Substrate Binding and Reduction Mechanism of Molybdenum Nitrogenase

As a key constituent of proteins, nucleic acids, and other biomolecules, nitrogen is essential to all living organisms including human beings. Dinitrogen represents the largest pool of nitrogen, about 79% of the Earth’s atmosphere, yet it is unusable by most living organisms due to its inertness. There are two ways to fix this inert dinitrogen to usable ammonia. One is the industrial Haber-Bosch process, which needs to be conducted at high temperature and pressure. This process uses a lot of the non-renewable fossil fuel as the energy source. The other major pathway is the biological nitrogen fixation carried out by some microorganisms called diazotrophs. The usable nitrogen output from this biological pathway ultimately supports an estimated 60% of the human population’s demand for nitrogen.The catalyst responsible for the biological nitrogen fixation is called nitrogenase, the most studied form of which contains molybdenum and iron in its active center, so called molybdenum nitrogenase. The work in this dissertation attempts to understand howthis biological catalyst breaks down dinitrogen to ammonia by application of different modern techniques. Firstly, an approach was developed to understand the stepwise reduction mechanism of dinitrogen to ammonia by molybdenum nitrogenase.The second goal of my research is to understand the roles of iron and molybdenum centers in nitrogenase function. My results using carbon monoxide as a probe for genetically modified molybdenum nitrogenase indicate that iron should be the metal sites functioning for nitrogen fixation. This is further supported by another study aimed at understanding the role of molybdenum during nitrogenase functioning.Moreover, an approach was developed to understand the mechanism for the obligatory production of hydrogen gas when nitrogenase activates dinitrogen for reduction. The same study also suggests possible pathways for the addition of hydrogenous species to nitrogen to produce ammonia.As part of this work, we also found that remodeled nitrogenases can use poisonous carbon monoxide and greenhouse-gas carbon dioxide to produce useful hydrocarbons by coupling one or more small molecules, which is hard to be achieved by other catalysts. Further study of these new reactions might give us deep insights on nitrogenase mechanism and inspire scientists to design better catalysts for relevant industrial processes

From Common to Special: When Multi-Attribute Learning Meets Personalized Opinions

Visual attributes, which refer to human-labeled semantic annotations, have gained increasing popularity in a wide range of real world applications. Generally, the existing attribute learning methods fall into two categories: one focuses on learning user-specific labels separately for different attributes, while the other one focuses on learning crowd-sourced global labels jointly for multiple attributes. However, both categories ignore the joint effect of the two mentioned factors: the personal diversity with respect to the global consensus; and the intrinsic correlation among multiple attributes. To overcome this challenge, we propose a novel model to learn user-specific predictors across multiple attributes. In our proposed model, the diversity of personalized opinions and the intrinsic relationship among multiple attributes are unified in a common-to-special manner. To this end, we adopt a three-component decomposition. Specifically, our model integrates a common cognition factor, an attribute-specific bias factor and a user-specific bias factor. Meanwhile Lasso and group Lasso penalties are adopted to leverage efficient feature selection. Furthermore, theoretical analysis is conducted to show that our proposed method could reach reasonable performance. Eventually, the empirical study carried out in this paper demonstrates the effectiveness of our proposed method

Exact Controllability of Linear Stochastic Differential Equations and Related Problems

A notion of $L^p$-exact controllability is introduced for linear controlled (forward) stochastic differential equations, for which several sufficient conditions are established. Further, it is proved that the $L^p$-exact controllability, the validity of an observability inequality for the adjoint equation, the solvability of an optimization problem, and the solvability of an $L^p$-type norm optimal control problem are all equivalent

HEN1 recognizes 21-24 nt small RNA duplexes and deposits a methyl group onto the 2' OH of the 3' terminal nucleotide.

microRNAs (miRNAs) and small interfering RNAs (siRNAs) in plants bear a methyl group on the ribose of the 3' terminal nucleotide. We showed previously that the methylation of miRNAs and siRNAs requires the protein HEN1 in vivo and that purified HEN1 protein methylates miRNA/miRNA* duplexes in vitro. In this study, we show that HEN1 methylates both miRNA/miRNA* and siRNA/siRNA* duplexes in vitro with a preference for 21-24 nt RNA duplexes with 2 nt overhangs. We also demonstrate that HEN1 deposits the methyl group on to the 2' OH of the 3' terminal nucleotide. Among various modifications that can occur on the ribose of the terminal nucleotide, such as 2'-deoxy, 3'-deoxy, 2'-O-methyl and 3'-O-methyl, only 2'-O-methyl on a small RNA inhibits the activity of yeast poly(A) polymerase (PAP). These findings indicate that HEN1 specifically methylates miRNAs and siRNAs and implicate the importance of the 2'-O-methyl group in the biology of RNA silencing