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Nord AJ, Wheeler TJ. Diviner uncovers hundreds of novel human (and other) exons though comparative analysis of proteins. bioRxiv 2024:2024.05.05.592595. [PMID: 38746152 PMCID: PMC11092782 DOI: 10.1101/2024.05.05.592595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background Eukaryotic genes are often composed of multiple exons that are stitched together by splicing out the intervening introns. These exons may be conditionally joined in different combinations to produce a collection of related, but distinct, mRNA transcripts. For protein-coding genes, these products of alternative splicing lead to production of related protein variants ( isoforms ) of a gene. Complete labeling of the protein-coding content of a eukaryotic genome requires discovery of mRNA encoding all isoforms, but it is impractical to enumerate all possible combinations of tissue, developmental stage, and environmental context; as a result, many true exons go unlabeled in genome annotations. Results One way to address the combinatoric challenge of finding all isoforms in a single organism A is to leverage sequencing efforts for other organisms - each time a new organism is sequenced, it may be under a new combination of conditions, so that a previously unobserved isoform may be sequenced. We present Diviner , a software tool that identifies previously undocumented exons in organisms by comparing isoforms across species. We demonstrate Diviner 's utility by locating hundreds of novel exons in the genomes of human, mouse, and rat, as well as in the ferret genome. Further, we provide analyses supporting the notion that most of the new exons reported by Diviner are likely to be part of a true (but unobserved) isoform of the containing species.
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2
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Geller-McGrath D, Konwar KM, Edgcomb VP, Pachiadaki M, Roddy JW, Wheeler TJ, McDermott JE. Predicting metabolic modules in incomplete bacterial genomes with MetaPathPredict. eLife 2024; 13:e85749. [PMID: 38696239 PMCID: PMC11065424 DOI: 10.7554/elife.85749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/16/2024] [Indexed: 05/04/2024] Open
Abstract
The reconstruction of complete microbial metabolic pathways using 'omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.
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Affiliation(s)
| | | | - Virginia P Edgcomb
- Marine Geology and Geophysics Department, Woods Hole Oceanographic InstitutionWoods HoleUnited States
| | - Maria Pachiadaki
- Biology Department, Woods Hole Oceanographic InstitutionWoods HoleUnited States
| | - Jack W Roddy
- R. Ken Coit College of Pharmacy, University of ArizonaTucsonUnited States
| | - Travis J Wheeler
- R. Ken Coit College of Pharmacy, University of ArizonaTucsonUnited States
| | - Jason E McDermott
- Computational Sciences Division, Pacific Northwest National LaboratoryRichlandUnited States
- Department of Molecular Microbiology and Immunology, Oregon Health & Science UniversityPortlandUnited States
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3
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Roddy JW, Rich DH, Wheeler TJ. nail: software for high-speed, high-sensitivity protein sequence annotation. bioRxiv 2024:2024.01.27.577580. [PMID: 38352323 PMCID: PMC10862755 DOI: 10.1101/2024.01.27.577580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
" Fast is fine, but accuracy is final. " -- Wyatt Earp. Background The extreme diversity of newly sequenced organisms and considerable scale of modern sequence databases lead to a tension between competing needs for sensitivity and speed in sequence annotation, with multiple tools displacing the venerable BLAST software suite on one axis or another. Alignment based on profile hidden Markov models (pHMMs) has demonstrated state of art sensitivity, while recent algorithmic advances have resulted in hyper-fast annotation tools with sensitivity close to that of BLAST. Results Here, we introduce a new tool that bridges the gap between advances in these two directions, reaching speeds comparable to fast annotation methods such as MMseqs2 while retaining most of the sensitivity offered by pHMMs. The tool, called nail, implements a heuristic approximation of the pHMM Forward/Backward (FB) algorithm by identifying a sparse subset of the cells in the FB dynamic programming matrix that contains most of the probability mass. The method produces an accurate approximation of pHMM scores and E-values with high speed and small memory requirements. On a protein benchmark, nail recovers the majority of recall difference between MMseqs2 and HMMER, with run time ~26x faster than HMMER3 (only ~2.4x slower than MMseqs2's sensitive variant). nail is released under the open BSD-3-clause license and is available for download at https://github.com/TravisWheelerLab/nail.
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Affiliation(s)
- Jack W Roddy
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA
| | - David H Rich
- Department of Computer Science, University of Montana, Missoula, Montana, USA
| | - Travis J Wheeler
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA
- Department of Computer Science, University of Montana, Missoula, Montana, USA
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Schimunek J, Seidl P, Elez K, Hempel T, Le T, Noé F, Olsson S, Raich L, Winter R, Gokcan H, Gusev F, Gutkin EM, Isayev O, Kurnikova MG, Narangoda CH, Zubatyuk R, Bosko IP, Furs KV, Karpenko AD, Kornoushenko YV, Shuldau M, Yushkevich A, Benabderrahmane MB, Bousquet-Melou P, Bureau R, Charton B, Cirou BC, Gil G, Allen WJ, Sirimulla S, Watowich S, Antonopoulos N, Epitropakis N, Krasoulis A, Itsikalis V, Theodorakis S, Kozlovskii I, Maliutin A, Medvedev A, Popov P, Zaretckii M, Eghbal-Zadeh H, Halmich C, Hochreiter S, Mayr A, Ruch P, Widrich M, Berenger F, Kumar A, Yamanishi Y, Zhang KYJ, Bengio E, Bengio Y, Jain MJ, Korablyov M, Liu CH, Marcou G, Glaab E, Barnsley K, Iyengar SM, Ondrechen MJ, Haupt VJ, Kaiser F, Schroeder M, Pugliese L, Albani S, Athanasiou C, Beccari A, Carloni P, D'Arrigo G, Gianquinto E, Goßen J, Hanke A, Joseph BP, Kokh DB, Kovachka S, Manelfi C, Mukherjee G, Muñiz-Chicharro A, Musiani F, Nunes-Alves A, Paiardi G, Rossetti G, Sadiq SK, Spyrakis F, Talarico C, Tsengenes A, Wade RC, Copeland C, Gaiser J, Olson DR, Roy A, Venkatraman V, Wheeler TJ, Arthanari H, Blaschitz K, Cespugli M, Durmaz V, Fackeldey K, Fischer PD, Gorgulla C, Gruber C, Gruber K, Hetmann M, Kinney JE, Padmanabha Das KM, Pandita S, Singh A, Steinkellner G, Tesseyre G, Wagner G, Wang ZF, Yust RJ, Druzhilovskiy DS, Filimonov DA, Pogodin PV, Poroikov V, Rudik AV, Stolbov LA, Veselovsky AV, De Rosa M, De Simone G, Gulotta MR, Lombino J, Mekni N, Perricone U, Casini A, Embree A, Gordon DB, Lei D, Pratt K, Voigt CA, Chen KY, Jacob Y, Krischuns T, Lafaye P, Zettor A, Rodríguez ML, White KM, Fearon D, Von Delft F, Walsh MA, Horvath D, Brooks CL, Falsafi B, Ford B, García-Sastre A, Yup Lee S, Naffakh N, Varnek A, Klambauer G, Hermans TM. A community effort in SARS-CoV-2 drug discovery. Mol Inform 2024; 43:e202300262. [PMID: 37833243 DOI: 10.1002/minf.202300262] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 10/13/2023] [Accepted: 10/13/2023] [Indexed: 10/15/2023]
Abstract
The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.
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5
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Krause GR, Shands W, Wheeler TJ. Sensitive and error-tolerant annotation of protein-coding DNA with BATH. bioRxiv 2024:2023.12.31.573773. [PMID: 38260252 PMCID: PMC10802276 DOI: 10.1101/2023.12.31.573773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
We present BATH, a tool for highly sensitive annotation of protein-coding DNA based on direct alignment of that DNA to a database of protein sequences or profile hidden Markov models (pHMMs). BATH is built on top of the HMMER3 code base, and simplifies the annotation workflow for pHMM-based annotation by providing a straightforward input interface and easy-to-interpret output. BATH also introduces novel frameshift-aware algorithms to detect frameshift-inducing nucleotide insertions and deletions (indels). BATH matches the accuracy of HMMER3 for annotation of sequences containing no errors, and produces superior accuracy to all tested tools for annotation of sequences containing nucleotide indels. These results suggest that BATH should be used when high annotation sensitivity is required, particularly when frameshift errors are expected to interrupt protein-coding regions, as is true with long read sequencing data and in the context of pseudogenes.
