Assessment of scoring functions to rank the quality of 3D subtomogram clusters from cryo-electron tomography.

Cryo-electron tomography provides the opportunity for unsupervised discovery of endogenous complexes in situ. This process usually requires particle picking, clustering and alignment of subtomograms to produce an average structure of the complex. When applied to heterogeneous samples, template-free clustering and alignment of subtomograms can potentially lead to the discovery of structures for unknown endogenous complexes. However, such methods require scoring functions to measure and accurately rank the quality of aligned subtomogram clusters, which can be compromised by contaminations from misclassified complexes and alignment errors. Here, we provide the first study to assess the effectiveness of more than 15 scoring functions for evaluating the quality of subtomogram clusters, which differ in the amount of structural misalignments and contaminations due to misclassified complexes. We assessed both experimental and simulated subtomograms as ground truth data sets. Our analysis showed that the robustness of scoring functions varies largely. Most scores were sensitive to the signal-to-noise ratio of subtomograms and often required Gaussian filtering as preprocessing for improved performance. Two scoring functions, Spectral SNR-based Fourier Shell Correlation and Pearson Correlation in the Fourier domain with missing wedge correction, showed a robust ranking of subtomogram clusters without any preprocessing and irrespective of SNR levels of subtomograms. Of these two scoring functions, Spectral SNR-based Fourier Shell Correlation was fastest to compute and is a better choice for handling large numbers of subtomograms. Our results provide a guidance for choosing an accurate scoring function for template-free approaches to detect complexes from heterogeneous samples.

Structural Bases for the Fitness Cost of the Antibiotic-Resistance and Lethal Mutations at Position 1408 of 16S rRNA.

To understand a structural basis for the fitness cost of the A1408G antibiotic-resistance mutation in the ribosomal A-site RNA, we have determined crystal structures of its A1408C and A1408U lethal mutants, and made comparison with previously solved structures of the wild type and the antibiotic-resistant mutant. The A-site RNA containing an asymmetric internal loop functions as a molecular switch to discriminate a single cognate tRNA from several near-cognate tRNAs by its conformational ON/OFF switching. Overall structures of the "off" states of the A1408C/U lethal mutants are very similar to those of the wild type and the A1408G antibiotic-resistant mutant. However, significant differences are found in local base stacking interactions including the functionally important A1492 and A1493 residues. In the wild type and the A1408G antibiotic-resistant mutant "off" states, both adenines are exposed to the solvent region. On the other hand, one of the corresponding adenines of the lethal A1408C/U mutants stay deeply inside their A-site helices by forming a purine-pyrimidine AoC or A-U base pair and is sandwiched between the upper and lower bases. Therefore, the ON/OFF switching might unfavorably occur in the lethal mutants compared to the wild type and the A1408G antibiotic-resistant mutant. It is probable that bacteria manage to acquire antibiotic resistance without losing the function of the A-site molecular switch by mutating the position 1408 only from A to G, but not to pyrimidine base C or U.

Purification, characterization and cytotoxicity assessment of Ageritin: The first ribotoxin from the basidiomycete mushroom Agrocybe aegerita.

BACKGROUND: Several species belonging to Ascomycota phylum produce extracellular ribonucleases, known as ribotoxins, which exhibit RNase activity through the cleavage of a single phosphodiester bond, located at the universally conserved sarcin/ricin loop of the large rRNA leading to inhibition of protein biosynthesis. Clarifying the structure-function relationship in ribotoxins is interesting for their use in human tumour therapy and in construction of pest resistant transgenic plants. RESULTS: The ribotoxin Ageritin has been isolated for the first time from the Basidiomycetes class. The enzyme, characterized by means of its amino acid composition, N-terminal sequence and a circular dichroism, structurally differs from Ascomycota ribotoxin prototype, although it was able, as α-sarcin, to release a specific α-fragment. However, it does not display aspecific ribonucleolytic activity. Ageritin exerts cytotoxicity and cell death promoting effects towards CNS model cell lines (SK-N-BE(2)-C, U-251 and C6), as vinblastine, a plant alkaloid used in cancer therapy. Moreover, our results indicate that Ageritin initially activates caspase-8, whereas caspase-9 cleavage was not detected, demonstrating the involvement of an extrinsic apoptotic pathway. CONCLUSIONS: Our findings show that Ageritin is the earliest diverging member of the Ascomycota ribotoxin family, suggesting that ribotoxins are more widely distributed among fungi than previously believed. GENERAL SIGNIFICANCE: Ageritin, structurally different from the widely known Ascomycota ribotoxins, with promising anti-cancer properties vs. aggressive brain tumours, has been found from the basidiomycete fungus Agrocybe aegerita. Finally, this finding highlights that the ribotoxin family has divergent members in Basidiomycota phylum, whose structural and functional characterization can give new information on ribotoxin or ribonuclease superfamilies.

