Metamorphic Protein IscU Changes Conformation by <i>cis</i>–<i>trans</i> Isomerizations of Two Peptidyl–Prolyl Peptide Bonds

IscU from <i>Escherichia coli</i>, the scaffold protein for iron–sulfur cluster biosynthesis and transfer, populates two conformational states with similar free energies and with lifetimes on the order of 1 s that interconvert in an apparent two-state reaction. One state (S) is structured, and the other (D) is largely disordered; however, both play essential functional roles. We report here nuclear magnetic resonance studies demonstrating that all four prolyl residues of apo-IscU (P14, P35, P100, and P101) are <i>trans</i> in the S state but that two absolutely conserved residues (P14 and P101) become <i>cis</i> in the D state. The peptidyl–prolyl peptide bond configurations were determined by analyzing assigned chemical shifts and were confirmed by measurements of nuclear Overhauser effects. We conclude that the S ⇄ D interconversion involves concerted <i>trans</i>–<i>cis</i> isomerization of the N13–P14 and P100–P101 peptide bonds. Although the D state is largely disordered, we show that it contains an ordered domain that accounts for the stabilization of two high-energy <i>cis</i> peptide bonds. Thus, IscU may be classified as a metamorphic protein

Relationship between recombinant protein expression and host metabolome as determined by two-dimensional NMR spectroscopy - Fig 3

<p><b>(a) PCA scores plot.</b> I (triangle), N (+), and S (x) represent samples expressing inclusion bodies, none, and soluble proteins, respectively. The source of the sample was denoted with 2-letter abbreviations: at, <i>Arabidopsis thaliana</i>; ce, <i>Caenorhabditis elegans</i>; cm, <i>Cyanidioschyzon merolae</i>; dr, <i>Danio rerio</i>; gs, <i>Galdieria sulphuraria</i>; hs, <i>Homo sapiens</i>; mm, <i>Mus musculus</i>; pp, <i>Photinus pyralis</i>; rn, <i>Rattus norvegicus</i>; sc, <i>Saccharomyces cerevisiae</i>. <b>(b) Biplot along the first and second principal component axes.</b> For better visibility, only the following metabolites were selected to avoid crowdedness: A, alanine; aK, N-acetyllysine; aki, alphaketoisovalerate; ap, acetylphosphate; b, betaine; GSSG, oxidized glutathione; gp, glycerol-3-phosphate; o, ornithine; V, valine.</p

Simultaneous Quantification and Identification of Individual Chemicals in Metabolite Mixtures by Two-Dimensional Extrapolated Time-Zero ¹H−¹³C HSQC (HSQC₀)

Quantitative one-dimensional (1D) ¹H NMR spectroscopy is a useful tool for determining metabolite concentrations because of the direct proportionality of signal intensity to the quantity of analyte. However, severe signal overlap in 1D ¹H NMR spectra of complex metabolite mixtures hinders accurate quantification. Extension of 1D ¹H to 2D ¹H−¹³C HSQC leads to the dispersion of peaks along the ¹³C dimension and greatly alleviates peak overlapping. Although peaks are better resolved in 2D ¹H−¹³C HSQC than in 1D ¹H NMR spectra, the simple proportionality of cross peaks to the quantity of individual metabolites is lost by resonance-specific signal attenuation during the coherence transfer periods. As a result, peaks for individual metabolites usually are quantified by reference to calibration data collected from samples of known concentration. We show here that data from a series of HSQC spectra acquired with incremented repetition times (the time between the end of the first ¹H excitation pulse to the beginning of data acquisition) can be extrapolated back to zero time to yield a time-zero 2D ¹H−¹³C HSQC spectrum (HSQC₀) in which signal intensities are proportional to concentrations of individual metabolites. Relative concentrations determined from cross peak intensities can be converted to absolute concentrations by reference to an internal standard of known concentration. Clustering of the HSQC₀ cross peaks by their normalized intensities identifies those corresponding to metabolites present at a given concentration, and this information can assist in assigning these peaks to specific compounds. The concentration measurement for an individual metabolite can be improved by averaging the intensities of multiple, nonoverlapping cross peaks assigned to that metabolite

Relationship between recombinant protein expression and host metabolome as determined by two-dimensional NMR spectroscopy - Fig 2

<p><b>(a) ROI view of the representative resonances of identified metabolites. (b) Barchart representation of ROI view.</b> Averages of metabolites within each group were converted to vertical bars with corresponding standard error bars.</p

Low-frequency region of the two-dimensional ¹H-¹³C HSQC spectrum of a sample (A1 of WG2137).

