Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Identification by a monoclonal antibody of a glycolipid highly expressed by cells from the human myeloid lineage.

A monoclonal antibody (MAb) HL-C5, which bound selectively to cells of the myeloid lineage tested, was derived from a fusion between P3/NS2/1-AG8 myeloma cells and splenocytes from a mouse immunized with cells of the promyelocytic leukemia line HL-60. Among a panel of 29 human cell lines derived from either hematopoietic or solid tumors, MAb HL-C5 was found to react exclusively with cells from the five differentiated acute myeloid leukemia lines, HL-60, ML1, ML2, ML3, KG-1B and not with the less differentiated myeloid lines. Fluorescence-activated cell sorter analysis of normal bone marrow samples confirmed that the reactivity of MAb HL-C5 was limited to myeloid cells, from the promyelocytic stage of differentiation to the mature granulocytes. Indirect immunoperoxidase staining of cytocentrifuge preparations of normal bone marrow and peripheral blood leukocytes confirmed these results and showed that MAb HL-C5 stained neutrophils but not eosinophils or basophils. The antigen recognized by HL-C5 was recovered in the upper phase of chloroform-methanol-water lipid extracts prepared from HL-60 cells. By competitive binding experiments, it was found that MAb HL-C5 recognizes the same antigenic determinant as MAb WGHS 29-1, which has been reported to react with glycolipids containing the sugar sequence lacto-N-fucopentaose 111. Autoradiographs of thin layer chromatograms of HL-60 glycolipid extracts which were revealed by incubation with MAb HL-C5 or WGHS 29-1 followed by the addition of 125I-labelled rabbit anti-mouse immunoglobulin antibody confirmed that the two MAbs reacted with the same or structurally very similar glycolipids.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

Islands of euchromatin-like sequence and expressed polymorphic sequences within the short arm of human chromosome 21

The goals of the human genome project did not include sequencing of the heterochromatic regions. We describe here an initial sequence of 1.1 Mb of the short arm of human chromosome 21 (HSA21p), estimated to be 10% of 21p. This region contains extensive euchromatic-like sequence and includes on average one transcript every 100 kb. These transcripts show multiple inter- and intrachromosomal copies, and extensive copy number and sequence variability. The sequencing of the "heterochromatic" regions of the human genome is likely to reveal many additional functional elements and provide important evolutionary information.

A comparison of random sequence reads versus 16S rDNA sequences for estimating the biodiversity of a metagenomic library

The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10,010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.

Estimation of protein coding density in a corpus of DNA sequence data

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a ‘coding statistic’ is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C.elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.

From SNPs to pathways: integration of functional effect of sequence variations on models of cell signalling pathways

Background: Single nucleotide polymorphisms (SNPs) are the most frequent type of sequence variation between individuals, and represent a promising tool for finding genetic determinants of complex diseases and understanding the differences in drug response. In this regard, it is of particular interest to study the effect of non-synonymous SNPs in the context of biological networks such as cell signalling pathways. UniProt provides curated information about the functional and phenotypic effects of sequence variation, including SNPs, as well as on mutations of protein sequences. However, no strategy has been developed to integrate this information with biological networks, with the ultimate goal of studying the impact of the functional effect of SNPs in the structure and dynamics of biological networks. Results: First, we identified the different challenges posed by the integration of the phenotypic effect of sequence variants and mutations with biological networks. Second, we developed a strategy for the combination of data extracted from public resources, such as UniProt, NCBI dbSNP, Reactome and BioModels. We generated attribute files containing phenotypic and genotypic annotations to the nodes of biological networks, which can be imported into network visualization tools such as Cytoscape. These resources allow the mapping and visualization of mutations and natural variations of human proteins and their phenotypic effect on biological networks (e.g. signalling pathways, protein-protein interaction networks, dynamic models). Finally, an example on the use of the sequence variation data in the dynamics of a network model is presented. Conclusion: In this paper we present a general strategy for the integration of pathway and sequence variation data for visualization, analysis and modelling purposes, including the study of the functional impact of protein sequence variations on the dynamics of signalling pathways. This is of particular interest when the SNP or mutation is known to be associated to disease. We expect that this approach will help in the study of the functional impact of disease-associated SNPs on the behaviour of cell signalling pathways, which ultimately will lead to a better understanding of the mechanisms underlying complex diseases.

Prediction of enzyme function by combining sequence similarity and protein interactions

Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

OSIRISv1.2: a named entity recognition system for sequence variants of genes in biomedical literature

