Institution
Kettering University
Education•Flint, Michigan, United States•
About: Kettering University is a education organization based out in Flint, Michigan, United States. It is known for research contribution in the topics: Cancer & RNA. The organization has 6842 authors who have published 7689 publications receiving 337503 citations. The organization is also known as: GMI Engineering & Management Institute & General Motors Institute.
Topics: Cancer, RNA, Antigen, DNA, Population
Papers published on a yearly basis
Papers
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TL;DR: It is determined that Clostridium scindens, a bile acid 7α-dehydroxylating intestinal bacterium, is associated with resistance to C. difficile infection and, upon administration, enhances resistance to infection in a secondary bile Acid dependent fashion.
Abstract: The gastrointestinal tracts of mammals are colonized by hundreds of microbial species that contribute to health, including colonization resistance against intestinal pathogens. Many antibiotics destroy intestinal microbial communities and increase susceptibility to intestinal pathogens. Among these, Clostridium difficile, a major cause of antibiotic-induced diarrhoea, greatly increases morbidity and mortality in hospitalized patients. Which intestinal bacteria provide resistance to C. difficile infection and their in vivo inhibitory mechanisms remain unclear. Here we correlate loss of specific bacterial taxa with development of infection, by treating mice with different antibiotics that result in distinct microbiota changes and lead to varied susceptibility to C. difficile. Mathematical modelling augmented by analyses of the microbiota of hospitalized patients identifies resistance-associated bacteria common to mice and humans. Using these platforms, we determine that Clostridium scindens, a bile acid 7α-dehydroxylating intestinal bacterium, is associated with resistance to C. difficile infection and, upon administration, enhances resistance to infection in a secondary bile acid dependent fashion. Using a workflow involving mouse models, clinical studies, metagenomic analyses, and mathematical modelling, we identify a probiotic candidate that corrects a clinically relevant microbiome deficiency. These findings have implications for the rational design of targeted antimicrobials as well as microbiome-based diagnostics and therapeutics for individuals at risk of C. difficile infection.
1,413 citations
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Massachusetts Institute of Technology1, Broad Institute2, Howard Hughes Medical Institute3, University of Cambridge4, European Bioinformatics Institute5, Wellcome Trust Sanger Institute6, Harvard University7, Weizmann Institute of Science8, University of Zurich9, Laboratory of Molecular Biology10, Utrecht University11, École Polytechnique Fédérale de Lausanne12, University of Pennsylvania13, Heidelberg University14, German Cancer Research Center15, Ludwig Maximilian University of Munich16, John Radcliffe Hospital17, Newcastle University18, Stanford University19, University of Oxford20, University of California, San Francisco21, Allen Institute for Brain Science22, Karolinska Institutet23, Royal Institute of Technology24, Icahn School of Medicine at Mount Sinai25, University of Cape Town26, University Medical Center Groningen27, Radboud University Nijmegen28, Kettering University29, University of Edinburgh30, Babraham Institute31, New York University32, Netherlands Cancer Institute33, Ragon Institute of MGH, MIT and Harvard34, University of Texas Health Science Center at Houston35, Technische Universität München36, Technical University of Denmark37, University of California, Berkeley38, King's College London39, California Institute of Technology40
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Abstract: The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.
1,391 citations
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TL;DR: Genetic analysis shows that Wim, Polaris and the IFT motor protein Kif3a are required for Hedgehog signalling at a step downstream of Patched1 (the Hedgehog receptor) and upstream of direct targets of hedgehog signalling.
Abstract: Intraflagellar transport (IFT) proteins were first identified as essential factors for the growth and maintenance of flagella in the single-celled alga Chlamydomonas reinhardtii. In a screen for embryonic patterning mutations induced by ethylnitrosourea, here we identify two mouse mutants, wimple (wim) and flexo (fxo), that lack ventral neural cell types and show other phenotypes characteristic of defects in Sonic hedgehog signalling. Both mutations disrupt IFT proteins: the wim mutation is an allele of the previously uncharacterized mouse homologue of IFT172; and fxo is a new hypomorphic allele of polaris, the mouse homologue of IFT88. Genetic analysis shows that Wim, Polaris and the IFT motor protein Kif3a are required for Hedgehog signalling at a step downstream of Patched1 (the Hedgehog receptor) and upstream of direct targets of Hedgehog signalling. Our data show that IFT machinery has an essential and vertebrate-specific role in Hedgehog signal transduction.
