Mechanistic implications for the formation of the diiron cluster in ribonucleotide reductase provided by quantitative EPR spectroscopy

The small subunit of Escherichia coli ribonucleotide reductase (R2) is a homodimeric (betabeta) protein, in which each beta-peptide contains a diiron cluster composed of two inequivalent iron sites. R2 is capable of reductively activating O(2) to produce a stable tyrosine radical (Y122*), which is essential for production of deoxyribonucleotides on the larger R1 subunit. In this work, the paramagnetic Mn(II) ion is used as a spectroscopic probe to characterize the assembly of the R2 site with EPR spectroscopy. Upon titration of Mn(II) into samples of apoR2, we have been able to quantitatively follow three species (aquaMn(II), mononuclear Mn(II)R2, and dinuclear Mn(2)(II)R2) and fit each to a sequential two binding site model. As previously observed for Fe(II) binding within apoR2, one of the sites has a greater binding affinity relative to the other, K(1) = (5.5 +/- 1.1) x 10(5) M(-)(1) and K(2) = (3.9 +/- 0.6) x 10(4) M(-)(1), which are assigned to the B and A sites, respectively. In multiple titrations, only one dinuclear Mn(2)(II)R2 site was created per homodimer of R2, indicating that only one of the two beta-peptides of R2 is capable of binding Mn(II) following addition of Mn(II) to apoR2. Under anaerobic conditions, addition of only 2 equiv of Fe(II) to R2 (Fe(2)(II)R2) completely prevented the formation of any bound MnR2 species. Upon reaction of this sample with O(2) in the presence of Mn(II), both Y122* and Mn(2)(II)R2 were produced in equal amounts. Previous stopped-flow absorption spectroscopy studies have indicated that apoR2 undergoes a protein conformational change upon binding of metal (Tong et al. J. Am. Chem. Soc. 1996, 118, 2107-2108). On the basis of these observations, we propose a model for R2 metal incorporation that invokes an allosteric interaction between the two beta-peptides of R2. Upon binding the first equiv of metal to a beta-peptide (beta(I)), the aforementioned protein conformational change prevents metal binding in the adjacent beta-peptide (beta(II)) approximately 25 A away. Furthermore, we show that metal incorporation into beta(II) occurs only during the O(2) activation chemistry of the beta(I)-peptide. This is the first direct evidence of an allosteric interaction between the two beta-peptides of R2. Furthermore, this model can explain the generally observed low Fe occupancy of R2. We also demonstrate that metal uptake and this newly observed allosteric effect are buffer dependent. Higher levels of glycerol cause loss of the allosteric effect. Reductive cycling of samples in the presence of Mn(II) produced a novel mixed metal Fe(III)Mn(III)R2 species within the active site of R2. The magnitude of the exchange coupling (J) determined for both the Mn(2)(II)R2 and Fe(III)Mn(III)R2 species was determined to be -1.8 +/- 0.3 and -18 +/- 3 cm(-)(1), respectively. Quantitative spectral simulations for the Fe(III)Mn(III)R2 and mononuclear Mn(II)R2 species are provided. This work represents the first instance where both X- and Q-band simulations of perpendicular and parallel mode spectra were used to quantitatively predict the concentration of a protein bound mononuclear Mn(II) species.     

Aggregation-fragmentation in a model of DNA-mediated colloidal assembly

We present results from an off-lattice Monte Carlo simulation of DNA-mediated colloidal assembly. In this simulation, the aggregation-fragmentation of a binary mixture of DNA-coated colloidal particles is studied through a simplified model of base-pair hybridization. Bonding between monomers is modeled as a simple temperature-sensitive A/B-type interaction, where type A and B monomers can bond to only the opposite type (no A/A or B/B attachments are allowed). The actual chemistry of base-pair hybridization is not included in the model. The morphological structures of the clusters formed as well as the kinetics of growth are analyzed in our 2D simulations. The fractal dimension and kinetic growth exponents for clusters formed near the DNA "melting" temperature agree with those seen previously for 2D diffusion-limited cluster aggregation (DLCA) models. The clusters appear more compact, exhibiting signs of local order at intermediate temperature values. At higher temperatures, the formation of large clusters is not favorable under the action of temperature-dependent fragmentation, and the system eventually reaches a steady state as a collection of small aggregates. The temperature profile for this dissolution of the colloidal assembly is sharp, indicating that the selective hybridization process provides a highly sensitive measurement tool. At high temperatures, we analyze the steady-state behavior of the average cluster size in terms of an aggregation-fragmentation model.     