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Affiliation(s)
- Genevieve R Krause
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA
- Department of Computer Science, University of Montana, Missoula, Montana, USA
| | - Walt Shands
- Department of Computer Science, University of Montana, Missoula, Montana, USA
- UC Santa Cruz Genomics Institute, Santa Cruz, California, USA
| | - Travis J Wheeler
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, Arizona, USA
- Department of Computer Science, University of Montana, Missoula, Montana, USA
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6
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Copeland CJ, Roddy JW, Schmidt AK, Secor PR, Wheeler TJ. VIBES: A Workflow for Annotating and Visualizing Viral Sequences Integrated into Bacterial Genomes. bioRxiv 2023:2023.10.17.562434. [PMID: 37905003 PMCID: PMC10614876 DOI: 10.1101/2023.10.17.562434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Bacteriophages are viruses that infect bacteria. Many bacteriophages integrate their genomes into the bacterial chromosome and become prophages. Prophages may substantially burden or benefit host bacteria fitness, acting in some cases as parasites and in others as mutualists, and have been demonstrated to increase host virulence. The increasing ease of bacterial genome sequencing provides an opportunity to deeply explore prophage prevalence and insertion sites. Here we present VIBES, a workflow intended to automate prophage annotation in complete bacterial genome sequences. VIBES provides additional context to prophage annotations by annotating bacterial genes and viral proteins in user-provided bacterial and viral genomes. The VIBES pipeline is implemented as a Nextflow-driven workflow, providing a simple, unified interface for execution on local, cluster, and cloud computing environments. For each step of the pipeline, a container including all necessary software dependencies is provided. VIBES produces results in simple tab separated format and generates intuitive and interactive visualizations for data exploration. Despite VIBES' primary emphasis on prophage annotation, its generic alignment-based design allows it to be deployed as a general-purpose sequence similarity search manager. We demonstrate the utility of the VIBES prophage annotation workflow by searching for 178 Pf phage genomes across 1,072 Pseudomonas spp. genomes. VIBES software is available at https://github.com/TravisWheelerLab/VIBES.
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Affiliation(s)
- Conner J. Copeland
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Jack W. Roddy
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, AZ, USA
| | - Amelia K. Schmidt
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Patrick R. Secor
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Travis J. Wheeler
- R. Ken Coit College of Pharmacy, University of Arizona, Tucson, AZ, USA
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7
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Colligan T, Irish K, Emlen DJ, Wheeler TJ. DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals. PLoS One 2023; 18:e0288172. [PMID: 37494341 PMCID: PMC10370718 DOI: 10.1371/journal.pone.0288172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/21/2023] [Indexed: 07/28/2023] Open
Abstract
Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling elements in recordings of animal sounds, and demonstrate its utility on recordings of beetle courtships and whale songs. The software, DISCO, computes sensible confidence estimates and produces labels with high precision and accuracy. In addition to the core labeling software, it provides a simple tool for labeling training data, and a visual system for analysis of resulting labels. DISCO is open-source and easy to install, it works with standard file formats, and it presents a low barrier of entry to use.
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Affiliation(s)
- Thomas Colligan
- College of Pharmacy, University of Arizona, Tucson, AZ, United States of America
- Department of Computer Science, University of Montana, Missoula, MT, United States of America
| | - Kayla Irish
- Department of Computer Science, University of Montana, Missoula, MT, United States of America
- Department of Statistics, University of Washington, Seattle, WA, United States of America
| | - Douglas J Emlen
- Division of Biological Sciences, University of Montana, Missoula, MT, United States of America
| | - Travis J Wheeler
- College of Pharmacy, University of Arizona, Tucson, AZ, United States of America
- Department of Computer Science, University of Montana, Missoula, MT, United States of America
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8
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Colligan T, Irish K, Emlen DJ, Wheeler TJ. DISCO: A deep learning ensemble for uncertainty-aware segmentation of acoustic signals. bioRxiv 2023:2023.01.24.525459. [PMID: 36747788 PMCID: PMC9900853 DOI: 10.1101/2023.01.24.525459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Recordings of animal sounds enable a wide range of observational inquiries into animal communication, behavior, and diversity. Automated labeling of sound events in such recordings can improve both throughput and reproducibility of analysis. Here, we describe our software package for labeling sound elements in recordings of animal sounds and demonstrate its utility on recordings of beetle courtships and whale songs. The software, DISCO, computes sensible confidence estimates and produces labels with high precision and accuracy. In addition to the core labeling software, it provides a simple tool for labeling training data, and a visual system for analysis of resulting labels. DISCO is open-source and easy to install, it works with standard file formats, and it presents a low barrier of entry to use.
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Affiliation(s)
- Thomas Colligan
- Department of Pharmacy Practice & Science, University of Arizona, Tucson, AZ, USA,Department of Computer Science, University of Montana, Missoula, MT, USA
| | - Kayla Irish
- Department of Computer Science, University of Montana, Missoula, MT, USA,Department of Statistics, University of Washington, Seattle, WA, USA
| | - Douglas J. Emlen
- Division of Biological Sciences, University of Montana, Missoula, MT, USA
| | - Travis J. Wheeler
- Department of Pharmacy Practice & Science, University of Arizona, Tucson, AZ, USA,Department of Computer Science, University of Montana, Missoula, MT, USA
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9
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Storer JM, Walker JA, Baker JN, Hossain S, Roos C, Wheeler TJ, Batzer MA. Framework of the Alu Subfamily Evolution in the Platyrrhine Three-Family Clade of Cebidae, Callithrichidae, and Aotidae. Genes (Basel) 2023; 14:249. [PMID: 36833175 PMCID: PMC9956951 DOI: 10.3390/genes14020249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/10/2023] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
The history of Alu retroposons has been choreographed by the systematic accumulation of inherited diagnostic nucleotide substitutions to form discrete subfamilies, each having a distinct nucleotide consensus sequence. The oldest subfamily, AluJ, gave rise to AluS after the split between Strepsirrhini and what would become Catarrhini and Platyrrhini. The AluS lineage gave rise to AluY in catarrhines and to AluTa in platyrrhines. Platyrrhine Alu subfamilies Ta7, Ta10, and Ta15 were assigned names based on a standardized nomenclature. However, with the subsequent intensification of whole genome sequencing (WGS), large scale analyses to characterize Alu subfamilies using the program COSEG identified entire lineages of subfamilies simultaneously. The first platyrrhine genome with WGS, the common marmoset (Callithrix jacchus; [caljac3]), resulted in Alu subfamily names sf0 to sf94 in an arbitrary order. Although easily resolved by alignment of the consensus sequences, this naming convention can become increasingly confusing as more genomes are independently analyzed. In this study, we reported Alu subfamily characterization for the platyrrhine three-family clade of Cebidae, Callithrichidae, and Aotidae. We investigated one species/genome from each recognized family of Callithrichidae and Aotidae and of both subfamilies (Cebinae and Saimiriinae) of the family Cebidae. Furthermore, we constructed a comprehensive network of Alu subfamily evolution within the three-family clade of platyrrhines to provide a working framework for future research. Alu expansion in the three-family clade has been dominated by AluTa15 and its derivatives.
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Affiliation(s)
- Jessica M. Storer
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, LA 70803, USA; (J.M.S.); (J.A.W.)
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Jerilyn A. Walker
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, LA 70803, USA; (J.M.S.); (J.A.W.)
| | - Jasmine N. Baker
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA;
| | - Shifat Hossain
- Department of Pharmacy Practice & Science, University of Arizona, Tucson, AZ 85721, USA; (S.H.); (T.J.W.)
| | - Christian Roos
- Gene Bank of Primates and Primate Genetics Laboratory, German Primate Center, Leibniz Institute for Primate Research, 37077 Göttingen, Germany;
| | - Travis J. Wheeler
- Department of Pharmacy Practice & Science, University of Arizona, Tucson, AZ 85721, USA; (S.H.); (T.J.W.)
| | - Mark A. Batzer
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, LA 70803, USA; (J.M.S.); (J.A.W.)
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10
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Nord AJ, Wheeler TJ. Mirage2's high-quality spliced protein-to-genome mappings produce accurate multiple-sequence alignments of isoforms. PLoS One 2023; 18:e0285225. [PMID: 37155621 PMCID: PMC10166558 DOI: 10.1371/journal.pone.0285225] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 04/18/2023] [Indexed: 05/10/2023] Open
Abstract
The organization of homologous protein sequences into multiple sequence alignments (MSAs) is a cornerstone of modern analysis of proteins. Recent focus on the importance of alternatively-spliced isoforms in disease and cell biology has highlighted the need for MSA software that can appropriately account for isoforms and the exon-length insertions or deletions that isoforms may have relative to each other. We previously developed Mirage, a software package for generating MSAs for isoforms spanning multiple species. Here, we present Mirage2, which retains the fundamental algorithms of the original Mirage implementation while providing substantially improved translated mapping and improving several aspects of usability. We demonstrate that Mirage2 is highly effective at mapping proteins to their encoding exons, and that these protein-genome mappings lead to extremely accurate intron-aware alignments. Additionally, Mirage2 implements a number of engineering improvements that simplify installation and use.
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Affiliation(s)
- Alexander J Nord
- Division of Biological Sciences, University of Montana, Missoula, Montana, United States of America
| | - Travis J Wheeler
- Department of Pharmacology & Toxicology, University of Arizona, Tucson, Arizona, United States of America
- Department of Computer Science, University of Montana, Missoula, Montana, United States of America
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11
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Roddy JW, Lesica GT, Wheeler TJ. SODA: a TypeScript/JavaScript library for visualizing biological sequence annotation. NAR Genom Bioinform 2022; 4:lqac077. [PMID: 36212708 PMCID: PMC9535774 DOI: 10.1093/nargab/lqac077] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/27/2022] [Accepted: 09/27/2022] [Indexed: 12/02/2022] Open
Abstract
We present SODA, a lightweight and open-source visualization library for biological sequence annotations that enables straightforward development of flexible, dynamic and interactive web graphics. SODA is implemented in TypeScript and can be used as a library within TypeScript and JavaScript.
