Biomedical subjects

Uri Laserson

Publications and source records attributed to Uri Laserson.

4 recordsLinked to original sources

PubMed2025

PhIP-Seq uncovers marked heterogeneity in acute rheumatic fever autoantibodies.

Acute rheumatic fever (ARF) and associated rheumatic heart disease are serious sequelae after infection with group A Streptococcus (Strep A). Autoantibodies are thought to contribute to pathogenesis, with deeper exploration of the autoantibody repertoire needed to improve mechanistic understanding and identify new biomarkers. Phage immunoprecipitation sequencing (PhIP-Seq) with the HuScan library (>250,000 overlapping 90-mer peptides spanning the human proteome) was utilized to analyze autoreactivity in sera from children with ARF, uncomplicated Strep A pharyngitis, and matched healthy controls. A global proteome-wide increase in autoantigen reactivity was observed in ARF, as was marked heterogeneity between patients. Public epitopes, common between individuals with ARF were rare, and comprised less than 1% of all enriched peptides. Differential analysis identified both unknown and previously identified ARF autoantigens, including PPP1R12B, a myosin phosphatase complex regulatory subunit expressed in cardiac muscle, and members of the collagen protein family, respectively. Pathway analysis found antigens from the disease-relevant processes encompassing sarcomere and heart morphogenesis were targeted. In sum, PhIP-Seq has substantially expanded the spectrum of autoantigens in ARF, and reveals the rarity of public epitopes in the disease. It provides further support for the role of epitope spreading in pathogenesis and has identified PPP1R12B as an enriched autoantigen.

Humans↗

PubMed2005

Predicting candidate genomic sequences that correspond to synthetic functional RNA motifs.

Riboswitches and RNA interference are important emerging mechanisms found in many organisms to control gene expression. To enhance our understanding of such RNA roles, finding small regulatory motifs in genomes presents a challenge on a wide scale. Many simple functional RNA motifs have been found by in vitro selection experiments, which produce synthetic target-binding aptamers as well as catalytic RNAs, including the hammerhead ribozyme. Motivated by the prediction of Piganeau and Schroeder [(2003) Chem. Biol., 10, 103-104] that synthetic RNAs may have natural counterparts, we develop and apply an efficient computational protocol for identifying aptamer-like motifs in genomes. We define motifs from the sequence and structural information of synthetic aptamers, search for sequences in genomes that will produce motif matches, and then evaluate the structural stability and statistical significance of the potential hits. Our application to aptamers for streptomycin, chloramphenicol, neomycin B and ATP identifies 37 candidate sequences (in coding and non-coding regions) that fold to the target aptamer structures in bacterial and archaeal genomes. Further energetic screening reveals that several candidates exhibit energetic properties and sequence conservation patterns that are characteristic of functional motifs. Besides providing candidates for experimental testing, our computational protocol offers an avenue for expanding natural RNA's functional repertoire.

Algorithms↗

PubMed2004

RAG: RNA-As-Graphs web resource.

BACKGROUND: The proliferation of structural and functional studies of RNA has revealed an increasing range of RNA's structural repertoire. Toward the objective of systematic cataloguing of RNA's structural repertoire, we have recently described the basis of a graphical approach for organizing RNA secondary structures, including existing and hypothetical motifs. DESCRIPTION: We now present an RNA motif database based on graph theory, termed RAG for RNA-As-Graphs, to catalogue and rank all theoretically possible, including existing, candidate and hypothetical, RNA secondary motifs. The candidate motifs are predicted using a clustering algorithm that classifies RNA graphs into RNA-like and non-RNA groups. All RNA motifs are filed according to their graph vertex number (RNA length) and ranked by topological complexity. CONCLUSIONS: RAG's quantitative cataloguing allows facile retrieval of all classes of RNA secondary motifs, assists identification of structural and functional properties of user-supplied RNA sequences, and helps stimulate the search for novel RNAs based on predicted candidate motifs.

Computational Biology↗

PubMed2004

RAG: RNA-As-Graphs database--concepts, analysis, and features.

MOTIVATION: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire. RESULTS: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as 'tree graphs' and other RNAs, including pseudoknots, as general 'dual graphs'. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs. AVAILABILITY: The database is accessible on the web at http://monod.biomath.nyu.edu/rna

Algorithms↗