Monte Carlo simulation of two-component bilayers: DMPC/DSPC mixtures

In this paper, we describe a relatively simple lattice model of a two-component, two-state phospholipid bilayer. Application of Monte Carlo methods to this model permits simulation of the observed excess heat capacity versus temperature curves of dimyristoylphosphatidylcholine (DMPC)/distearoylphosphatidylcholine (DSPC) mixtures as well as the lateral distributions of the components and properties related to these distributions. The analysis of the bilayer energy distribution functions reveals that the gel-fluid transition is a continuous transition for DMPC, DSPC, and all DMPC/DSPC mixtures. A comparison of the thermodynamic properties of DMPC/DSPC mixtures with the configurational properties shows that the temperatures characteristics of the configurational properties correlate well with the maxima in the excess heat capacity curves rather than with the onset and completion temperatures of the gel-fluid transition. In the gel-fluid coexistence region, we also found excellent agreement between the threshold temperatures at different system compositions detected in fluorescence recovery after photobleaching experiments and the temperatures at which the percolation probability of the gel clusters is 0.36. At every composition, the calculated mole fraction of gel state molecules at the fluorescence recovery after photobleaching threshold is 0.34 and, at the percolation threshold of gel clusters, it is 0.24. The percolation threshold mole fraction of gel or fluid lipid depends on the packing geometry of the molecules and the interchain interactions. However, it is independent of temperature, system composition, and state of the percolating cluster.     

Geometrical properties of gel and fluid clusters in DMPC/DSPC bilayers: Monte Carlo simulation approach using a two-state model

In this paper the geometrical properties of gel and fluid clusters of equimolar dimyristoylphosphatidylcholine/distearoylphosphatidylcholine (DMPC/DSPC) lipid bilayers are calculated by using an Ising-type model (Sugar, I. P., T. E. Thompson, and R. L. Biltonen. 1999. Biophys. J. 76:2099-2110). The model is able to predict the following properties in agreement with the respective experimental data: the excess heat capacity curves, fluorescence recovery after photobleaching (FRAP) threshold temperatures at different mixing ratios, the most frequent center-to-center distance between DSPC clusters, and the fractal dimension of gel clusters. In agreement with the neutron diffraction and fluorescence microscopy data, the simulations show that below the percolation threshold temperature of gel clusters many nanometer-size gel clusters co-exist with one large gel cluster of size comparable with the membrane surface area. With increasing temperature the calculated effective fractal dimension and capacity dimension of gel and fluid clusters decrease and increase, respectively, within the (0, 2) interval. In the region of the gel-to-fluid transition the following geometrical properties are independent from the temperature and the state of the cluster: 1) the cluster perimeter linearly increases with the number of cluster arms at a rate of 8.2 nm/arm; 2) the average number of inner islands in a cluster increases with increasing cluster size, S, according to a power function of 0.00427 x S(1.3); 3) the following exponential function describes the average size of an inner island versus the size of the host cluster, S: 1 + 1.09(1 - e(-0.0072xS)). By means of the equations describing the average geometry of the clusters the process of the association of clusters is investigated.     

Component and state separation in DMPC/DSPC lipid bilayers: a Monte Carlo simulation study

In this paper a two-state, two-component, Ising-type model is used to simulate the lateral distribution of the components and gel/fluid state acyl chains in dimyristoylphosphatidylcholine/distearoylphosphatidylcholine (DMPC/DSPC) lipid bilayers. The same model has been successful in calculating the excess heat capacity curves, the fluorescence recovery after photobleaching (FRAP) threshold temperatures, the most frequent center-to-center distances between DSPC clusters, and the fractal dimensions of gel clusters (Sugar, I. P., T. E. Thompson, and R. L. Biltonen, 1999. Biophys. J. 76:2099-2110). Depending on the temperature and mole fraction the population of the cluster size is either homogeneous or inhomogeneous. In the inhomogeneous population the size of the largest cluster scales with the size of the system, while the rest of the clusters remain small with increasing system size. In a homogeneous population, however, every cluster remains small with increasing system size. For both compositional and fluid/gel state clusters, threshold temperatures-the so-called percolation threshold temperatures-are determined where change in the type of the population takes place. At a given mole fraction, the number of percolation threshold temperatures can be 0, 1, 2, or 3. By plotting these percolation threshold temperatures on the temperature/mole fraction plane, the diagrams of component and state separation of DMPC/DSPC bilayers are constructed. In agreement with the small-angle neutron scattering measurements, the component separation diagram shows nonrandom lateral distribution of the components not only in the gel-fluid mixed phase region, but also in the pure gel and pure fluid regions. A combined diagram of component and state separation is constructed to characterize the lateral distribution of lipid components and gel/fluid state acyl chains in DMPC/DSPC mixtures. While theoretical phase diagrams of two component mixtures can be constructed only in the case of first-order transitions, state and component separation diagrams can be constructed whether or not the system is involved in first-order transition. The effects of interchain interactions on the component and state separation diagrams are demonstrated on three different models. The influences of state and component separation on the in-plane and off-plane membrane reactions are discussed.     