<p>Assigned resonances are labeled.</p

NMR Investigations of the Rieske Protein from <i>Thermus thermophilus</i> Support a Coupled Proton and Electron Transfer Mechanism

The Rieske protein component of the cytochrome <i>bc</i> complex contains a [2Fe−2S] cluster ligated by two cysteines and two histidines. We report here the p<i>K</i>_a values of each of the imidazole rings of the two ligating histidines (His134 and His154) in the oxidized and reduced states of the Rieske protein from <i>Thermus thermophilus</i> (<i>Tt</i>Rp) as determined by NMR spectroscopy. Knowledge of these p<i>K</i>_a values is of critical interest because of their pertinence to the mechanism of electron and proton transfer in the bifurcated Q-cycle. Although we earlier had observed the pH dependence of a ¹⁵N NMR signal from each of the two ligand histidines in oxidized <i>Tt</i>Rp (Lin, I. J.; Chen, Y.; Fee, J. A.; Song, J.; Westler, W. M.; Markley, J. L. J. Am. Chem. Soc. 2006, 128, 10672−10673), the strong paramagnetism of the [2Fe−2S] cluster prevented the assignment of these signals by conventional methods. Our approach here was to take advantage of the unique histidine−leucine (His134−Leu135) sequence and to use residue-selective labeling to establish a key sequence-specific assignment, which was then extended. Analysis of the pH dependence of assigned ¹³C′, ¹³C^α, and ¹⁵N^ε2 signals from the two histidine cluster ligands led to unambiguous assignment of the p<i>K</i>_a values of oxidized and reduced <i>Tt</i>Rp. The results showed that the p<i>K</i>_a of His134 changes from 9.1 in oxidized to ∼12.3 in reduced <i>Tt</i>Rp, whereas the p<i>K</i>_a of His154 changes from 7.4 in oxidized to ∼12.6 in reduced <i>Tt</i>Rp. This establishes His154, which is close to the quinone when the Rieske protein is in the cytochrome <i>b</i> site, as the residue experiencing the remarkable redox-dependent p<i>K</i>_a shift. Secondary structural analysis of oxidized and reduced <i>Tt</i>Rp based upon our extensive chemical shift assignments rules out a large conformational change between the oxidized and reduced states. Therefore, <i>Tt</i>Rp likely translocates between the cytochrome <i>b</i> and cytochrome <i>c</i> sites by passive diffusion. Our results are most consistent with a mechanism involving the coupled transfer of an electron and transfer of the proton across the hydrogen bond between the hydroquinone and His154 at the cytochrome <i>b</i> site

Three-Dimensional Structure and Determinants of Stability of the Iron–Sulfur Cluster Scaffold Protein IscU from <i>Escherichia coli</i>

The highly conserved protein, IscU, serves as the scaffold for iron–sulfur cluster (ISC) assembly in the ISC system common to bacteria and eukaryotic mitochondria. The apo-form of IscU from <i>Escherichia coli</i> has been shown to populate two slowly interconverting conformational states: one structured (S) and one dynamically disordered (D). Furthermore, single-site amino acid substitutions have been shown to shift the equilibrium between the metamorphic states. Here, we report three-dimensional structural models derived from NMR spectroscopy for the S-state of wild-type (WT) apo-IscU, determined under conditions where the protein was 80% in the S-state and 20% in the D-state, and for the S-state of apo-IscU­(D39A), determined under conditions where the protein was ∼95% in the S-state. We have used these structures in interpreting the effects of single site amino acid substitutions that alter %S = (100 × [S])/([S] + [D]). These include different residues at the same site, %S: D39V > D39L > D39A > D39G ≈ WT, and alanine substitutions at different sites, %S: N90A > S107A ≈ E111A > WT. Hydrophobic residues at residue 39 appear to stabilize the S-state by decreasing the flexibility of the loops that contain the conserved cysteine residues. The alanine substitutions at positions 90, 107, and 111, on the other hand, stabilize the protein without affecting the loop dynamics. In general, the stability of the S-state correlates with the compactness and thermal stability of the variant