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Affiliation(s)
- Jack W Roddy
- Department of Computer Science, University of Montana, Missoula, MT 59812, USA
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ 85721, USA
| | - George T Lesica
- Department of Computer Science, University of Montana, Missoula, MT 59812, USA
| | - Travis J Wheeler
- Department of Computer Science, University of Montana, Missoula, MT 59812, USA
- Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ 85721, USA
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12
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Hubley R, Wheeler TJ, Smit AFA. Accuracy of multiple sequence alignment methods in the reconstruction of transposable element families. NAR Genom Bioinform 2022; 4:lqac040. [PMID: 35591887 PMCID: PMC9112768 DOI: 10.1093/nargab/lqac040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 03/29/2022] [Accepted: 04/29/2022] [Indexed: 02/06/2023] Open
Abstract
The construction of a high-quality multiple sequence alignment (MSA) from copies of a transposable element (TE) is a critical step in the characterization of a new TE family. Most studies of MSA accuracy have been conducted on protein or RNA sequence families, where structural features and strong signals of selection may assist with alignment. Less attention has been given to the quality of sequence alignments involving neutrally evolving DNA sequences such as those resulting from TE replication. Transposable element sequences are challenging to align due to their wide divergence ranges, fragmentation, and predominantly-neutral mutation patterns. To gain insight into the effects of these properties on MSA accuracy, we developed a simulator of TE sequence evolution, and used it to generate a benchmark with which we evaluated the MSA predictions produced by several popular aligners, along with Refiner, a method we developed in the context of our RepeatModeler software. We find that MAFFT and Refiner generally outperform other aligners for low to medium divergence simulated sequences, while Refiner is uniquely effective when tasked with aligning high-divergent and fragmented instances of a family.
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Affiliation(s)
- Robert Hubley
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Travis J Wheeler
- Department of Computer Science, University of Montana, Missoula, MT 59801, USA
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13
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Venkatraman V, Colligan TH, Lesica GT, Olson DR, Gaiser J, Copeland CJ, Wheeler TJ, Roy A. Drugsniffer: An Open Source Workflow for Virtually Screening Billions of Molecules for Binding Affinity to Protein Targets. Front Pharmacol 2022; 13:874746. [PMID: 35559261 PMCID: PMC9086895 DOI: 10.3389/fphar.2022.874746] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
The SARS-CoV2 pandemic has highlighted the importance of efficient and effective methods for identification of therapeutic drugs, and in particular has laid bare the need for methods that allow exploration of the full diversity of synthesizable small molecules. While classical high-throughput screening methods may consider up to millions of molecules, virtual screening methods hold the promise of enabling appraisal of billions of candidate molecules, thus expanding the search space while concurrently reducing costs and speeding discovery. Here, we describe a new screening pipeline, called drugsniffer, that is capable of rapidly exploring drug candidates from a library of billions of molecules, and is designed to support distributed computation on cluster and cloud resources. As an example of performance, our pipeline required ∼40,000 total compute hours to screen for potential drugs targeting three SARS-CoV2 proteins among a library of ∼3.7 billion candidate molecules.
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Affiliation(s)
- Vishwesh Venkatraman
- Department of Chemistry, Norwegian University of Science and Technology, Trondheim, Norway
| | - Thomas H. Colligan
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - George T. Lesica
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Daniel R. Olson
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Jeremiah Gaiser
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Conner J. Copeland
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Travis J. Wheeler
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Amitava Roy
- Department of Computer Science, University of Montana, Missoula, MT, United States
- Rocky Mountain Laboratories, Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, United States
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14
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Altemose N, Glennis A, Bzikadze AV, Sidhwani P, Langley SA, Caldas GV, Hoyt SJ, Uralsky L, Ryabov FD, Shew CJ, Sauria MEG, Borchers M, Gershman A, Mikheenko A, Shepelev VA, Dvorkina T, Kunyavskaya O, Vollger MR, Rhie A, McCartney AM, Asri M, Lorig-Roach R, Shafin K, Aganezov S, Olson D, de Lima LG, Potapova T, Hartley GA, Haukness M, Kerpedjiev P, Gusev F, Tigyi K, Brooks S, Young A, Nurk S, Koren S, Salama SR, Paten B, Rogaev EI, Streets A, Karpen GH, Dernburg AF, Sullivan BA, Straight AF, Wheeler TJ, Gerton JL, Eichler EE, Phillippy AM, Timp W, Dennis MY, O'Neill RJ, Zook JM, Schatz MC, Pevzner PA, Diekhans M, Langley CH, Alexandrov IA, Miga KH. Complete genomic and epigenetic maps of human centromeres. Science 2022; 376:eabl4178. [PMID: 35357911 PMCID: PMC9233505 DOI: 10.1126/science.abl4178] [Citation(s) in RCA: 157] [Impact Index Per Article: 78.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Existing human genome assemblies have almost entirely excluded repetitive sequences within and near centromeres, limiting our understanding of their organization, evolution, and functions, which include facilitating proper chromosome segregation. Now, a complete, telomere-to-telomere human genome assembly (T2T-CHM13) has enabled us to comprehensively characterize pericentromeric and centromeric repeats, which constitute 6.2% of the genome (189.9 megabases). Detailed maps of these regions revealed multimegabase structural rearrangements, including in active centromeric repeat arrays. Analysis of centromere-associated sequences uncovered a strong relationship between the position of the centromere and the evolution of the surrounding DNA through layered repeat expansions. Furthermore, comparisons of chromosome X centromeres across a diverse panel of individuals illuminated high degrees of structural, epigenetic, and sequence variation in these complex and rapidly evolving regions.
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Affiliation(s)
- Nicolas Altemose
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - A. Glennis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California San Diego, La Jolla, CA, USA
| | - Pragya Sidhwani
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Sasha A. Langley
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Lev Uralsky
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
| | | | - Colin J. Shew
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | | | | | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | | | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Olga Kunyavskaya
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mobin Asri
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Ryan Lorig-Roach
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Daniel Olson
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | | | - Tamara Potapova
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | | | - Fedor Gusev
- Vavilov Institute of General Genetics, Moscow, Russia
| | - Kristof Tigyi
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Shelise Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Alice Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sofie R. Salama
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology, Sochi, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Gary H. Karpen
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- BioEngineering and BioMedical Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Abby F. Dernburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, USA
| | | | - Travis J. Wheeler
- Department of Computer Science, University of Montana, Missoula, MT. USA
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research, Kansas City, MO, USA
- University of Kansas Medical School, Department of Biochemistry and Molecular Biology and Cancer Center, University of Kansas, Kansas City, KS, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, and Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | - Rachel J. O'Neill
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California at San Diego, San Diego, CA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Charles H. Langley
- Department of Evolution and Ecology, University of California Davis, Davis, CA, USA
| | - Ivan A. Alexandrov
- Vavilov Institute of General Genetics, Moscow, Russia
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences, Moscow, Russia
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
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15
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Hoyt SJ, Storer JM, Hartley GA, Grady PGS, Gershman A, de Lima LG, Limouse C, Halabian R, Wojenski L, Rodriguez M, Altemose N, Rhie A, Core LJ, Gerton JL, Makalowski W, Olson D, Rosen J, Smit AFA, Straight AF, Vollger MR, Wheeler TJ, Schatz MC, Eichler EE, Phillippy AM, Timp W, Miga KH, O’Neill RJ. From telomere to telomere: The transcriptional and epigenetic state of human repeat elements. Science 2022; 376:eabk3112. [PMID: 35357925 PMCID: PMC9301658 DOI: 10.1126/science.abk3112] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Mobile elements and repetitive genomic regions are sources of lineage-specific genomic innovation and uniquely fingerprint individual genomes. Comprehensive analyses of such repeat elements, including those found in more complex regions of the genome, require a complete, linear genome assembly. We present a de novo repeat discovery and annotation of the T2T-CHM13 human reference genome. We identified previously unknown satellite arrays, expanded the catalog of variants and families for repeats and mobile elements, characterized classes of complex composite repeats, and located retroelement transduction events. We detected nascent transcription and delineated CpG methylation profiles to define the structure of transcriptionally active retroelements in humans, including those in centromeres. These data expand our insight into the diversity, distribution, and evolution of repetitive regions that have shaped the human genome.