Multiple folding pathways of proteins with shallow knots and co-translational folding.

We study the folding process in the shallowly knotted protein MJ0366 within two variants of a structure-based model. We observe that the resulting topological pathways are much richer than identified in previous studies. In addition to the single knot-loop events, we find novel, and dominant, two-loop mechanisms. We demonstrate that folding takes place in a range of temperatures and the conditions of most successful folding are at temperatures which are higher than those required for the fastest folding. We also demonstrate that nascent conditions are more favorable to knotting than off-ribosome folding.

Residual Conformational Entropies on the Sugar-Phosphate Backbone of Nucleic Acids: An Analysis of the Nucleosome Core DNA and the Ribosome.

A nucleic acid folds according to its free energy, but persistent residual conformational fluctuations remain along its sugar-phosphate backbone even after secondary and tertiary structures have been assembled, and these residual conformational entropies provide a rigorous lower bound for the folding free energy. We extend a recently reported algorithm to calculate the residual backbone entropy along a RNA or DNA given configuration of its bases and apply it to the crystallographic structures of the 23S ribosomal subunit and DNAs in the nucleosome core particle. In the 23S rRNAs, higher entropic strains are concentrated in helices and certain tertiary interaction platforms while residues with high surface accessibility and those not involved in base pairing generally have lower strains. Upon folding, residual backbone entropy in the 23S subunit accounts for an average free energy penalty of +0.47 (kcal/mol)/nt (nt = nucleotide) at 310 K. In nucleosomal DNAs, backbone entropies show periodic oscillations with sequence position correlating with the superhelical twist and shifts in the base-pair-step geometries, and nucleosome positioning on the bound DNA exerts strong influence over where entropic strains are located. In contrast to rRNAs, residual backbone entropies account for a free energy penalty of only +0.09 (kcal/mol)/nt in duplex relative to single-stranded DNAs.

Composition of distinct sub-proteomes in Myxococcus xanthus: metabolic cost and amino acid availability.

Subsets of proteins involved in distinct functional processes are subject to different selective pressures. We investigated whether there is an amino acid composition bias (AACB) inherent in discrete subsets of proteins, and whether we could identify changing patterns of AACB during the life cycle of the social bacterium Myxococcus xanthus. We quantitatively characterised the cellular, soluble secreted, and outer membrane vesicle (OMV) sub-proteomes of M. xanthus, identifying 315 proteins. The AACB of the cellular proteome differed only slightly from that deduced from the genome, suggesting that genome-inferred proteomes can accurately reflect the AACB of their host. Inferred AA deficiencies arising from prey consumption were exacerbated by the requirements of the 68%GC genome, whose character thus seems to be selected for directly rather than via the proteome. In our analysis, distinct subsets of the proteome (whether segregated spatially or temporally) exhibited distinct AACB, presumably tailored according to the needs of the organism's lifestyle and nutrient availability. Secreted AAs tend to be of lower cost than those retained in the cell, except for the early developmental A-signal, which is a particularly costly sub-proteome. We propose a model of AA reallocation during the M. xanthus life cycle, involving ribophagy during early starvation and sequestration of limiting AAs within cells during development.

Progressive Stochastic Reconstruction Technique (PSRT) for cryo electron tomography.

Cryo Electron Tomography (cryoET) plays an essential role in Structural Biology, as it is the only technique that allows to study the structure of large macromolecular complexes in their close to native environment in situ. The reconstruction methods currently in use, such as Weighted Back Projection (WBP) or Simultaneous Iterative Reconstruction Technique (SIRT), deliver noisy and low-contrast reconstructions, which complicates the application of high-resolution protocols, such as Subtomogram Averaging (SA). We propose a Progressive Stochastic Reconstruction Technique (PSRT) - a novel iterative approach to tomographic reconstruction in cryoET based on Monte Carlo random walks guided by Metropolis-Hastings sampling strategy. We design a progressive reconstruction scheme to suit the conditions present in cryoET and apply it successfully to reconstructions of macromolecular complexes from both synthetic and experimental datasets. We show how to integrate PSRT into SA, where it provides an elegant solution to the region-of-interest problem and delivers high-contrast reconstructions that significantly improve template-based localization without any loss of high-resolution structural information. Furthermore, the locality of SA is exploited to design an importance sampling scheme which significantly speeds up the otherwise slow Monte Carlo approach. Finally, we design a new memory efficient solution for the specimen-level interior problem of cryoET, removing all associated artifacts.