Computer simulation of surface-induced aggregation of ferritin.

Models are presented describing the transient mass-transport limited adsorption and cluster growth of ferritin at a solid surface. Computer simulations are carried out on a hexagonal lattice using a computer model that can be characterized as a two-dimensional stochastic cellular automaton allowing different rules regarding association, lateral interaction and dissociation to be incorporated in the model. The fractal dimensions of individual clusters were extracted from simulated aggregates and for similar rules found to be consistent with literature values on reversible diffusion-limited aggregation in two dimensions. The distribution of clusters versus free surface were shown to be affected by neighbor-dependent association probability. Low fractal dimension clusters were generated by a combination of strong lateral cohesion and neighbor-dependent dissociation to the bulk. By comparing computer simulated aggregation to experimental electron micrographs of adsorbed ferritin layers it is suggested that neighbor-dependent association, neighbor-dependent dissociation and lateral interactions are important factors in the complex dynamics of adsorbed protein layers.     

Fractal bird nest distribution produces scale-free colony sizes

The spatial distribution of organisms often differs across scales. For instance, colonial bird populations could be described, from large to small scale, as scattered clumps of otherwise regularly distributed breeding pairs. We analysed the distribution of nests of a large colonial population of white storks (Ciconia ciconia) and found a fractal pattern in each of the 4 study years. Moreover, we found that the often-observed, long-tailed frequency distribution of colony sizes was well described by a power law, regardless of the cut-off used to define colonies (from 16 to 1024 m). Thus, although storks were locally highly clumped even with tens of nests in a single tree, the population was not structured in colonies (a simple clustered distribution) as previously thought. Rather, they were distributed in a continuous hierarchical set of clusters within clusters across scales, clusters lacking the commonly assumed characteristic mean size. These quantitative solutions to previously perceived scaling problems will potentially improve our understanding of the ecology and evolution of bird coloniality and animal spacing patterns and group living in general.     

Comparative genomic analysis reveals evolutionary characteristics and patterns of microRNA clusters in vertebrates

MicroRNAs (miRNAs) are a class of small non-coding RNAs that can play important regulatory roles in many important biological processes. Although clustering patterns of miRNA clusters have been uncovered in animals, the origin and evolution of miRNA clusters in vertebrates are still poorly understood. Here, we performed comparative genomic analyses to construct 51 sets of orthologous miRNA clusters (SOMCs) across seven test vertebrate species, a collection of miRNA clusters from two or more species that are likely to have evolved from a common ancestral miRNA cluster, and used these to systematically examine the evolutionary characteristics and patterns of miRNA clusters in vertebrates. We found that miRNA clusters are continuously generated, and most of them tend to be conserved and maintained in vertebrate genomes, although some adaptive gains and losses of miRNA cluster have occurred during evolution. Furthermore, miRNA clusters appeared relatively early in the evolutionary history might suffer from more complicated adaptive gain-and-loss than those young miRNA clusters. Detailed analysis showed that genomic duplication events of ancestral miRNAs or miRNA clusters are likely to be major driving force and apparently contribute to origin and evolution of miRNA clusters. Comparison of conserved with lineage-specific miRNA clusters revealed that the contribution of duplication events for the formation of miRNA cluster appears to be more important for conserved miRNA clusters than lineage-specific. Our study provides novel insights for further exploring the origins and evolution of miRNA clusters in vertebrates at a genome scale.     