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Affiliation(s)
- Savannah J. Hoyt
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | | | - Gabrielle A. Hartley
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Patrick G. S. Grady
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
| | | | - Charles Limouse
- Department of Biochemistry, Stanford University, Stanford, CA, USA
| | - Reza Halabian
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, Münster, Germany
| | - Luke Wojenski
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
| | - Matias Rodriguez
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, Münster, Germany
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Leighton J. Core
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
| | | | - Wojciech Makalowski
- Institute of Bioinformatics, Faculty of Medicine, University of Münster, Münster, Germany
| | - Daniel Olson
- Department of Computer Science, University of Montana, Missoula, MT, USA
| | - Jeb Rosen
- Institute for Systems Biology, Seattle, WA, USA
| | | | | | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Travis J. Wheeler
- Department of Computer Science, University of Montana, Missoula, MT, USA
| | - Michael C. Schatz
- Department of Computer Science and Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Rachel J. O’Neill
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA
- Department of Genetics and Genome Sciences, UConn Health, Farmington, CT, USA
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16
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Abstract
BACKGROUND Pattern matching is a key step in a variety of biological sequence analysis pipelines. The FM-index is a compressed data structure for pattern matching, with search run time that is independent of the length of the database text. Implementation of the FM-index is reasonably complicated, so that increased adoption will be aided by the availability of a fast and flexible FM-index library. RESULTS We present AvxWindowedFMindex (AWFM-index), a lightweight, open-source, thread-parallel FM-index library written in C that is optimized for indexing nucleotide and amino acid sequences. AWFM-index introduces a new approach to storing FM-index data in a strided bit-vector format that enables extremely efficient computation of the FM-index occurrence function via AVX2 bitwise instructions, and combines this with optional on-disk storage of the index's suffix array and a cache-efficient lookup table for partial k-mer searches. The AWFM-index performs exact match count and locate queries faster than SeqAn3's FM-index implementation across a range of comparable memory footprints. When optimized for speed, AWFM-index is [Formula: see text]2-4x faster than SeqAn3 for nucleotide search, and [Formula: see text]2-6x faster for amino acid search; it is also [Formula: see text]4x faster with similar memory footprint when storing the suffix array in on-disk SSD storage. CONCLUSIONS AWFM-index is easy to incorporate into bioinformatics software, offers run-time performance parameterization, and provides clients with FM-index functionality at both a high-level (count or locate all instances of a query string) and low-level (step-wise control of the FM-index backward-search process). The open-source library is available for download at https://github.com/TravisWheelerLab/AvxWindowFmIndex.
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Affiliation(s)
- Tim Anderson
- Department of Computer Science, University of Montana, Missoula, MT, USA
| | - Travis J Wheeler
- Department of Computer Science, University of Montana, Missoula, MT, USA.
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17
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Elliott TA, Heitkam T, Hubley R, Quesneville H, Suh A, Wheeler TJ. TE Hub: A community-oriented space for sharing and connecting tools, data, resources, and methods for transposable element annotation. Mob DNA 2021; 12:16. [PMID: 34154643 PMCID: PMC8215825 DOI: 10.1186/s13100-021-00244-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 06/03/2021] [Indexed: 12/16/2022] Open
Abstract
Transposable elements (TEs) play powerful and varied evolutionary and functional roles, and are widespread in most eukaryotic genomes. Research into their unique biology has driven the creation of a large collection of databases, software, classification systems, and annotation guidelines. The diversity of available TE-related methods and resources raises compatibility concerns and can be overwhelming to researchers and communicators seeking straightforward guidance or materials. To address these challenges, we have initiated a new resource, TE Hub, that provides a space where members of the TE community can collaborate to document and create resources and methods. The space consists of (1) a website organized with an open wiki framework, https://tehub.org , (2) a conversation framework via a Twitter account and a Slack channel, and (3) bi-monthly Hub Update video chats on the platform's development. In addition to serving as a centralized repository and communication platform, TE Hub lays the foundation for improved integration, standardization, and effectiveness of diverse tools and protocols. We invite the TE community, both novices and experts in TE identification and analysis, to join us in expanding our community-oriented resource.
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Affiliation(s)
| | - Tyler A. Elliott
- grid.34429.380000 0004 1936 8198Centre for Biodiversity Genomics, University of Guelph, Guelph, ON Canada
| | - Tony Heitkam
- grid.4488.00000 0001 2111 7257Faculty of Biology, Technische Universität Dresden, 01069 Dresden, Germany
| | - Robert Hubley
- grid.64212.330000 0004 0463 2320Institute for Systems Biology, Seattle, WA USA
| | - Hadi Quesneville
- grid.507621.7Université Paris-Saclay, INRAE, URGI, 78026 Versailles, France
| | - Alexander Suh
- grid.8273.e0000 0001 1092 7967School of Biological Sciences, University of East Anglia, Norwich, UK ,grid.8993.b0000 0004 1936 9457Department of Organismal Biology, Uppsala University, Uppsala, Sweden
| | - Travis J. Wheeler
- grid.253613.00000 0001 2192 5772Department of Computer Science, University of Montana, Missoula, MT USA
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18
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Abstract
Background Transposable element (TE) sequences are classified into families based on the reconstructed history of replication, and into subfamilies based on more fine-grained features that are often intended to capture family history. We evaluate the reliability of annotation with common subfamilies by assessing the extent to which subfamily annotation is reproducible in replicate copies created by segmental duplications in the human genome, and in homologous copies shared by human and chimpanzee. Results We find that standard methods annotate over 10% of replicates as belonging to different subfamilies, despite the fact that they are expected to be annotated as belonging to the same subfamily. Point mutations and homologous recombination appear to be responsible for some of this discordant annotation (particularly in the young Alu family), but are unlikely to fully explain the annotation unreliability. Conclusions The surprisingly high level of disagreement in subfamily annotation of homologous sequences highlights a need for further research into definition of TE subfamilies, methods for representing subfamily annotation confidence of TE instances, and approaches to better utilizing such nuanced annotation data in downstream analysis.
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Affiliation(s)
- Kaitlin M Carey
- Department of Computer Science, University of Montana, 32 Campus Drive, Missoula, MT, USA
| | - Gilia Patterson
- Department of Computer Science, University of Montana, 32 Campus Drive, Missoula, MT, USA.,Institute of Ecology and Evolution, University of Oregon, 272 Onyx Bridge, Eugene, OR, USA
| | - Travis J Wheeler
- Department of Computer Science, University of Montana, 32 Campus Drive, Missoula, MT, USA.
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19
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Storer J, Hubley R, Rosen J, Wheeler TJ, Smit AF. The Dfam community resource of transposable element families, sequence models, and genome annotations. Mob DNA 2021; 12:2. [PMID: 33436076 PMCID: PMC7805219 DOI: 10.1186/s13100-020-00230-y] [Citation(s) in RCA: 193] [Impact Index Per Article: 64.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/28/2020] [Indexed: 02/02/2023] Open
Abstract
Dfam is an open access database of repetitive DNA families, sequence models, and genome annotations. The 3.0-3.3 releases of Dfam ( https://dfam.org ) represent an evolution from a proof-of-principle collection of transposable element families in model organisms into a community resource for a broad range of species, and for both curated and uncurated datasets. In addition, releases since Dfam 3.0 provide auxiliary consensus sequence models, transposable element protein alignments, and a formalized classification system to support the growing diversity of organisms represented in the resource. The latest release includes 266,740 new de novo generated transposable element families from 336 species contributed by the EBI. This expansion demonstrates the utility of many of Dfam's new features and provides insight into the long term challenges ahead for improving de novo generated transposable element datasets.
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Affiliation(s)
| | - Robert Hubley
- Institute for Systems Biology, Seattle, WA, 98109, USA.
| | - Jeb Rosen
- Institute for Systems Biology, Seattle, WA, 98109, USA
| | | | - Arian F Smit
- Institute for Systems Biology, Seattle, WA, 98109, USA.
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20
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Secor PR, Burgener EB, Kinnersley M, Jennings LK, Roman-Cruz V, Popescu M, Van Belleghem JD, Haddock N, Copeland C, Michaels LA, de Vries CR, Chen Q, Pourtois J, Wheeler TJ, Milla CE, Bollyky PL. Pf Bacteriophage and Their Impact on Pseudomonas Virulence, Mammalian Immunity, and Chronic Infections. Front Immunol 2020; 11:244. [PMID: 32153575 PMCID: PMC7047154 DOI: 10.3389/fimmu.2020.00244] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 01/30/2020] [Indexed: 12/11/2022] Open
Abstract
Pf bacteriophage are temperate phages that infect the bacterium Pseudomonas aeruginosa, a major cause of chronic lung infections in cystic fibrosis (CF) and other settings. Pf and other temperate phages have evolved complex, mutualistic relationships with their bacterial hosts that impact both bacterial phenotypes and chronic infection. We and others have reported that Pf phages are a virulence factor that promote the pathogenesis of P. aeruginosa infections in animal models and are associated with worse skin and lung infections in humans. Here we review the biology of Pf phage and what is known about its contributions to pathogenesis and clinical disease. First, we review the structure, genetics, and epidemiology of Pf phage. Next, we address the diverse and surprising ways that Pf phages contribute to P. aeruginosa phenotypes including effects on biofilm formation, antibiotic resistance, and motility. Then, we cover data indicating that Pf phages suppress mammalian immunity at sites of bacterial infection. Finally, we discuss recent literature implicating Pf in chronic P. aeruginosa infections in CF and other settings. Together, these reports suggest that Pf bacteriophage have direct effects on P. aeruginosa infections and that temperate phages are an exciting frontier in microbiology, immunology, and human health.