Background: Single Nucleotide Polymorphisms, among other type of sequence variants, constitute key elements in genetic epidemiology and pharmacogenomics. While sequence data about genetic variation is found at databases such as dbSNP, clues about the functional and phenotypic consequences of the variations are generally found in biomedical literature. The identification of the relevant documents and the extraction of the information from them are hampered by the large size of literature databases and the lack of widely accepted standard notation for biomedical entities. Thus, automatic systems for the identification of citations of allelic variants of genes in biomedical texts are required. Results: Our group has previously reported the development of OSIRIS, a system aimed at the retrieval of literature about allelic variants of genes http://ibi.imim.es/osirisform.html. Here we describe the development of a new version of OSIRIS (OSIRISv1.2, http://ibi.imim.es/OSIRISv1.2.html webcite) which incorporates a new entity recognition module and is built on top of a local mirror of the MEDLINE collection and HgenetInfoDB: a database that collects data on human gene sequence variations. The new entity recognition module is based on a pattern-based search algorithm for the identification of variation terms in the texts and their mapping to dbSNP identifiers. The performance of OSIRISv1.2 was evaluated on a manually annotated corpus, resulting in 99% precision, 82% recall, and an F-score of 0.89. As an example, the application of the system for collecting literature citations for the allelic variants of genes related to the diseases intracranial aneurysm and breast cancer is presented. Conclusion: OSIRISv1.2 can be used to link literature references to dbSNP database entries with high accuracy, and therefore is suitable for collecting current knowledge on gene sequence variations and supporting the functional annotation of variation databases. The application of OSIRISv1.2 in combination with controlled vocabularies like MeSH provides a way to identify associations of biomedical interest, such as those that relate SNPs with diseases.

Molecular phylogeny and evolution of Sorex shrews (Soricidae: insectivora) inferred from mitochondrial DNA sequence data.

Shrews of the genus Sorex are characterized by a Holarctic distribution, and relationships among extant taxa have never been fully resolved. Phylogenies have been proposed based on morphological, karyological, and biochemical comparisons, but these analyses often produced controversial and contradictory results. Phylogenetic analyses of partial mitochondrial cytochrome b gene sequences (1011 bp) were used to examine the relationships among 27 Sorex species. The molecular data suggest that Sorex comprises two major monophyletic lineages, one restricted mostly to the New World and one with a primarily Palearctic distribution. Furthermore, several sister-species relationships are revealed by the analysis. Based on the split between the Soricinae and Crocidurinae subfamilies, we used a 95% confidence interval for both the calibration of a molecular clock and the subsequent calculation of major diversification events within the genus Sorex. Our analysis does not support an unambiguous acceleration of the molecular clock in shrews, the estimated rate being similar to other estimates of mammalian mitochondrial clocks. In addition, the data presented here indicate that estimates from the fossil record greatly underestimate divergence dates among Sorex taxa.

Ultra-Thin PCC Overlays, January 2005

· Evaluate conventional methods of slab removal and asphalt surface preparation for subsequent overlays of portland cement concrete (PCC) in the “remove and replace” areas. · Evaluate existing asphaltic concrete surface under the “remove and patch” areas of rehabilitation areas and evaluate joint formation in the areas of patching. · Evaluate polypropylene fiber enhanced concrete at the three-inch depth to determine the cost/benefit of its inclusion. · Evaluate the performance of the rehabilitated ultra-thin whitetopping sections and the extended performance of the existing ultra-thin sections with and without patching. · Validate existing ultra-thin whitetopping design procedures of the Portland Cement Association (PCA) and American Concrete Pavement Association (ACPA) for application in Iowa.

Transposase and cointegrase: specialized transposition proteins of the bacterial insertion sequence IS21 and related elements.

The bacterial insertion sequence IS21 shares with many insertion sequences a two-step, reactive junction transposition pathway, for which a model is presented in this review: a reactive junction with abutted inverted repeats is first formed and subsequently integrated into the target DNA. The reactive junction occurs in IS21-IS21 tandems and IS21 minicircles. In addition, IS21 shows a unique specialization of transposition functions. By alternative translation initiation, the transposase gene codes for two products: the transposase, capable of promoting both steps of the reactive junction pathway, and the cointegrase, which only promotes the integration of reactive junctions but with higher efficiency. This review also includes a survey of the IS21 family and speculates on the possibility that other members present a similar transpositional specialization.

Ultra-Thin Portland Cement Concrete Overlay Extended Evaluation, January 2005

In this day of the mature highway systems, a new set of problems is facing the highway engineer. The existing infrastructure has aged to or past the design life of the original pavement design. In many cases, increased commercial traffic is creating the need for additional load carrying capacity, causing state highway engineers to consider new alternatives for rehabilitation of existing surfaces. Alternative surface materials, thicknesses, and methods of installation must be identified to meet the needs of individual pavements and budgets. With overlays being one of the most frequently used rehabilitation alternatives, it is important to learn more about the limitations and potential performance of thin bonded portland cement overlays and subsequent rehabilitation. The Iowa ultra-thin project demonstrated the application of thin portland cement concrete overlays as a rehabilitation technique. It combined the variables of base preparation, overlay thickness, slab size, and fiber enhancement into a series of test sections over a 7.2-mile length. This report identifies the performance of the overlays in terms of deflection reduction, reduced cracking, and improved bonding between the portland cement concrete (PCC) and asphalt cement concrete (ACC) base layers. The original research project was designed to evaluate the variables over a 5-year period of time. A second project provided the opportunity to test overlay rehabilitation techniques and continue measurement of the original overlay performance for 5 additional years. All performance indicators identified exceptional performance over the 10-year evaluation period for each of the variable combinations considered. The report summarizes the research methods, results, and identifies future research ideas to aid the pavement overlay designer in the successful implementation of ultra-thin portland cement concrete overlays as an lternative pavement rehabilitation technique.

Estimating the basic reproductive number from viral sequence data.

Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.