Characterization of lipid membrane dynamics by simulation: I. Torsion angle motions of the linear chains

The torsion angle motions, generated from molecular dynamics (MD) simulations, of the two aliphatic chains of 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine (DMPC) in its lipid monolayer were evaluated by comparing these motions to those of an equivalent isolated (free) n-alkane chain, and the same n-alkane chain in its crystal lattice. The time-dependent autocorrelation and (1,2)-, (1,3)-, (1,4)-, and (1,5)-cross-correlation functions were constructed to analyze the torsion angle motions. It was found that the torsion angle motions of the DMPC lipid monolayer aliphatic chains are intermediate to those of the free n-alkane chain and the same n-alkane chain in its crystal lattice, particularly for short correlation times. The torsion angle motions of the aliphatic chains of DMPC are also found to be essentially independent of the charge state on the head group. The linear aliphatic chains of a DMPC lipid monolayer behave most like the isolated n-alkane chains with respect to torsion angle flexibility, even though the pairs of aliphatic chains of each DMPC are part of an ordered monolayer assembly. The aliphatic chains of the DMPC molecules in their monolayer exhibit at least two types of wave motions. One of the wave motions is the same in form, though somewhat more diffuse, as a traveling wave found in n-alkane crystals. The other wave motion involves major torsion angle transitions, and has some characteristics of the soliton properties observed in n-alkane crystals near their respective melt transition temperatures. © 1997 John Wiley & Sons, Inc.     

Simulation study on the disordered state of an Alzheimer's beta amyloid peptide Abeta(12 36) in water consisting of random-structural, beta-structural, and helical clusters

The monomeric Alzheimer's beta amyloid peptide, Abeta, is known to adopt a disordered state in water at room temperature, and a circular dichroism (CD) spectroscopy experiment has provided the secondary-structure contents for the disordered state: 70% random, 25% beta-structural, and 5% helical. We performed an enhanced conformational sampling (multicanonical molecular dynamics simulation) of a 25-residue segment (residues 12-36) of Abeta in explicit water and obtained the conformational ensemble over a wide temperature range. The secondary-structure contents calculated from the conformational ensemble at 300 degrees K reproduced the experimental secondary-structure contents. The constructed free-energy landscape at 300 degrees K was not plain but rugged with five clearly distinguishable clusters, and each cluster had its own characteristic tertiary structure: a helix-structural cluster, two beta-structural clusters, and two random-structural clusters. This indicates that the contribution from the five individual clusters determines the secondary-structure contents experimentally measured. The helical cluster had a similarity with a stable helical structure for monomeric Abeta in 2,2,2-trifluoroethanol (TFE)/water determined by an NMR experiment: The positions of helices in the helical cluster were the same as those in the NMR structure, and the residue-residue contact patterns were also similar with those of the NMR structure. The cluster-cluster separation in the conformational space indicates that free-energy barriers separate the clusters at 300 degrees K. The two beta-structural clusters were characterized by different strand-strand hydrogen-bond (H-bond) patterns, suggesting that the free-energy barrier between the two clusters is due to the H-bond rearrangements.     

A Tight-binding Molecular Dynamics Study of the Dissociation of Boron Clusters in c-Si

Boron clusters with silicon self-interstitials have been implicated in the phenomenon of transient enhanced diffusion (TED) following ion implantation of boron and subsequent annealing steps. This paper explores possible dissolution mechanisms for boron-interstitial clusters during the simulation of a typical annealing process. Using tight-binding molecular dynamics (TBMD) and employing a Goodwin-Skinner-Pettifor sp-based TB model, we have been able to observe the complete dissolution of a B 4 I 4 cluster into the surrounding crystalline silicon matrix. Many unsuccessful attempts to observe dissolution are also presented, highlighting the effect of cluster stability, temperature and the role of vacancies in cluster dissolution. Though we can make no unambiguous statements on the definitive dissolution mechanism of boron-defect clusters based on one successful dissolution event, we can hint at key events that appear to be important, such as the diffusion of self-interstitials (presciently predicted by Pelaz et al. ), the "stranding" of boron atoms in their wake, and the importance of mobile boron-self-interstitial (B-I) pairs. The intrinsic diffusivity of boron in a c-Si lattice and its retardation of the diffusivity of Si self-interstitials is also discussed.     

Molecular Dynamics Simulations of Mixed Acidic/Zwitterionic Phospholipid Bilayers

Anionic lipids are key components in the cell membranes. Many cell-regulatory and signaling mechanisms depend upon a complicated interplay between them and membrane-bound proteins. Phospholipid bilayers are commonly used as model systems in experimental or theoretical studies to gain insight into the structure and dynamics of biological membranes. We report here 200-ns-long MD simulations of pure (DMPC and DMPG) and mixed equimolar (DMPC/DMPG, DMPC/DMPS, and DMPC/DMPA) bilayers that each contain 256 lipids. The intra- and intermolecular interaction patterns in pure and mixed bilayers are analyzed and compared. The effect of monovalent ions (Na⁺) on the formation of salt-bridges is investigated. In particular, the number of Na⁺-mediated clusters in the presence of DMPS is higher than with DMPG and DMPA. We observe a preferential clustering of DMPS (and to some extent DMPA) lipids together rather than with DMPC molecules, which can explain the phase separation observed experimentally for DMPC/DMPS and DMPC/DMPA bilayers.     