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Affiliation(s)
- Patrick R. Secor
- Division of Biological Sciences, University of Montana, Missoula, MT, United States
- Center for Translational Medicine, University of Montana, Missoula, MT, United States
- Center for Biomolecular Structure and Dynamics, University of Montana, Missoula, MT, United States
| | - Elizabeth B. Burgener
- Department of Pediatrics, Center for Excellence in Pulmonary Biology, Stanford University, Stanford, CA, United States
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - M. Kinnersley
- Division of Biological Sciences, University of Montana, Missoula, MT, United States
| | - Laura K. Jennings
- Division of Biological Sciences, University of Montana, Missoula, MT, United States
- Center for Translational Medicine, University of Montana, Missoula, MT, United States
| | - Valery Roman-Cruz
- Division of Biological Sciences, University of Montana, Missoula, MT, United States
- Center for Translational Medicine, University of Montana, Missoula, MT, United States
| | - Medeea Popescu
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Jonas D. Van Belleghem
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Naomi Haddock
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Conner Copeland
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Lia A. Michaels
- Division of Biological Sciences, University of Montana, Missoula, MT, United States
| | - Christiaan R. de Vries
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Qingquan Chen
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Julie Pourtois
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
| | - Travis J. Wheeler
- Center for Biomolecular Structure and Dynamics, University of Montana, Missoula, MT, United States
- Department of Computer Science, University of Montana, Missoula, MT, United States
| | - Carlos E. Milla
- Department of Pediatrics, Center for Excellence in Pulmonary Biology, Stanford University, Stanford, CA, United States
| | - Paul L. Bollyky
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, United States
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21
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Hubley R, Finn RD, Clements J, Eddy SR, Jones TA, Bao W, Smit AFA, Wheeler TJ. The Dfam database of repetitive DNA families. Nucleic Acids Res 2015; 44:D81-9. [PMID: 26612867 PMCID: PMC4702899 DOI: 10.1093/nar/gkv1272] [Citation(s) in RCA: 391] [Impact Index Per Article: 43.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Accepted: 11/03/2015] [Indexed: 11/20/2022] Open
Abstract
Repetitive DNA, especially that due to transposable elements (TEs), makes up a large fraction of many genomes. Dfam is an open access database of families of repetitive DNA elements, in which each family is represented by a multiple sequence alignment and a profile hidden Markov model (HMM). The initial release of Dfam, featured in the 2013 NAR Database Issue, contained 1143 families of repetitive elements found in humans, and was used to produce more than 100 Mb of additional annotation of TE-derived regions in the human genome, with improved speed. Here, we describe recent advances, most notably expansion to 4150 total families including a comprehensive set of known repeat families from four new organisms (mouse, zebrafish, fly and nematode). We describe improvements to coverage, and to our methods for identifying and reducing false annotation. We also describe updates to the website interface. The Dfam website has moved to http://dfam.org. Seed alignments, profile HMMs, hit lists and other underlying data are available for download.
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Affiliation(s)
- Robert Hubley
- Institute for Systems Biology, Seattle, WA 98109, USA
| | - Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1RQ, UK
| | - Jody Clements
- HHMI Janelia Research Campus, Ashburn, VA 20147, USA
| | - Sean R Eddy
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Thomas A Jones
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Weidong Bao
- Genetic Information Research Institute, Los Altos, CA 94022, USA
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22
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Hoen DR, Hickey G, Bourque G, Casacuberta J, Cordaux R, Feschotte C, Fiston-Lavier AS, Hua-Van A, Hubley R, Kapusta A, Lerat E, Maumus F, Pollock DD, Quesneville H, Smit A, Wheeler TJ, Bureau TE, Blanchette M. A call for benchmarking transposable element annotation methods. Mob DNA 2015; 6:13. [PMID: 26244060 PMCID: PMC4524446 DOI: 10.1186/s13100-015-0044-6] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2015] [Accepted: 07/22/2015] [Indexed: 12/31/2022] Open
Abstract
DNA derived from transposable elements (TEs) constitutes large parts of the genomes of complex eukaryotes, with major impacts not only on genomic research but also on how organisms evolve and function. Although a variety of methods and tools have been developed to detect and annotate TEs, there are as yet no standard benchmarks-that is, no standard way to measure or compare their accuracy. This lack of accuracy assessment calls into question conclusions from a wide range of research that depends explicitly or implicitly on TE annotation. In the absence of standard benchmarks, toolmakers are impeded in improving their tools, annotators cannot properly assess which tools might best suit their needs, and downstream researchers cannot judge how accuracy limitations might impact their studies. We therefore propose that the TE research community create and adopt standard TE annotation benchmarks, and we call for other researchers to join the authors in making this long-overdue effort a success.
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Affiliation(s)
- Douglas R Hoen
- School of Computer Science, McGill University, McConnell Engineering Bldg., Rm. 318, 3480 Rue University, Montréal, Québec H3A 0E9 Canada ; Department of Biology, McGill University, Stewart Biology Bldg., 1205 Ave. du Docteur-Penfield, Montréal, Québec H3A 1B1 Canada
| | - Glenn Hickey
- School of Computer Science, McGill University, McConnell Engineering Bldg., Rm. 318, 3480 Rue University, Montréal, Québec H3A 0E9 Canada ; McGill Centre for Bioinformatics, McGill University, Montréal, Québec Canada
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, Québec Canada ; McGill University and Génome Québec Innovation Center, Montréal, Québec Canada
| | - Josep Casacuberta
- Centre for Research in Agricultural Genomics CSIC-IRTA-UAB-UB, 08193 Barcelona, Spain
| | - Richard Cordaux
- Université de Poitiers, UMR CNRS 7267 Ecologie et Biologie des Interactions, Equipe Ecologie Evolution Symbiose, 5 Rue Albert Turpin, 86073 Poitiers Cedex 9, France
| | - Cédric Feschotte
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112 USA
| | - Anna-Sophie Fiston-Lavier
- Institut des Sciences de l'Evolution de Montpellier (ISE-M), Equipe Evolution, Vecteurs, Adaptation et Symbiose, UMR5554 CNRS-Université Montpellier, Montpellier, 34090 cedex 05 France
| | - Aurélie Hua-Van
- Laboratoire Evolution, Génomes, Comportement Ecologie, CNRS-Université Paris-Sud (UMR 9191)-IRD (UMR 247)-Université Paris-Saclay, F-91198 Gif-sur-Yvette, France
| | - Robert Hubley
- Institute for Systems Biology, 401 Terry Ave. N, Seattle, WA 98109 USA
| | - Aurélie Kapusta
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112 USA
| | - Emmanuelle Lerat
- Laboratoire Biometrie et Biologie Evolutive, Universite Claude Bernard-Lyon 1, UMR-CNRS 5558-Bat. Mendel, 43 bd du 11 novembre 1918, 69622 Villeurbanne cedex, France
| | - Florian Maumus
- INRA, UR1164 URGI-Research Unit in Genomics-Info, INRA de Versailles-Grignon, Route de Saint-Cyr, Versailles, 78026 France
| | - David D Pollock
- University of Colorado School of Medicine, Aurora, CO 80045 USA
| | - Hadi Quesneville
- INRA, UR1164 URGI-Research Unit in Genomics-Info, INRA de Versailles-Grignon, Route de Saint-Cyr, Versailles, 78026 France
| | - Arian Smit
- Institute for Systems Biology, 401 Terry Ave. N, Seattle, WA 98109 USA
| | - Travis J Wheeler
- Department of Computer Science, University of Montana, Missoula, MT 59812 USA
| | - Thomas E Bureau
- Department of Biology, McGill University, Stewart Biology Bldg., 1205 Ave. du Docteur-Penfield, Montréal, Québec H3A 1B1 Canada
| | - Mathieu Blanchette
- School of Computer Science, McGill University, McConnell Engineering Bldg., Rm. 318, 3480 Rue University, Montréal, Québec H3A 0E9 Canada ; McGill Centre for Bioinformatics, McGill University, Montréal, Québec Canada
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Finn RD, Clements J, Arndt W, Miller BL, Wheeler TJ, Schreiber F, Bateman A, Eddy SR. HMMER web server: 2015 update. Nucleic Acids Res 2015; 43:W30-8. [PMID: 25943547 PMCID: PMC4489315 DOI: 10.1093/nar/gkv397] [Citation(s) in RCA: 611] [Impact Index Per Article: 67.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 04/15/2015] [Indexed: 12/27/2022] Open
Abstract
The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.
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Affiliation(s)
- Robert D Finn
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Jody Clements
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - William Arndt
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Benjamin L Miller
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
| | - Travis J Wheeler
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA Department of Computer Science, University of Montana, Social Sciences Building Room 412, Missoula MT 59812, USA
| | - Fabian Schreiber
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Alex Bateman
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Sean R Eddy
- HHMI Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA
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Abstract
SUMMARY Sequence database searches are an essential part of molecular biology, providing information about the function and evolutionary history of proteins, RNA molecules and DNA sequence elements. We present a tool for DNA/DNA sequence comparison that is built on the HMMER framework, which applies probabilistic inference methods based on hidden Markov models to the problem of homology search. This tool, called nhmmer, enables improved detection of remote DNA homologs, and has been used in combination with Dfam and RepeatMasker to improve annotation of transposable elements in the human genome. AVAILABILITY nhmmer is a part of the new HMMER3.1 release. Source code and documentation can be downloaded from http://hmmer.org. HMMER3.1 is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X.