Arginine-rhamnosylation as new strategy to activate translation elongation factor P.

Ribosome stalling at polyproline stretches is common and fundamental. In bacteria, translation elongation factor P (EF-P) rescues such stalled ribosomes, but only when it is post-translationally activated. In Escherichia coli, activation of EF-P is achieved by (R)-ß-lysinylation and hydroxylation of a conserved lysine. Here we have unveiled a markedly different modification strategy in which a conserved arginine of EF-P is rhamnosylated by a glycosyltransferase (EarP) using dTDP-L-rhamnose as a substrate. This is to our knowledge the first report of N-linked protein glycosylation on arginine in bacteria and the first example in which a glycosylated side chain of a translation elongation factor is essential for function. Arginine-rhamnosylation of EF-P also occurs in clinically relevant bacteria such as Pseudomonas aeruginosa. We demonstrate that the modification is needed to develop pathogenicity, making EarP and dTDP-L-rhamnose-biosynthesizing enzymes ideal targets for antibiotic development.

Bayesian orientation estimate and structure information from sparse single-molecule x-ray diffraction images.

We developed a Bayesian method to extract macromolecular structure information from sparse single-molecule x-ray free-electron laser diffraction images. The method addresses two possible scenarios. First, using a "seed" structural model, the molecular orientation is determined for each of the provided diffraction images, which are then averaged in three-dimensional reciprocal space. Subsequently, the real space electron density is determined using a relaxed averaged alternating reflections algorithm. In the second approach, the probability that the "seed" model fits to the given set of diffraction images as a whole is determined and used to distinguish between proposed structures. We show that for a given x-ray intensity, unexpectedly, the achievable resolution increases with molecular mass such that structure determination should be more challenging for small molecules than for larger ones. For a sufficiently large number of recorded photons (>200) per diffraction image an M^{1/6} scaling is seen. Using synthetic diffraction data for a small glutathione molecule as a challenging test case, successful determination of electron density was demonstrated for 20000 diffraction patterns with random orientations and an average of 82 elastically scattered and recorded photons per image, also in the presence of up to 50% background noise. The second scenario is exemplified and assessed for three biomolecules of different sizes. In all cases, determining the probability of a structure given set of diffraction patterns allowed successful discrimination between different conformations of the test molecules. A structure model of the glutathione tripeptide was refined in a Monte Carlo simulation from a random starting conformation. Further, effective distinguishing between three differently arranged immunoglobulin domains of a titin molecule and also different states of a ribosome in a tRNA translocation process was demonstrated. These results show that the proposed method is robust and enables structure determination from sparse and noisy x-ray diffraction images of single molecules spanning a wide range of molecular masses.

Dynamical phase transitions reveal amyloid-like states on protein folding landscapes.

Developing an understanding of protein misfolding processes presents a crucial challenge for unlocking the mysteries of human disease. In this article, we present our observations of ß-sheet-rich misfolded states on a number of protein dynamical landscapes investigated through molecular dynamics simulation and Markov state models. We employ a nonequilibrium statistical mechanical theory to identify the glassy states in a protein's dynamics, and we discuss the nonnative, ß-sheet-rich states that play a distinct role in the slowest dynamics within seven protein folding systems. We highlight the fundamental similarity between these states and the amyloid structures responsible for many neurodegenerative diseases, and we discuss potential consequences for mechanisms of protein aggregation and intermolecular amyloid formation.

An enumerative stepwise ansatz enables atomic-accuracy RNA loop modeling.

