COORDINATION CHEMISTRY OF BIS(BENZYL)PHOSPHINATE

The work presented in this dissertation deals with the coordination chemistry of the bis(benzyl)phosphinate ligand with vanadium, tungsten and cobalt. The long term goal of this project was to produce and physically characterize high oxidation state transition metal oxide phosphinate compounds with potential catalytic applications. The reaction of bis(benzyl)phosphinic acid with VO(acac)2 in the presence of water or pyridine leads to the synthesis of trimeric vanadium(IV) clusters (V3(µ3-O)O2)(µ2-O2P(CH2C6H5)2)6(H2O) and (V3(µ3-O)O2)(µ2-O2P(CH2C6H5)2)6(py). In contrast, when diphenylphosphinic acid or 2-hydroxyisophosphindoline-2-oxide were reacted with VO(acac)2, insoluble polymeric compounds were produced. The trimeric clusters were characterized using FTIR, elemental analysis, single crystal diffraction, room temperature magnetic susceptibility, thermogravimetric analysis and differential scanning calorimetry. The variable-temperature, solid-state magnetic susceptibility was measured on (V3(µ3-O)O2)(µ2-O2P(CH2C6H5)2)6(py). The polymeric compounds were characterized using FTIR, powder diffraction and elemental analysis. Two different cubane clusters made of tungsten(V) and vanadium(V) were stabilized using bis(benzyl)phosphinate. The oxidation of (V3(µ3-O)O2)(µ2-O2P(CH2C6H5)2)6(H2O) with tBuOOH led to the formation of V4(µ3-O)4(µ2-O2P(Bn)2)4(O4). W4(µ3-O)4(µ2-O2P(Bn)2)4(O4) was produced by heating W(CO)6 in a 1:1 mixture of EtOH/THF at 120 ˚C. Both compounds were characterized using single crystal diffraction, FTIR, 31P-NMR, 1H-NMR and elemental analysis. W4(µ3-O)4(µ2-O2P(Bn)2)4(O4) was also characterized using UV-vis. Cobalt(II) reacted with bis(benzyl)phosphinate to produce three different dinuclear complexes. [(py)3Co(µ2-O2P(Bn)2)3Co(py)][ClO4], (py)3Co(µ2-O2P(Bn)2)3Co(Cl) and (py)(µ2-NO3)Co(µ2-O2P(Bn)2)3Co(py) were all characterized using single crystal diffraction, elemental analysis and FTIR. Room temperature magnetic susceptibility measurements were performed on [(py)3Co(µ2-O2P(Bn)2)3Co(py)][ClO4] and (py)3Co(µ2-O2P(Bn)2)3Co(Cl). The variable-temperature, solid-state magnetic susceptibility was also measured on [(py)3Co(µ2-O2P(Bn)2)3Co(py)][ClO4].

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.