Human Mitochondrial Ferredoxin 1 (FDX1) and Ferredoxin 2 (FDX2) Both Bind Cysteine Desulfurase and Donate Electrons for Iron–Sulfur Cluster Biosynthesis

Ferredoxins play an important role as an electron donor in iron–sulfur (Fe–S) cluster biosynthesis. Two ferredoxins, human mitochondrial ferredoxin 1 (FDX1) and human mitochondrial ferredoxin 2 (FDX2), are present in the matrix of human mitochondria. Conflicting results have been reported regarding their respective function in mitochondrial iron–sulfur cluster biogenesis. We report here biophysical studies of the interaction of these two ferredoxins with other proteins involved in mitochondrial iron–sulfur cluster assembly. Results from nuclear magnetic resonance spectroscopy show that both FDX1 and FDX2 (in both their reduced and oxidized states) interact with the protein complex responsible for cluster assembly, which contains cysteine desulfurase (NFS1), ISD11 (also known as LYRM4), and acyl carrier protein (Acp). In all cases, ferredoxin residues close to the Fe–S cluster are involved in the interaction with this complex. Isothermal titration calorimetry results showed that FDX2 binds more tightly to the cysteine desulfurase complex than FDX1 does. The reduced form of each ferredoxin became oxidized in the presence of the cysteine desulfurase complex when l-cysteine was added, leading to its conversion to l-alanine and the generation of sulfide. In an <i>in vitro</i> reaction, the reduced form of each ferredoxin was found to support Fe–S cluster assembly on ISCU; the rate of cluster assembly was faster with FDX2 than with FDX1. Taken together, these results show that both FDX1 and FDX2 can function in Fe–S cluster assembly <i>in vitro</i>

Mitochondrial Cysteine Desulfurase and ISD11 Coexpressed in <i>Escherichia coli</i> Yield Complex Containing Acyl Carrier Protein

Mitochondrial cysteine desulfurase is an essential component of the machinery for iron–sulfur cluster biosynthesis. It has been known that human cysteine desulfurase that is catalytically active <i>in vitro</i> can be prepared by overexpressing in <i>Escherichia coli</i> cells two protein components of this system, the cysteine desulfurase protein NFS1 and the auxiliary protein ISD11. We report here that this active preparation contains, in addition, the holo-form of <i>E. coli</i> acyl carrier protein (Acp). We have determined the stoichiometry of the complex to be [Acp]₂:[ISD11]₂:[NFS1]₂. Acyl carrier protein recently has been found to be an essential component of the iron–sulfur protein biosynthesis machinery in mitochondria; thus, because of the activity of [Acp]₂:[ISD11]₂:[NFS1]₂ in supporting iron–sulfur cluster assembly <i>in vitro</i>, it appears that <i>E. coli</i> Acp can substitute for its human homologue

Deconvolution of Two-Dimensional NMR Spectra by Fast Maximum Likelihood Reconstruction: Application to Quantitative Metabolomics

We have developed an algorithm called fast maximum likelihood reconstruction (FMLR) that performs spectral deconvolution of 1D–2D NMR spectra for the purpose of accurate signal quantification. FMLR constructs the simplest time-domain model (e.g., the model with the fewest number of signals and parameters) whose frequency spectrum matches the visible regions of the spectrum obtained from identical Fourier processing of the acquired data. We describe the application of FMLR to quantitative metabolomics and demonstrate the accuracy of the method by analysis of complex, synthetic mixtures of metabolites and liver extracts. The algorithm demonstrates greater accuracy (0.5–5.0% error) than peak height analysis and peak integral analysis with greatly reduced operator intervention. FMLR has been implemented in a Java-based framework that is available for download on multiple platforms and is interoperable with popular NMR display and processing software. Two-dimensional ¹H–¹³C spectra of mixtures can be acquired with acquisition times of 15 min and analyzed by FMLR in the range of 2–5 min per spectrum to identify and quantify constituents present at concentrations of 0.2 mM or greater