Atomic-accuracy structure prediction of macromolecules should be achievable by optimizing a physically realistic energy function but is presently precluded by incomplete sampling of a biopolymer's many degrees of freedom. We present herein a working hypothesis, called the "stepwise ansatz," for recursively constructing well-packed atomic-detail models in small steps, enumerating several million conformations for each monomer, and covering all build-up paths. By making use of high-performance computing and the Rosetta framework, we provide first tests of this hypothesis on a benchmark of 15 RNA loop-modeling problems drawn from riboswitches, ribozymes, and the ribosome, including 10 cases that are not solvable by current knowledge-based modeling approaches. For each loop problem, this deterministic stepwise assembly method either reaches atomic accuracy or exposes flaws in Rosetta's all-atom energy function, indicating the resolution of the conformational sampling bottleneck. As a further rigorous test, we have carried out a blind all-atom prediction for a noncanonical RNA motif, the C7.2 tetraloop/receptor, and validated this model through nucleotide-resolution chemical mapping experiments. Stepwise assembly is an enumerative, ab initio build-up method that systematically outperforms existing Monte Carlo and knowledge-based methods for 3D structure prediction.

Coarse-grained lattice model simulations of sequence-structure fitness of a ribosome-inactivating protein.

Many realistic protein-engineering design problems extend beyond the computational limits of what is considered practical when applying all-atom molecular-dynamics simulation methods. Lattice models provide computationally robust alternatives, yet most are regarded as too simplistic to accurately capture the details of complex designs. We revisit a coarse-grained lattice simulation model and demonstrate that a multiresolution modeling approach of reconstructing all-atom structures from lattice chains is of sufficient accuracy to resolve the comparability of sequence-structure modifications of the ricin A-chain (RTA) protein fold. For a modeled structure, the unfolding-folding transition temperature was calculated from the heat capacity using either the potential energy from the lattice model or the all-atom CHARMM19 force-field plus a generalized Born solvent approximation. We found, that despite the low-resolution modeling of conformational states, the potential energy functions were capable of detecting the relative change in the thermodynamic transition temperature that distinguishes between a protein design and the native RTA fold in excellent accord with reported experimental studies of thermal denaturation. A discussion is provided of different sequences fitted to the RTA fold and a possible unfolding model.

Lattice simulations of cotranslational folding of single domain proteins.

We use lattice protein models and Monte Carlo simulations to study cotranslational folding of small single domain proteins. We show that the assembly of native structure begins during late extrusion stages, but final formation of native state occurs during de novo folding, when all residues are extruded. There are three main results in our study. First, for the sequences displaying two-state refolding mechanism de novo cotranslational folding pathway differs from that sampled in in vitro refolding. The change in folding pathways is due to partial assembly of native interactions during extrusion that results in different starting conditions for in vitro refolding and for de novo cotranslational folding. For small single domain proteins cotranslational folding is slower than in vitro refolding, but is generally fast enough to be completed before the release from a ribosome. Second, we found that until final stages of biosynthesis cotranslational folding is essentially equilibrium. This observation is explained by low stability of structured states for partially extruded chains. Finally, our data suggest that the proteins, which refold in vitro slowly via intermediates, complete their de novo folding after the release from a ribosome. Comparison of our lattice cotranslational simulations with recent experimental and computational studies is discussed.

Protein translocation through a tunnel induces changes in folding kinetics: a lattice model study.

Compaction of a nascent polypeptide chain inside the ribosomal exit tunnel, before it leaves the ribosome, has been proposed to accelerate the folding of newly synthesized proteins following their release from the ribosome. Thus, we used Kinetic Monte Carlo simulations of a minimalist on-lattice model to explore the effect that polypeptide translocation through a variety of channels has on protein folding kinetics. Our results demonstrate that tunnel confinement promotes faster folding of a well-designed protein relative to its folding in free space by displacing the unfolded state towards more compact structures that are closer to the transition state. Since the tunnel only forbids rarely visited, extended configurations, it has little effect on a "poorly designed" protein whose unfolded state is largely composed of low-energy, compact, misfolded configurations. The beneficial effect of the tunnel depends on its width; for example, a too-narrow tunnel enforces unfolded states with limited or no access to the transition state, while a too-wide tunnel has no effect on the unfolded state entropy. We speculate that such effects are likely to play an important role in the folding of some proteins or protein domains in the cellular environment and might dictate whether a protein folds co-translationally or post-translationally.

Dependency map of proteins in the small ribosomal subunit.