Tests for inbreeding and outbreeding depression and estimation of population differentiation in the bird-pollinated shrub Grevillea mucronulata

Background and Aims

Plants show patterns of spatial genetic differentiation reflecting gene flow mediated by pollen and seed dispersal and genotype × environment interactions. If patterns of genetic structure are determined largely by gene flow then they may be useful in predicting the likelihood of inbreeding or outbreeding depression but should be less useful if there is strong site-specific selection. For many Australian plants little is known about either their population genetics or the effects on mating systems of variation in pollen transfer distances. Experimental pollinations were used to compare the reproductive success of bird-adapted Grevillea mucronulata plants mated with individuals from a range of spatial scales. A hierarchical survey of microsatellite DNA variation was also conducted to describe the scale of population differentiation for neutral markers.

Methods

The effects of four pollen treatments on reproductive performance were compared. These treatments were characterized by transfer of pollen from (a) neighbouring adults; (b) an adjacent cluster of adults (30–50 m distant); (c) a distant cluster (>5 km distant); and (d) open pollination. Sets of 17·9 ± 3·3 leaves from each of 15 clusters of plants were genotyped and spatial autocorrelation and F statistics were used to describe patterns of genetic structure.

Key Results

Grevillea mucronulata displayed evidence of both inbreeding and outbreeding depression, with ‘intermediate’ pollen producing consistently superior outcomes for most aspects of fitness including seed set, seed size, germination and seedling growth. Significant genotypic structuring was detected within clusters (spatial autocorrelation) and among adjacent clusters and clusters separated by >5 km distance (F_ST = 0·07 and 0·10).

Conclusions

The superior outcome of intermediate pollen transfer and genetic differentiation of adjacent clusters suggests that G. mucronulata selection disfavours matings among closely and distantly related neighbours. Moreover, the performance of open-pollinated seedlings was poor, implying that current mating patterns are suboptimal.     

Population substructure and space use of Foxe Basin polar bears

Climate change has been identified as a major driver of habitat change, particularly for sea ice-dependent species such as the polar bear (Ursus maritimus). Population structure and space use of polar bears have been challenging to quantify because of their circumpolar distribution and tendency to range over large areas. Knowledge of movement patterns, home range, and habitat is needed for conservation and management. This is the first study to examine the spatial ecology of polar bears in the Foxe Basin management unit of Nunavut, Canada. Foxe Basin is in the mid-Arctic, part of the seasonal sea ice ecoregion and it is being negatively affected by climate change. Our objectives were to examine intrapopulation spatial structure, to determine movement patterns, and to consider how polar bear movements may respond to changing sea ice habitat conditions. Hierarchical and fuzzy cluster analyses were used to assess intrapopulation spatial structure of geographic position system satellite-collared female polar bears. Seasonal and annual movement metrics (home range, movement rates, time on ice) and home-range fidelity (static and dynamic overlap) were compared to examine the influence of regional sea ice on movements. The polar bears were distributed in three spatial clusters, and there were differences in the movement metrics between clusters that may reflect sea ice habitat conditions. Within the clusters, bears moved independently of each other. Annual and seasonal home-range fidelity was observed, and the bears used two movement patterns: on-ice range residency and annual migration. We predict that home-range fidelity may decline as the spatial and temporal predictability of sea ice changes. These new findings also provide baseline information for managing and monitoring this polar bear population.     