Classification of gasoline data obtained by gas chromatography using a piecewise alignment algorithm combined with feature selection and principal component analysis

A fast and objective chemometric classification method is developed and applied to the analysis of gas chromatography (GC) data from five commercial gasoline samples. The gasoline samples serve as model mixtures, whereas the focus is on the development and demonstration of the classification method. The method is based on objective retention time alignment (referred to as piecewise alignment) coupled with analysis of variance (ANOVA) feature selection prior to classification by principal component analysis (PCA) using optimal parameters. The degree-of-class-separation is used as a metric to objectively optimize the alignment and feature selection parameters using a suitable training set thereby reducing user subjectivity, as well as to indicate the success of the PCA clustering and classification. The degree-of-class-separation is calculated using Euclidean distances between the PCA scores of a subset of the replicate runs from two of the five fuel types, i.e., the training set. The unaligned training set that was directly submitted to PCA had a low degree-of-class-separation (0.4), and the PCA scores plot for the raw training set combined with the raw test set failed to correctly cluster the five sample types. After submitting the training set to piecewise alignment, the degree-of-class-separation increased (1.2), but when the same alignment parameters were applied to the training set combined with the test set, the scores plot clustering still did not yield five distinct groups. Applying feature selection to the unaligned training set increased the degree-of-class-separation (4.8), but chemical variations were still obscured by retention time variation and when the same feature selection conditions were used for the training set combined with the test set, only one of the five fuels was clustered correctly. However, piecewise alignment coupled with feature selection yielded a reasonably optimal degree-of-class-separation for the training set (9.2), and when the same alignment and ANOVA parameters were applied to the training set combined with the test set, the PCA scores plot correctly classified the gasoline fingerprints into five distinct clusters.     

Computer simulation of selective aggregation in binary colloids

The morphology of clusters formed by selective aggregation of binary colloids is studied in a two-dimensional Monte Carlo simulation for a large range of number fractions (200:1, 100:1, 10:1, 2:1). We find remarkable similarity in morphology to those observed in experiments, from the formation of closed "micelles" to large branched clusters. Quantitative studies of the fractal dimension, kinetics, and cluster size distribution are also carried out and compared with diffusion-limited cluster aggregation and reaction-limited cluster aggregation models.     

Environmental monitoring on shellfish using UV laser ablation ICP-MS

Laser ablation inductive coupled plasma – mass spectrometry (LA-ICP-MS) was used to analyse minor and trace elements in the hard parts of a shellfish, representing the environmental changes. A large, long-lived bivalve such as Arctica islandica can produce historical records of trace element fluctuations in seawater. Analytical traverses using LA-ICP-MS were performed from the inner to the outer wall of the shell at different locations. The development of the UV laser system now offers spatial resolution of craters of 10 m diameter, enabling several analyses between the various growthbands. The elemental changes between growthbands of the shell are discussed, showing the potential for precise determination of heavy-metal pollution over the years.     

Environmental monitoring on shellfish using UV laser ablation ICP-MS

Laser ablation inductive coupled plasma – mass spectrometry (LA-ICP-MS) was used to analyse minor and trace elements in the hard parts of a shellfish, representing the environmental changes. A large, long-lived bivalve such as Arctica islandica can produce historical records of trace element fluctuations in seawater. Analytical traverses using LA-ICP-MS were performed from the inner to the outer wall of the shell at different locations. The development of the UV laser system now offers spatial resolution of craters of 10 μm diameter, enabling several analyses between the various growthbands. The elemental changes between growthbands of the shell are discussed, showing the potential for precise determination of heavy-metal pollution over the years.