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Abstract
Summary: Sequence database searches are an essential part of molecular biology, providing information about the function and evolutionary history of proteins, RNA molecules and DNA sequence elements. We present a tool for DNA/DNA sequence comparison that is built on the HMMER framework, which applies probabilistic inference methods based on hidden Markov models to the problem of homology search. This tool, called nhmmer, enables improved detection of remote DNA homologs, and has been used in combination with Dfam and RepeatMasker to improve annotation of transposable elements in the human genome. Availability: nhmmer is a part of the new HMMER3.1 release. Source code and documentation can be downloaded from http://hmmer.org. HMMER3.1 is freely licensed under the GNU GPLv3 and should be portable to any POSIX-compliant operating system, including Linux and Mac OS/X. Contact:wheelert@janelia.hhmi.org
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Wheeler TJ, Clements J, Eddy SR, Hubley R, Jones TA, Jurka J, Smit AFA, Finn RD. Dfam: a database of repetitive DNA based on profile hidden Markov models. Nucleic Acids Res 2012. [PMID: 23203985 PMCID: PMC3531169 DOI: 10.1093/nar/gks1265] [Citation(s) in RCA: 178] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
We present a database of repetitive DNA elements, called Dfam (http://dfam.janelia.org). Many genomes contain a large fraction of repetitive DNA, much of which is made up of remnants of transposable elements (TEs). Accurate annotation of TEs enables research into their biology and can shed light on the evolutionary processes that shape genomes. Identification and masking of TEs can also greatly simplify many downstream genome annotation and sequence analysis tasks. The commonly used TE annotation tools RepeatMasker and Censor depend on sequence homology search tools such as cross_match and BLAST variants, as well as Repbase, a collection of known TE families each represented by a single consensus sequence. Dfam contains entries corresponding to all Repbase TE entries for which instances have been found in the human genome. Each Dfam entry is represented by a profile hidden Markov model, built from alignments generated using RepeatMasker and Repbase. When used in conjunction with the hidden Markov model search tool nhmmer, Dfam produces a 2.9% increase in coverage over consensus sequence search methods on a large human benchmark, while maintaining low false discovery rates, and coverage of the full human genome is 54.5%. The website provides a collection of tools and data views to support improved TE curation and annotation efforts. Dfam is also available for download in flat file format or in the form of MySQL table dumps.
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Tanifuji G, Onodera NT, Wheeler TJ, Dlutek M, Donaher N, Archibald JM. Complete nucleomorph genome sequence of the nonphotosynthetic alga Cryptomonas paramecium reveals a core nucleomorph gene set. Genome Biol Evol 2010; 3:44-54. [PMID: 21147880 PMCID: PMC3017389 DOI: 10.1093/gbe/evq082] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Nucleomorphs are the remnant nuclei of algal endosymbionts that were engulfed by nonphotosynthetic host eukaryotes. These peculiar organelles are found in cryptomonad and chlorarachniophyte algae, where they evolved from red and green algal endosymbionts, respectively. Despite their independent origins, cryptomonad and chlorarachniophyte nucleomorph genomes are similar in size and structure: they are both <1 million base pairs in size (the smallest nuclear genomes known), comprised three chromosomes, and possess subtelomeric ribosomal DNA operons. Here, we report the complete sequence of one of the smallest cryptomonad nucleomorph genomes known, that of the secondarily nonphotosynthetic cryptomonad Cryptomonas paramecium. The genome is 486 kbp in size and contains 518 predicted genes, 466 of which are protein coding. Although C. paramecium lacks photosynthetic ability, its nucleomorph genome still encodes 18 plastid-associated proteins. More than 90% of the “conserved” protein genes in C. paramecium (i.e., those with clear homologs in other eukaryotes) are also present in the nucleomorph genomes of the cryptomonads Guillardia theta and Hemiselmis andersenii. In contrast, 143 of 466 predicted C. paramecium proteins (30.7%) showed no obvious similarity to proteins encoded in any other genome, including G. theta and H. andersenii. Significantly, however, many of these “nucleomorph ORFans” are conserved in position and size between the three genomes, suggesting that they are in fact homologous to one another. Finally, our analyses reveal an unexpected degree of overlap in the genes present in the independently evolved chlorarachniophyte and cryptomonad nucleomorph genomes: ∼80% of a set of 120 conserved nucleomorph genes in the chlorarachniophyte Bigelowiella natans were also present in all three cryptomonad nucleomorph genomes. This result suggests that similar reductive processes have taken place in unrelated lineages of nucleomorph-containing algae.
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Affiliation(s)
- Goro Tanifuji
- Canadian Institute for Advanced Research, Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia, Canada
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Turner Ellis SA, Miles TR, Wheeler TJ. Extraneous bodily movements and irrelevant vocalizations by dyslexic and non-dyslexic boys during calculation tasks. Dyslexia 2009; 15:156-163. [PMID: 18756461 DOI: 10.1002/dys.363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Thirty dyslexic boys, aged between 9 and 15 years, and 30 age-matched controls were tested on a series of sums involving division, subtraction and addition. During the testing a record was kept of any bodily movements or verbal utterances (vocalizations) irrelevant to the task in hand. It was found that the dyslexics produced many more extraneous bodily movements and many more irrelevant vocalizations than did the controls. Possible reasons for these findings are tentatively suggested.
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Abstract
MOTIVATION Multiple sequence alignment is a fundamental task in bioinformatics. Current tools typically form an initial alignment by merging subalignments, and then polish this alignment by repeated splitting and merging of subalignments to obtain an improved final alignment. In general this form-and-polish strategy consists of several stages, and a profusion of methods have been tried at every stage. We carefully investigate: (1) how to utilize a new algorithm for aligning alignments that optimally solves the common subproblem of merging subalignments, and (2) what is the best choice of method for each stage to obtain the highest quality alignment. RESULTS We study six stages in the form-and-polish strategy for multiple alignment: parameter choice, distance estimation, merge-tree construction, sequence-pair weighting, alignment merging, and polishing. For each stage, we consider novel approaches as well as standard ones. Interestingly, the greatest gains in alignment quality come from (i) estimating distances by a new approach using normalized alignment costs, and (ii) polishing by a new approach using 3-cuts. Experiments with a parameter-value oracle suggest large gains in quality may be possible through an input-dependent choice of alignment parameters, and we present a promising approach for building such an oracle. Combining the best approaches to each stage yields a new tool we call Opal that on benchmark alignments matches the quality of the top tools, without employing alignment consistency or hydrophobic gap penalties. AVAILABILITY Opal, a multiple alignment tool that implements the best methods in our study, is freely available at http://opal.cs.arizona.edu.
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Affiliation(s)
- Travis J Wheeler
- Department of Computer Science, The University of Arizona, Tucson, AZ 85721, USA.
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Abstract
Two recent studies demonstrated a positive correlation between divergence in gene expression and protein sequence in Drosophila. This correlation could be driven by positive selection or variation in functional constraint. To distinguish between these alternatives, we compared patterns of molecular evolution for 1,862 genes with two previously reported estimates of expression divergence in Drosophila. We found a slight negative trend (nonsignificant) between positive selection on protein sequence and divergence in expression levels between Drosophila melanogaster and Drosophila simulans. Conversely, shifts in expression patterns during Drosophila development showed a positive association with adaptive protein evolution, though as before the relationship was weak and not significant. Overall, we found no strong evidence for an increase in the incidence of positive selection on protein-coding regions in genes with divergent expression in Drosophila, suggesting that the previously reported positive association between protein and regulatory divergence primarily reflects variation in functional constraint.
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Cutter AD, Good JM, Pappas CT, Saunders MA, Starrett DM, Wheeler TJ. Transposable element orientation bias in the Drosophila melanogaster genome. J Mol Evol 2005; 61:733-41. [PMID: 16315105 DOI: 10.1007/s00239-004-0243-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2004] [Accepted: 05/26/2005] [Indexed: 10/25/2022]
Abstract
Nonrandom distributions of transposable elements can be generated by a variety of genomic features. Using the full D. melanogaster genome as a model, we characterize the orientations of different classes of transposable elements in relation to the directionality of genes. DNA-mediated transposable elements are more likely to be in the same orientation as neighboring genes when they occur in the nontranscribed region's that flank genes. However, RNA-mediated transposable elements located in an intron are more often oriented in the direction opposite to that of the host gene. These orientation biases are strongest for genes with highly biased codon usage, probably reflecting the ability of such loci to respond to weak positive or negative selection. The leading hypothesis for selection against transposable elements in the coding orientation proposes that transcription termination poly(A) signal motifs within retroelements interfere with normal gene transcription. However, after accounting for differences in base composition between the strands, we find no evidence for global selection against spurious transcription termination signals in introns. We therefore conclude that premature termination of host gene transcription due to the presence of poly(A) signal motifs in retroelements might only partially explain strand-specific detrimental effects in the D. melanogaster genome.
