José María Carazo

GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists

We present GENECODIS, a web-based tool that integrates different sources of information to search for annotations that frequently co-occur in a set of genes and rank them by statistical significance. The analysis of concurrent annotations provides significant information for the biologic interpretation of high-throughput experiments and may outperform the results of standard methods for the functional analysis of gene lists. GENECODIS is publicly available at http://genecodis.dacya.ucm.es/.

Image processing for electron microscopy single-particle analysis using XMIPP

We describe a collection of standardized image processing protocols for electron microscopy single-particle analysis using the XMIPP software package. These protocols allow performing the entire processing workflow starting from digitized micrographs up to the final refinement and evaluation of 3D models. A particular emphasis has been placed on the treatment of structurally heterogeneous data through maximum-likelihood refinements and self-organizing maps as well as the generation of initial 3D models for such data sets through random conical tilt reconstruction methods. All protocols presented have been implemented as stand-alone, executable python scripts, for which a dedicated graphical user interface has been developed. Thereby, they may provide novice users with a convenient tool to quickly obtain useful results with minimum efforts in learning about the details of this comprehensive package. Examples of applications are presented for a negative stain random conical tilt data set on the hexameric helicase G40P and for a structurally heterogeneous data set on 70S Escherichia coli ribosomes embedded in vitrified ice.

Phylogenetic Reconstruction Using an Unsupervised Growing Neural Network That Adopts the Topology of a Phylogenetic Tree

Abstract. We propose a new type of unsupervised, growing, self-organizing neural network that expands itself by following the taxonomic relationships that exist among the sequences being classified. The binary tree topology of this neutral network, contrary to other more classical neural network topologies, permits an efficient classification of sequences. The growing nature of this procedure allows to stop it at the desired taxonomic level without the necessity of waiting until a complete phylogenetic tree is produced. This novel approach presents a number of other interesting properties, such as a time for convergence which is, approximately, a lineal function of the number of sequences. Computer simulation and a real example show that the algorithm accurately finds the phylogenetic tree that relates the data. All this makes the neural network presented here an excellent tool for phylogenetic analysis of a large number of sequences.

Quaternary structures of tumor suppressor p53 and a specific p53–DNA complex

The homotetrameric tumor suppressor p53 consists of folded core and tetramerization domains, linked and flanked by intrinsically disordered segments that impede structure analysis by x-ray crystallography and NMR. Here, we solved the quaternary structure of human p53 in solution by a combination of small-angle x-ray scattering, which defined its shape, and NMR, which identified the core domain interfaces and showed that the folded domains had the same structure in the intact protein as in fragments. We combined the solution data with electron microscopy on immobilized samples that provided medium resolution 3D maps. Ab initio and rigid body modeling of scattering data revealed an elongated cross-shaped structure with a pair of loosely coupled core domain dimers at the ends, which are accessible for binding to DNA and partner proteins. The core domains in that open conformation closed around a specific DNA response element to form a compact complex whose structure was independently determined by electron microscopy. The structure of the DNA complex is consistent with that of the complex of four separate core domains and response element fragments solved by x-ray crystallography and contacts identified by NMR. Electron microscopy on the conformationally mobile, unbound p53 selected a minor compact conformation, which resembled the closed conformation, from the ensemble of predominantly open conformations. A multipronged structural approach could be generally useful for the structural characterization of the rapidly growing number of multidomain proteins with intrinsically disordered regions.

Biclustering of gene expression data by non-smooth non-negative matrix factorization

BackgroundThe extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states.ResultsIn this work we present a methodology able to cluster genes and conditions highly related in sub-portions of the data. Our approach is based on a new data mining technique, Non-smooth Non-Negative Matrix Factorization (n sNMF), able to identify localized patterns in large datasets. We assessed the potential of this methodology analyzing several synthetic datasets as well as two large and heterogeneous sets of gene expression profiles. In all cases the method was able to identify localized features related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The uncovered structures showed a clear biological meaning in terms of relationships among functional annotations of genes and the phenotypes or physiological states of the associated conditions.ConclusionThe proposed approach can be a useful tool to analyze large and heterogeneous gene expression datasets. The method is able to identify complex relationships among genes and conditions that are difficult to identify by standard clustering algorithms.

