Thomas R. Cech

Bio: Thomas R. Cech is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: RNA & Ribozyme. The author has an hindex of 120, co-authored 473 publications receiving 54536 citations. Previous affiliations of Thomas R. Cech include Anschutz Medical Campus & Howard Hughes Medical Institute.

Telomerase catalytic subunit homologs from fission yeast and human

Abstract: Catalytic protein subunits of telomerase from the ciliate Euplotes aediculatus and the yeast Saccharomyces cerevisiae contain reverse transcriptase motifs. Here the homologous genes from the fission yeast Schizosaccharomyces pombe and human are identified. Disruption of the S. pombe gene resulted in telomere shortening and senescence, and expression of mRNA from the human gene correlated with telomerase activity in cell lines. Sequence comparisons placed the telomerase proteins in the reverse transcriptase family but revealed hallmarks that distinguish them from retroviral and retrotransposon relatives. Thus, the proposed telomerase catalytic subunits are phylogenetically conserved and represent a deep branch in the evolution of reverse transcriptases.

Reverse Transcriptase Motifs in the Catalytic Subunit of Telomerase

Abstract: Telomerase is a ribonucleoprotein enzyme essential for the replication of chromosome termini in most eukaryotes. Telomerase RNA components have been identified from many organisms, but no protein component has been demonstrated to catalyze telomeric DNA extension. Telomerase was purified from Euplotes aediculatus, a ciliated protozoan, and one of its proteins was partially sequenced by nanoelectrospray tandem mass spectrometry. Cloning and sequence analysis of the corresponding gene revealed that this 123-kilodalton protein (p123) contains reverse transcriptase motifs. A yeast (Saccharomyces cerevisiae) homolog was found and subsequently identified as EST2 (ever shorter telomeres), deletion of which had independently been shown to produce telomere defects. Introduction of single amino acid substitutions within the reverse transcriptase motifs of Est2 protein led to telomere shortening and senescence in yeast, indicating that these motifs are important for catalysis of telomere elongation in vivo. In vitro telomeric DNA extension occurred with extracts from wild-type yeast but not from est2 mutants or mutants deficient in telomerase RNA. Thus, the reverse transcriptase protein fold, previously known to be involved in retroviral replication and retrotransposition, is essential for normal chromosome telomere replication in diverse eukaryotes.

Crystal Structure of a Group I Ribozyme Domain: Principles of RNA Packing

Abstract: Group I self-splicing introns catalyze their own excision from precursor RNAs by way of a two-step transesterification reaction. The catalytic core of these ribozymes is formed by two structural domains. The 2.8-angstrom crystal structure of one of these, the P4-P6 domain of the Tetrahymena thermophila intron, is described. In the 160-nucleotide domain, a sharp bend allows stacked helices of the conserved core to pack alongside helices of an adjacent region. Two specific long-range interactions clamp the two halves of the domain together: a two-Mg2+-coordinated adenosine-rich corkscrew plugs into the minor groove of a helix, and a GAAA hairpin loop binds to a conserved 11-nucleotide internal loop. Metal- and ribose-mediated backbone contacts further stabilize the close side-by-side helical packing. The structure indicates the extent of RNA packing required for the function of large ribozymes, the spliceosome, and the ribosome.

Highly accurate protein structure prediction with AlphaFold

Abstract: Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1–4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’8—has been an important open research problem for more than 50 years9. Despite recent progress10–14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

In vitro selection of RNA molecules that bind specific ligands.

Abstract: Subpopulations of RNA molecules that bind specifically to a variety of organic dyes have been isolated from a population of random sequence RNA molecules. Roughly one in 10(10) random sequence RNA molecules folds in such a way as to create a specific binding site for small ligands.

Circular RNAs are a large class of animal RNAs with regulatory potency

Abstract: Circular RNAs (circRNAs) in animals are an enigmatic class of RNA with unknown function. To explore circRNAs systematically, we sequenced and computationally analysed human, mouse and nematode RNA. We detected thousands of well-expressed, stable circRNAs, often showing tissue/developmental-stage-specific expression. Sequence analysis indicated important regulatory functions for circRNAs. We found that a human circRNA, antisense to the cerebellar degeneration-related protein 1 transcript (CDR1as), is densely bound by microRNA (miRNA) effector complexes and harbours 63 conserved binding sites for the ancient miRNA miR-7. Further analyses indicated that CDR1as functions to bind miR-7 in neuronal tissues. Human CDR1as expression in zebrafish impaired midbrain development, similar to knocking down miR-7, suggesting that CDR1as is a miRNA antagonist with a miRNA-binding capacity ten times higher than any other known transcript. Together, our data provide evidence that circRNAs form a large class of post-transcriptional regulators. Numerous circRNAs form by head-to-tail splicing of exons, suggesting previously unrecognized regulatory potential of coding sequences.