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Affiliation(s)
- Asher D Cutter
- Department of Ecology & Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA.
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Abstract
SUMMARY Errors are prevalent in cDNA sequences but the extent to which sequence collections differ in frequencies and types of errors has not been investigated systematically. cDNA quality control, or cQC, was developed to evaluate the quality of cDNA sequence collections and to revise those sequences that differ from a higher quality genomic sequence. After removing rRNA, vector, bacterial insertion sequence and chimeric cDNA contaminants, small-scale nucleotide discrepancies were found in 51% of cDNA sequences from one Arabidopsis cDNA collection, 89% from a second Arabidopsis collection and 75% from a rice collection. These errors created premature termination codons in 4 and 42% of cDNA sequences in the respective Arabidopsis collections and in 7% of the rice cDNA sequences.
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Affiliation(s)
- Celine A Hayden
- Department of Plant Sciences, University of Arizona, Tucson, AZ 85721-0036, USA
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Abstract
Previously we showed that hypoxia in heart stimulates glucose transport via translocation of glucose transporters from intracellular membranes to the plasma membrane. We later showed that rotenone, an inhibitor of oxidative phosphorylation, also decreased intracellular transporters. Here, using another membrane fractionation technique, we show that rotenone increases plasma membrane transporters, and that another respiratory chain inhibitor, azide, acts similarly. Thus, they likely activate the same signaling pathway as hypoxia. Genistein, a tyrosine kinase inhibitor, inhibited insulin- and azide-stimulated 3-O-methylglucose transport similarly in cardiac myocytes. It also increased glucose transporters in the plasma membranes of perfused hearts even though it inhibited glucose uptake, suggesting effects on membrane trafficking. Another tyrosine kinase inhibitor, lavendustin A, and the cyclic nucleotide-dependent protein kinase inhibitors H-8 and H-7 had little effect on basal or azide-stimulated transport. Polymyxin B was a weak inhibitor of basal, insulin-stimulated, and azide-stimulated transport. A nitric oxide donor and a nitric oxide synthase inhibitor had no effect on basal and azide-stimulated transport. The results indicate that tyrosine kinases; protein kinases A, G, and C; and nitric oxide are not involved in the hypoxic activation of cardiac glucose transport.
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Affiliation(s)
- V L Colston
- Department of Biochemistry and Molecular Biology, University of Louisville, KY 40292, USA
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Abstract
We examined several aspects of glucose transport reconstituted in liposomes, with emphasis on transporters of rat heart (mostly GLUT4) compared to those of human erythrocytes (GLUT1), and on effects of agents that modulate transport in intact cells. Several types of samples gave higher reconstituted activity using liposomes of egg lipids rather than soybean lipids. Diacylglycerol, proposed to activate transporters directly as part of the mechanism of insulin action, increased the intrinsic activity of heart transporters by only 25%, but increased the size of the reconstituted liposomes by 90%. The dipeptide Cbz-Gly-Phe-NH2 inhibited GLUT4 with a Ki of 0.2 mM, compared to 2.5 mM for GLUT1, which explains its preferential inhibition of insulin-stimulated glucose transport in adipocytes. Verapamil, which inhibits insulin- and hypoxia-stimulated glucose transport in muscle, had no effect on reconstituted transporters. Heart transporters had a higher Km for glucose uptake (13.4) than did GLUT1 (1.6 mM), in agreement with a recent study of GLUT1 and GLUT4 expressed in yeast and reconstituted in liposomes. Transporters reconstituted from heart and adipocytes were 40-70% inactivated by external trypsin, suggesting the presence of trypsin-sensitive sites on the cytoplasmic domain of GLUT4. NaCl and KCl both reduced reconstituted transport activity, but KCl had a much smaller effect on the size of the liposomes.
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry and Molecular Biology, University of Louisville, Louisville, KY 40292, USA.
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Abstract
We present our experience with pentobarbital for sedation during mechanical ventilation in six infants when fentanyl and midazolam failed. The patients ranged in age from 2 to 17 months and in weight from 3.0 to 11.4 kg. Before the switch to pentobarbital, the maximum doses of fentanyl ranged from 7 to 13 micrograms/kg/hr and the midazolam infusions, from 0.2 to 0.4 mg/kg/hr. Pentobarbital was administered as a bolus dose followed by a continuous infusion. The hourly infusion rates ranged from 1 to 4 mg/kg. Adequate sedation was achieved in all six patients. In the four patients who required neuromuscular blocking agents, their use was discontinued after pentobarbital was given. The antihypertensive agents (diazoxide and nitroprusside) required by the two patients receiving extracorporeal membrane oxygenation were also discontinued after pentobarbital administration. Although we continue to use fentanyl and benzodiazepines as first-line drugs for sedation, pentobarbital may be an effective alternative when these agents fail.
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Affiliation(s)
- J D Tobias
- Department of Anesthesiology, Vanderbilt University, Nashville, TN 37232
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Wheeler TJ, Fell RD, Hauck MA. Translocation of two glucose transporters in heart: effects of rotenone, uncouplers, workload, palmitate, insulin and anoxia. Biochim Biophys Acta 1994; 1196:191-200. [PMID: 7841183 DOI: 10.1016/0005-2736(94)00211-8] [Citation(s) in RCA: 48] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Our previous studies on the acute regulation of glucose transport in perfused rat hearts were extended to explore further the mechanism of regulation by anoxia; to test the effects of palmitate, a transport inhibitor; and to compare the translocation of two glucose transporter isoforms (GLUT1 and GLUT4). Following heart perfusions under various conditions, glucose transporters in intracellular membranes were quantitated by reconstitution of transport activity and by Western blotting. Rotenone stimulated glucose uptake and decreased the intracellular contents of glucose transporters. This indicates that it activates glucose transport via net outward translocation, similarly to anoxia. However, two uncouplers of oxidative phosphorylation produced little or no effect. Increased workload (which stimulates glucose transport) reduced the intracellular contents of transporters, while palmitate increased the contents, indicating that these factors cause net translocation from or to the intracellular pool, respectively. Relative changes in GLUT1 were similar to those in GLUT4 for most factors tested. A plot of changes in total intracellular transporter content vs. changes in glucose uptake was roughly linear, with a slope of -0.18. This indicates that translocation accounts for most of the changes in glucose transport, and the basal pool of intracellular transporters is five times as large as the plasma membrane pool.
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville, KY 40292
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Tobias JD, Flanagan JF, Wheeler TJ, Garrett JS, Burney C. Noninvasive monitoring of end-tidal CO2 via nasal cannulas in spontaneously breathing children during the perioperative period. Crit Care Med 1994; 22:1805-8. [PMID: 7956285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To determine the correlation between end-tidal CO2 and PaCO2 values measured via nasal cannulas in spontaneously breathing children during the perioperative period. DESIGN Prospective evaluation. SETTING Pediatric intensive/intermediate care unit in a tertiary care referral center. PATIENTS Thirty postoperative surgical and trauma patients aged < or = 18 yrs (average age 7.8 yrs [range 6 months to 16 yrs] and average weight 28.3 kg (range 8.5 to 69). MEASUREMENTS AND MAIN RESULTS Spontaneously breathing, nonintubated patients with an arterial cannula in place were selected for study. End-tidal CO2 was sampled from nasal cannulas by a sidestream aspirator and was estimated by infrared spectroscopy. The difference between PaCO2 and end-tidal CO2 was compared using linear regression analysis. A total of 55 blood gas measurements were obtained on the 30 patients. The PaCO2 to end-tidal CO2 gradient was < or = 4 torr in 54 of the 55 samples. The mean PaCO2 was 39.5 +/- 3.3 torr (5.27 +/- 0.44 kPa) with a mean end-tidal CO2 value of 39.7 +/- 3.8 torr (5.29 +/- 0.51 kPa). Linear regression analysis of arterial vs. end-tidal CO2 yielded a slope of 0.992 and p = .0001. CONCLUSIONS End-tidal CO2 measurement by infrared spectroscopy provided an accurate estimation of PaCO2 in this patient population. Its use may limit the need for invasive monitoring and/or repeated arterial blood gas analysis.
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Affiliation(s)
- J D Tobias
- Department of Anesthesiology, Vanderbilt University, Nashville, TN 37232
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Wheeler TJ, Tobias JD. Complications of autotransfusion with salvaged blood. J Post Anesth Nurs 1994; 9:150-2. [PMID: 7799232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
As a means of limiting homologous transfusions, many centers are using autotransfusion devices during the postoperative period. Although their use may limit the risks associated with homologous blood administration, various adverse effects have been reported including sepsis, disseminated intravascular coagulation, and renal insufficiency. The authors present the case of a 9-year-old girl who developed acute cardiorespiratory dysfunction after reinfusion of salvaged blood. The use of autotransfusion devices and the probable mechanisms responsible for adverse effects are discussed.