A two-step patterning process increases the robustness of periodic patterning in the fly eye

Complex periodic patterns can self-organize through dynamic interactions between diffusible activators and inhibitors. In the biological context, self-organized patterning is challenged by spatial heterogeneities (‘noise’) inherent to biological systems. How spatial variability impacts the periodic patterning mechanism and how it can be buffered to ensure precise patterning is not well understood. We examine the effect of spatial heterogeneity on the periodic patterning of the fruit fly eye, an organ composed of ～800 miniature eye units (ommatidia) whose periodic arrangement along a hexagonal lattice self-organizes during early stages of fly development. The patterning follows a two-step process, with an initial formation of evenly spaced clusters of ～10 cells followed by a subsequent refinement of each cluster into a single selected cell. Using a probabilistic approach, we calculate the rate of patterning errors resulting from spatial heterogeneities in cell size, position and biosynthetic capacity. Notably, error rates were largely independent of the desired cluster size but followed the distributions of signaling speeds. Pre-formation of large clusters therefore greatly increases the reproducibility of the overall periodic arrangement, suggesting that the two-stage patterning process functions to guard the pattern against errors caused by spatial heterogeneities. Our results emphasize the constraints imposed on self-organized patterning mechanisms by the need to buffer stochastic effects. Author summary Complex periodic patterns are common in nature and are observed in physical, chemical and biological systems. Understanding how these patterns are generated in a precise manner is a key challenge. Biological patterns are especially intriguing, as they are generated in a noisy environment; cell position and cell size, for example, are subject to stochastic variations, as are the strengths of the chemical signals mediating cell-to-cell communication. The need to generate a precise and robust pattern in this ‘noisy’ environment restricts the space of patterning mechanisms that can function in the biological setting. Mathematical modeling is useful in comparing the sensitivity of different mechanisms to such variations, thereby highlighting key aspects of their design.We use mathematical modeling to study the periodic patterning of the fruit fly eye. In this system, a highly ordered lattice of differentiated cells is generated in a two-dimensional cell epithelium. The pattern is first observed by the appearance of evenly spaced clusters of ～10 cells that express specific genes. Each cluster is subsequently refined into a single cell, which initiates the formation and differentiation of a miniature eye unit, the ommatidium. We formulate a mathematical model based on the known molecular properties of the patterning mechanism, and use a probabilistic approach to calculate the errors in cluster formation and refinement resulting from stochastic cell-to-cell variations (‘noise’) in different quantitative parameters. This enables us to define the parameters most influencing noise sensitivity. Notably, we find that this error is roughly independent of the desired cluster size, suggesting that large clusters are beneficial for ensuring the overall reproducibility of the periodic cluster arrangement. For the stage of cluster refinement, we find that rapid communication between cells is critical for reducing error. Our work provides new insights into the constraints imposed on mechanisms generating periodic patterning in a realistic, noisy environment, and in particular, discusses the different considerations in achieving optimal design of the patterning network.     

The fractal architecture of cytoplasmic organization: Scaling,kinetics and emergence in metabolic networks

In this work, we highlight the links between fractals and scaling in cells and explore the kinetic consequences for biochemical reactions operating in fractal media. Based on the proposal that the cytoskeletal architecture is organized as a percolation lattice, with clusters emerging as fractal forms, the analysis of kinetics in percolation clusters is especially emphasized. A key consequence of this spatiotemporal cytoplasmic organization is that enzyme reactions following Michaelis-Menten or allosteric type kinetics exhibit higher rates in fractal media (for short times and at lower substrate concentrations) at the percolation threshold than in Euclidean media. As a result, considerably faster and higher amplification of enzymatic activity is obtained. Finally, we describe some of the properties bestowed by cytoskeletal organization and dynamics on metabolic networks.     

Conformation of nifedipine in hydrated 1,2-di-myristoyl-sn-glycero-3-phosphorylcholine bilayer molecular dynamics simulation

The conformation of nifedipine, a cardiac and smooth muscle calcium ion channel antagonist is studied in a hydrated bilayer of forty nine 1,2-di-myristoyl-sn-glycero-3-phosphorylcho-line (DMPC) molecules using molecular dynamics (MD) simulation technique. The simulation was carried out in conditions of constant number, volume and temperature (NVT) at 310 K, which is above the liquid crystalline (Lα) transition temperature of DMPC. The periodic boundary conditions were applied in three-dimensions. Thus the model represented an infinite bilayer. The important geometric parameters characteristic to DMPC and nifedipine molecules were calculated and compared with other theoretical and experimental results pertaining to nifedipine and other related dihydrophyridine (DHP) analogues. Our results suggest that conformational parameters required for antagonist activity are fairly conserved during the interaction of nifedipine with DMPC bilary and bilayer stabilizes the drug conformation in the bioactive form.     

Topology of gel-phase domains and lipid mixing properties in phase-separated two-component phosphatidylcholine bilayers.

