. Collectively, these findings suggest that m6A modification of the long noncoding RNA pncRNA-D plays a role in the regulation of CCND1 gene expression and cell cycle progression.

Publication Date: Apr 10 2020 New Fund Launches In addition to completing the Listing Application, new funds are required to complete a certification prior to receiving approval of an initial listing application. The certification can be found here. Listing Transfers In addition to completing the Listing Application, funds switching from another market to Nasdaq are required to complete a certification regarding compliance with SEC Rule 6c-11. The certification must be completed prior to...

Storm surge is often the most devastating part of a hurricane. Mathematical models used to predict surge must incorporate the effects of winds, atmospheric pressure, tides, waves and river flows, as well as the geometry and topography of the coastal ocean and the adjacent floodplain. Equations from fluid dynamics describe the movement of water, but most often such huge systems of equations need to be solved by numerical analysis in order to better forecast where potential flooding will occur. Much of the detailed geometry and topography on or near a coast require very fine precision to model, while other regions such as large open expanses of deep water can typically be solved with much coarser resolution. So using one scale throughout either has too much data to be feasible or is not very predictive in the area of greatest concern, the coastal floodplain. Researchers solve this problem by using an unstructured grid size that adapts to the relevant regions and allows for coupling of the information from the ocean to the coast and inland. The model was very accurate in tests of historical storms in southern Louisiana and is being used to design better and safer levees in the region and to evaluate the safety of all coastal regions. For More Information: A New Generation Hurricane Storm Surge Model for Southern Louisiana, by Joannes Westerink et al.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

What.s in store for our climate and us? It.s an extraordinarily complex question whose answer requires physics, chemistry, earth science, and mathematics (among other subjects) along with massive computing power. Mathematicians use partial differential equations to model the movement of the atmosphere; dynamical systems to describe the feedback between land, ocean, air, and ice; and statistics to quantify the uncertainty of current projections. Although there is some discrepancy among different climate forecasts, researchers all agree on the tremendous need for people to join this effort and create new approaches to help understand our climate. It.s impossible to predict the weather even two weeks in advance, because almost identical sets of temperature, pressure, etc. can in just a few days result in drastically different weather. So how can anyone make a prediction about long-term climate? The answer is that climate is an average of weather conditions. In the same way that good predictions about the average height of 100 people can be made without knowing the height of any one person, forecasts of climate years into the future are feasible without being able to predict the conditions on a particular day. The challenge now is to gather more data and use subjects such as fluid dynamics and numerical methods to extend today.s 20-year projections forward to the next 100 years. For More Information: Mathematics of Climate Change: A New Discipline for an Uncertain Century, Dana Mackenzie, 2007.

A new way of looking at marine evolution over the past 540 million years has shown that levels of biodiversity in our oceans have remained fairly constant, rather than increasing continuously over the last 200 million years, as scientists previously thought.

Outcomes of the Meeting of the Friends of the Co-Chairs on liability and redress, Bonn, 7-10 May 2008