1,345 citations
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TL;DR: The findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, contingent on the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.
Abstract: The similarity in the three-dimensional structures of homologous proteins imposes strong constraints on their sequence variability. It has long been suggested that the resulting correlations among amino acid compositions at different sequence positions can be exploited to infer spatial contacts within the tertiary protein structure. Crucial to this inference is the ability to disentangle direct and indirect correlations, as accomplished by the recently introduced direct-coupling analysis (DCA). Here we develop a computationally efficient implementation of DCA, which allows us to evaluate the accuracy of contact prediction by DCA for a large number of protein domains, based purely on sequence information. DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global structure of the contact map for the majority of the protein domains examined. Furthermore, our analysis captures clear signals beyond intradomain residue contacts, arising, e.g., from alternative protein conformations, ligand-mediated residue couplings, and interdomain interactions in protein oligomers. Our findings suggest that contacts predicted by DCA can be used as a reliable guide to facilitate computational predictions of alternative protein conformations, protein complex formation, and even the de novo prediction of protein domain structures, contingent on the existence of a large number of homologous sequences which are being rapidly made available due to advances in genome sequencing.
1,319 citations
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TL;DR: It is demonstrated that directing a CD19-specific CAR to the T- cell receptor α constant (TRAC) locus not only results in uniform CAR expression in human peripheral blood T cells, but also enhances T-cell potency, with edited cells vastly outperforming conventionally generated CAR T cells in a mouse model of acute lymphoblastic leukaemia.
Abstract: Chimeric antigen receptors (CARs) are synthetic receptors that redirect and reprogram T cells to mediate tumour rejection. The most successful CARs used to date are those targeting CD19 (ref. 2), which offer the prospect of complete remission in patients with chemorefractory or relapsed B-cell malignancies. CARs are typically transduced into the T cells of a patient using γ-retroviral vectors or other randomly integrating vectors, which may result in clonal expansion, oncogenic transformation, variegated transgene expression and transcriptional silencing. Recent advances in genome editing enable efficient sequence-specific interventions in human cells, including targeted gene delivery to the CCR5 and AAVS1 loci. Here we show that directing a CD19-specific CAR to the T-cell receptor α constant (TRAC) locus not only results in uniform CAR expression in human peripheral blood T cells, but also enhances T-cell potency, with edited cells vastly outperforming conventionally generated CAR T cells in a mouse model of acute lymphoblastic leukaemia. We further demonstrate that targeting the CAR to the TRAC locus averts tonic CAR signalling and establishes effective internalization and re-expression of the CAR following single or repeated exposure to antigen, delaying effector T-cell differentiation and exhaustion. These findings uncover facets of CAR immunobiology and underscore the potential of CRISPR/Cas9 genome editing to advance immunotherapies.
1,219 citations
Authors
Showing all 6853 results
Name | H-index | Papers | Citations |
---|---|---|---|
Joan Massagué | 189 | 408 | 149951 |
Chris Sander | 178 | 713 | 233287 |
Timothy A. Springer | 167 | 669 | 122421 |
Murray F. Brennan | 161 | 925 | 97087 |
Charles M. Rice | 154 | 561 | 83812 |
Lloyd J. Old | 152 | 775 | 101377 |
Howard I. Scher | 151 | 944 | 101737 |
Paul Tempst | 148 | 309 | 89225 |
Pier Paolo Pandolfi | 146 | 529 | 88334 |
Barton F. Haynes | 144 | 911 | 79014 |
Jedd D. Wolchok | 140 | 713 | 123336 |
James P. Allison | 137 | 483 | 83336 |
Harold E. Varmus | 137 | 496 | 76320 |
Scott W. Lowe | 134 | 396 | 89376 |
David S. Klimstra | 133 | 564 | 61682 |