The influence of the lipid mixing properties on the lateral organization in a two-component, two-phase phosphatidylcholine bilayer was investigated using both an experimental (fluorescence recovery after photobleaching (FRAP)) and a simulated (Monte Carlo) approach. With the FRAP technique, we have examined binary mixtures of 1-stearoyl-2-capryl-phosphatidylcholine/1,2-distearoyl-phosphat idylcholine (C18C10PC/DSPC), and 1-stearoyl-2-capryl-phosphatidylcholine/1,2-dipalmitoyl-phospha tid ylcholine (C18C10PC/DPPC). Comparison with the 1,2-dimyristoyl-phosphatidylcholine/1,2-distearoyl-phosphatidylcholine (DMPC/DSPC) previously investigated by FRAP by Vaz and co-workers (Biophys. J., 1989, 56:869-876) shows that the gel phase domains become more effective in restricting the diffusion coefficient when the ideality of the mixture increases (i.e., in the order C18C10PC/DSPC-->C18C10PC/DPPC-->DMPC/DSPC). However, an increased lipid miscibility is accompanied by an increasing compositional dependence: the higher the proportion of the high-temperature melting component, the less efficient the gel phase is in compartmentalizing the diffusion plane, a trend that is best accounted for by a variation of the gel phase domain shape rather than size. Computer-simulated fluorescence recoveries obtained in a matrix obstructed with obstacle aggregates of various fractal dimension demonstrate that: 1) for a given obstacle size and area fraction, the relative diffusion coefficient increases linearly with the obstacle fractal dimension and 2) aggregates with a lower fractal dimension are more efficient in compartmentalizing the diffusion plane. Comparison of the simulated with the experimental mobile fractions strongly suggests that the fractal dimension of the gel phase domains increases with the proportion of high-temperature melting component in DMPC/DSPC and (slightly) in C18C10PC/DPPC.     

Monomethylarsonate (MMAv) exerts stronger effects than arsenate on the structure and thermotropic properties of phospholipids bilayers

Methylation of inorganic arsenic has been regarded as a detoxification mechanism because its metabolites monomethylarsonic acid (MMA(v)) and dimethylarsinic acid (DMA(v)) are supposed to be less toxic than inorganic arsenite and arsenate. In recent years, however, this interpretation has been questioned. Additionally, there are insufficient reports concerning the effects of arsenic compounds on cell membrane structure and functions. With the aim to better understand the molecular mechanisms of the interaction of MMA(v) and arsenate with cell membranes, we have utilized molecular models consisting in bilayers of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylethanolamine (DMPE), representative of phospholipid classes located in the outer and inner monolayers of many cell membranes including that of the human erythrocyte. The capacity of MMA(v) and arsenate to perturb the bilayer structures of DMPC and DMPE was evaluated by X-ray diffraction; the modifications of their thermotropic behavior were followed by differential scanning calorimetry (DSC), while DMPC large unilamellar vesicles (LUV) were studied by fluorescence spectroscopy. It was found that MMA(v) and arsenate did not structurally perturb DMPC bilayers; however, DMPE bilayers did suffer structural perturbations by MMA(v). DSC measurements also revealed that DMPE's thermotropic properties were significantly affected by arsenicals, where MMA(v) was more effective than arsenate, whilst only slight modifications were observed in the case of DMPC-MMA(v) system.     

Chloroplast monothiol glutaredoxins as scaffold proteins for the assembly and delivery of [2Fe-2S] clusters

Glutaredoxins (Grxs) are small oxidoreductases that reduce disulphide bonds or protein-glutathione mixed disulphides. More than 30 distinct grx genes are expressed in higher plants, but little is currently known concerning their functional diversity. This study presents biochemical and spectroscopic evidence for incorporation of a [2Fe-2S] cluster in two heterologously expressed chloroplastic Grxs, GrxS14 and GrxS16, and in vitro cysteine desulphurase-mediated assembly of an identical [2Fe-2S] cluster in apo-GrxS14. These Grxs possess the same monothiol CGFS active site as yeast Grx5 and both were able to complement a yeast grx5 mutant defective in Fe-S cluster assembly. In vitro kinetic studies monitored by CD spectroscopy indicate that [2Fe-2S] clusters on GrxS14 are rapidly and quantitatively transferred to apo chloroplast ferredoxin. These data demonstrate that chloroplast CGFS Grxs have the potential to function as scaffold proteins for the assembly of [2Fe-2S] clusters that can be transferred intact to physiologically relevant acceptor proteins. Alternatively, they may function in the storage and/or delivery of preformed Fe-S clusters or in the regulation of the chloroplastic Fe-S cluster assembly machinery.