The assembly of the ribosome has recently become an interesting target for antibiotics in several bacteria. In this work, we extended an analytical procedure to determine native state fluctuations and contact breaking to investigate the protein stability dependence in the 30S small ribosomal subunit of Thermus thermophilus. We determined the causal influence of the presence and absence of proteins in the 30S complex on the binding free energies of other proteins. The predicted dependencies are in overall agreement with the experimentally determined assembly map for another organism, Escherichia coli. We found that the causal influences result from two distinct mechanisms: one is pure internal energy change, the other originates from the entropy change. We discuss the implications on how to target the ribosomal assembly most effectively by suggesting six proteins as targets for mutations or other hindering of their binding. Our results show that by blocking one out of this set of proteins, the association of other proteins is eventually reduced, thus reducing the translation efficiency even more. We could additionally determine the binding dependency of THX--a peptide not present in the ribosome of E. coli--and suggest its assembly path.

Mean-field approaches to the totally asymmetric exclusion process with quenched disorder and large particles.

The process of protein synthesis in biological systems resembles a one-dimensional driven lattice gas in which the particles (ribosomes) have spatial extent, covering more than one lattice site. Realistic, nonuniform gene sequences lead to quenched disorder in the particle hopping rates. We study the totally asymmetric exclusion process with large particles and quenched disorder via several mean-field approaches and compare the mean-field results with Monte Carlo simulations. Mean-field equations obtained from the literature are found to be reasonably effective in describing this system. A numerical technique is developed for computing the particle current rapidly. The mean-field approach is extended to include two-point correlations between adjacent sites. The two-point results are found to match Monte Carlo simulations more closely.

EasyGene--a prokaryotic gene finder that ranks ORFs by statistical significance.

BACKGROUND: Contrary to other areas of sequence analysis, a measure of statistical significance of a putative gene has not been devised to help in discriminating real genes from the masses of random Open Reading Frames (ORFs) in prokaryotic genomes. Therefore, many genomes have too many short ORFs annotated as genes. RESULTS: In this paper, we present a new automated gene-finding method, EasyGene, which estimates the statistical significance of a predicted gene. The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Using extensions of similarities in Swiss-Prot, a high quality training set of genes is automatically extracted from the genome and used to estimate the HMM. Putative genes are then scored with the HMM, and based on score and length of an ORF, the statistical significance is calculated. The measure of statistical significance for an ORF is the expected number of ORFs in one megabase of random sequence at the same significance level or better, where the random sequence has the same statistics as the genome in the sense of a third order Markov chain. CONCLUSIONS: The result is a flexible gene finder whose overall performance matches or exceeds other methods. The entire pipeline of computer processing from the raw input of a genome or set of contigs to a list of putative genes with significance is automated, making it easy to apply EasyGene to newly sequenced organisms. EasyGene with pre-trained models can be accessed at http://www.cbs.dtu.dk/services/EasyGene.

A structural model for the assembly of the 30S subunit of the ribosome.

The order in which proteins bind to 16S rRNA, the assembly map, was determined by Nomura and co-workers in the early 1970s. The assembly map shows the dependencies of binding of successive proteins but fails to address the relationship of these dependencies to the three-dimensional folding of the ribosome. Here, using molecular mechanics techniques, we rationalize the order of protein binding in terms of ribosomal folding. We determined the specific contacts between the ribosomal proteins and 16S rRNA from a crystal structure of the 30S subunit (1FJG). We then used these contacts as restraints in a rigid body Monte-Carlo simulation with reduced-representation models of the RNA and proteins. Proteins were added sequentially to the RNA in the order that they appear in the assembly map. Our results show that proteins nucleate the folding of the head, platform, and body domains, but they do not strongly restrict the orientations of the domains relative to one another. We also examined the contributions of individual proteins to the formation of binding sites for sequential proteins in the assembly process. Binding sites for the primary binding proteins are generally more ordered in the naked RNA than those for other proteins. Furthermore, we examined one pathway in the assembly map and found that the addition of early binding proteins helps to organize the RNA around the binding sites of proteins that bind later. It appears that the order of assembly depends on the degree of pre-organization of each protein's binding site at a given stage of assembly, and the impact that the binding of each protein has on the organization of the remaining unoccupied binding sites.

The economics of ribosome biosynthesis in yeast.

In a rapidly growing yeast cell, 60% of total transcription is devoted to ribosomal RNA, and 50% of RNA polymerase II transcription and 90% of mRNA splicing are devoted to ribosomal proteins (RPs). Coordinate regulation of the approximately 150 rRNA genes and 137 RP genes that make such prodigious use of resources is essential for the economy of the cell. This is entrusted to a number of signal transduction pathways that can abruptly induce or silence the ribosomal genes, leading to major implications for the expression of other genes as well.