Consistent and elastic registration of histological sections using vector-spline regularization

Here we present a new image registration algorithm for the alignment of histological sections that combines the ideas of B-spline based elastic registration and consistent image registration, to allow simultaneous registration of images in two directions (direct and inverse). In principle, deformations based on B-splines are not invertible. The consistency term overcomes this limitation and allows registration of two images in a completely symmetric way. This extension of the elastic registration method simplifies the search for the optimum deformation and allows registering with no information about landmarks or deformation regularization. This approach can also be used as the first step to solve the problem of group-wise registration.

Integrated analysis of gene expression by association rules discovery

BackgroundMicroarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process.ResultsIn this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. We applied the proposed methodology to the analysis of gene expression datasets in which genes were annotated with metabolic pathways, transcriptional regulators and Gene Ontology categories. Automatically extracted associations revealed significant relationships among these gene attributes and expression patterns, where many of them are clearly supported by recently reported work.ConclusionThe integration of external biological information and gene expression data can provide insights about the biological processes associated to gene expression programs. In this paper we show that the proposed methodology is able to integrate multiple gene annotations and expression data in the same analytic framework and extract meaningful associations among heterogeneous sources of data. An implementation of the method is included in the Enge ne software package.

Crystal structure of a near-full-length archaeal MCM: Functional insights for an AAA+ hexameric helicase

The minichromosome maintenance protein (MCM) complex is an essential replicative helicase for DNA replication in Archaea and Eukaryotes. Whereas the eukaryotic complex consists of 6 homologous proteins (MCM2–7), the archaeon Sulfolobus solfataricus has only 1 MCM protein (ssoMCM), 6 subunits of which form a homohexamer. Here, we report a 4.35-Å crystal structure of the near-full-length ssoMCM. The structure shows an elongated fold, with 5 subdomains that are organized into 2 large N- and C-terminal domains. A near-full-length ssoMCM hexamer generated based on the 6-fold symmetry of the N-terminal Methanothermobacter thermautotrophicus (mtMCM) hexamer shows intersubunit distances suitable for bonding contacts, including the interface around the ATP pocket. Four unusual β-hairpins of each subunit are located inside the central channel or around the side channels in the hexamer. Additionally, the hexamer fits well into the double-hexamer EM map of mtMCM. Our mutational analysis of residues at the intersubunit interfaces and around the side channels demonstrates their critical roles for hexamerization and helicase function. These structural and biochemical results provide a basis for future study of the helicase mechanisms of the archaeal and eukaryotic MCM complexes in DNA replication.

Marker-free image registration of electron tomography tilt-series

BackgroundTilt series are commonly used in electron tomography as a means of collecting three-dimensional information from two-dimensional projections. A common problem encountered is the projection alignment prior to 3D reconstruction. Current alignment techniques usually employ gold particles or image derived markers to correctly align the images. When these markers are not present, correlation between adjacent views is used to align them. However, sequential pairwise correlation is prone to bias and the resulting alignment is not always optimal.ResultsIn this paper we introduce an algorithm to find regions of the tilt series which can be tracked within a subseries of the tilt series. These regions act as landmarks allowing the determination of the alignment parameters. We show our results with synthetic data as well as experimental cryo electron tomography.ConclusionOur algorithm is able to correctly align a single-tilt tomographic series without the help of fiducial markers thanks to the detection of thousands of small image patches that can be tracked over a short number of images in the series.

Large T-Antigen Double Hexamers Imaged at the Simian Virus 40 Origin of Replication

ABSTRACT The initial step of simian virus 40 (SV40) DNA replication is the binding of the large tumor antigen (T-Ag) to the SV40 core origin. In the presence of Mg2+ and ATP, T-Ag forms a double-hexamer complex covering the complete core origin. By using electron microscopy and negative staining, we visualized for the first time T-Ag double hexamers bound to the SV40 origin. Image processing of side views of these nucleoprotein complexes revealed bilobed particles 24 nm long and 8 to 12 nm wide, which indicates that the two T-Ag hexamers are oriented head to head. Taking into account all of the biochemical data known on the T-Ag–DNA interactions at the replication origin, we present a model in which the DNA passes through the inner channel of both hexamers. In addition, we describe a previously undetected structural domain of the T-Ag hexamer and thereby amend the previously published dimensions of the T-Ag hexamer. This domain we have determined to be the DNA-binding domain of T-Ag.