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Abstract
In a study of 3-O-methylglucose transport in insulin-stimulated rat adipocytes (catalyzed primarily by the GLUT4 isoform), it was reported that at 37 degrees C the Km and Vmax were 2.8-fold higher for net efflux than for equilibrium exchange (Vinten, J. (1984) Biochim. Biophys. Acta 772, 244-250). Because of its implications for the relative sizes of steps in the transport cycle, we reinvestigated this phenomenon. Accelerated net efflux was apparent when the extracellular methylglucose was diluted 26-fold but not when it was diluted 11-fold. When analyzed according to the one-site alternating conformation model, the data indicate about a 1.7-fold higher Vmax for efflux than for exchange, only about 40% of the difference reported previously. Together with other results in the literature, the accelerated net flux indicates that the conformational change of the loaded transporter from its outward-facing to its inward-facing form is likely the slowest step in the transport cycle, in contrast to the case for GLUT1. Experiments at 25 degrees C indicate a lower degree of accelerated net flux than at 37 degrees C. This is consistent with the above conformational change being the step with the lowest activation energy, as for GLUT1.
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville School of Medicine, KY 40292
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Abstract
ATP has been reported to affect glucose transport in human erythrocytes and resealed erythrocyte ghosts [Jacquez, J. A. (1983) Biochim. Biophys. Acta 727, 367-378; Jensen, M. R., & Brahm, J. (1987) Biochim. Biophys. Acta 900, 282-290]. In more detailed studies, effects of micromolar levels of ATP on transport in ghosts and inside-out vesicles, and on the fluorescence of ghosts and the purified glucose transporter [Carruthers, A. (1986) Biochemistry 25, 3592-3602; Hebert, D. N., & Carruthers, A. (1986) J. Biol. Chem. 261, 10093-10099; Carruthers, A. (1986) J. Biol. Chem. 261, 11028-11037], have been interpreted as supporting a model in which ATP regulates the catalytic properties of the transporter. Both allosteric and covalent effects of ATP were proposed; among the allosteric effects was a 60% reduction in the Km for zero-trans uptake. In order to test whether allosteric ATP regulation of the transporter occurs, we reconstituted glucose transport activity into liposomes using erythrocyte membranes without detergent treatment. The effects of ATP, present either outside, inside, or both inside and outside the liposomes, on the transport activity were examined. Effects of ATP on trypsin-treated liposomes, which have only a single orientation of active transporters, were also tested. While the model predicts activation by ATP, only inhibition was observed. This was significant only at millimolar concentrations of ATP, in contrast to the previously reported effects at micromolar levels, and was primarily on the extracellular surface of the transporter. In addition, the ATP effects on reconstituted transport were nonspecific, with similar effects produced by tripolyphosphate.(ABSTRACT TRUNCATED AT 250 WORDS)
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville School of Medicine, Kentucky 40292
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Abstract
Three compounds which inhibit glucose transport in rat adipocytes have been proposed to act directly on the glucose transporter protein. We tested these proposals by examining the effects of the compounds on the stereospecific glucose uptake catalyzed by adipocyte membrane proteins after reconstitution into liposomes. Effects on the transport activity reconstituted from human erythrocyte membranes were also examined. Glucose 6-phosphate, which was suggested to inhibit the transporter noncompetitively (Foley, J.E. and Huecksteadt, T.P. (1984) Biochim. Biophys. Acta 805, 313-316), had no effect on either type of reconstituted transporter, even when present at 5 mM on both sides of the liposomal membranes. Thus, it is unlikely to act directly on the transporter. The metalloendoproteinase substrate dipeptide Cbz-Gly-Phe-NH2, which inhibited insulin-stimulated but not basal glucose uptake in adipocytes (Aiello, L.P., Wessling-Resnick, M. and Pilch, P.F. (1986) Biochemistry 25, 3944-3950), inhibited the reconstituted erythrocyte transporter noncompetitively with a Ki of 1.5-2 mM. The inhibition of the erythrocyte transporter was identical in liposomes of soybean and egg lipid. Transport reconstituted using adipocyte membrane fractions was also inhibited by the dipeptide, with the activity from basal microsomes more sensitive than that from insulin-stimulated plasma membranes. These results indicate that the dipeptide interacts directly with the transporter, and may be a potentially useful probe for changes in transporter structure accompanying insulin action. Phenylarsine oxide, which was suggested to act directly on the adipocyte transporter (Douen, A.G., and Jones, M.N. (1988) Biochim. Biophys. Acta 968, 109-118), produced only slight (about 10%) inhibition of the reconstituted adipocyte and erythrocyte transporters, even when present at 100-200 microM and after 30 min of pretreatment. These results suggest that the major actions of phenylarsine oxide observed in adipocytes are not direct effects on the transporter, but rather effects on the pathways by which insulin regulates glucose transport activity (Frost, S.C. and Lane, M.D. (1985) J. Biol. Chem. 260, 2646-2652).
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville School of Medicine, KY 40292
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Saunders RA, Wheeler TJ. Statements made to police and road traffic accident analysis. J R Soc Health 1989; 109:26-9. [PMID: 2494336 DOI: 10.1177/146642408910900112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Wheeler TJ. Translocation of glucose transporters in response to anoxia in heart. J Biol Chem 1988; 263:19447-54. [PMID: 3058699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
We tested whether translocation of glucose transporters between subcellular membrane fractions is involved in the stimulation of glucose transport by anoxia by perfusing rat hearts in the presence or absence of oxygen. The hearts were then fractionated by a modification of the procedures of Watanabe, et al. (Watanabe, T., Smith, M. M., Robinson, F. W., and Kono, T. (1984) J. Biol. Chem. 259, 13117-13122), who previously demonstrated translocation in response to insulin in heart, to give plasma membrane and high-speed pellet fractions. The contents of glucose transporters in the two fractions were determined by reconstitution of transport activity, D-glucose-reversible binding of cytochalasin B, and labeling with antibodies against the erythrocyte transporter. The heart transporter was also recognized by antibodies against the COOH-terminal peptide of the glucose transporter. All three types of assays revealed a decrease (20-30%) in the high-speed pellet fraction and an increase (20-70%) in the plasma membranes in response to anoxia. Treatment of hearts with insulin produced a similar extent of translocation and a similar stimulation (about 2-fold) of glucose uptake, indicating that translocation plays a role of similar importance in the stimulation of transport by both of these effectors.
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville School of Medicine, Kentucky 40292
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Abstract
It has been claimed that the Km for infinite-cis uptake of glucose in human erythrocytes is so low that the carrier model for transport must be rejected. We redetermined this parameter for three experimental conditions and found instead that the Km values were in good agreement with the model. For each of a variety of cis glucose concentrations, cells were preequilibrated with various concentrations of glucose, and the apparent Km was determined as the intracellular concentration reducing the initial rate of net uptake by half. The dependence of the apparent Km values on the cis glucose was as predicted by the carrier model; the infinite-cis Km was determined from both this concentration dependence and the extrapolated value at infinite cis glucose. The resulting values were 15 mM for fresh blood at 0 degrees C, 39 mM for outdated blood at 0 degrees C, and 11 mM for outdated blood at 25 degrees C. Previous measurements of the Km at room temperature yielded values of 2-3 mM. These earlier studies used a time course procedure that indicated rapid changes in rates during the initial 10 s of uptake but did not directly measure such changes. We examined the uptake of 60 mM glucose at 20 degrees C into cells containing 0 and 5 mM glucose; rapid changes in rates were not observed in the first few seconds, and the time courses were more consistent with our higher Km values. Our new values, together with other initial rate measurements in the literature, support the adequacy of the carrier model to account for the kinetics of glucose transport in human erythrocytes.
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Affiliation(s)
- T J Wheeler
- Department of Biochemistry, University of Louisville School of Medicine, Kentucky 40292
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Abstract
As a step in the purification and characterization of the glucose transporter from rat skeletal muscle, we have reconstituted glucose transport activity in liposomes. Plasma membranes were prepared from skeletal muscle which display D-glucose reversible binding of cytochalasin B (10 pmol sites/mg protein; KD = 0.3 microM). Older rats gave a slightly lower specific activity and much lower yield of sites per g muscle than young rats. Glucose transport activity was reconstituted into liposomes by the freeze-thaw procedure using either plasma membranes directly or cholate-extracted membrane proteins; the latter gave a 50% higher specific activity. The reconstituted transport activity was stereospecific, saturable, and inhibited by cytochalasin B, phloretin, and mercuric chloride. The optimum cholate concentration for extraction and reconstitution of transport activity was about 1.5%, and the highest specific activity of reconstituted transport was seen only at low ratios of protein to lipid in the reconstitution. Chromatography on agarose lentil lectin and agarose ethanethiol doubled both the specific activity of reconstituted transport and the fraction of glucose uptake which was stereospecific. In all of these respects the results were similar to our results with the bovine heart transporter (T. J. Wheeler and M. A. Hauck, Biochim. Biophys. Acta 818, 171-182 (1985)). Our findings suggest that further purification procedures developed for the heart transporter may be applicable to the skeletal muscle transporter as well.
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