1
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Bukhman YV, Morin PA, Meyer S, Chu LF, Jacobsen JK, Antosiewicz-Bourget J, Mamott D, Gonzales M, Argus C, Bolin J, Berres ME, Fedrigo O, Steill J, Swanson SA, Jiang P, Rhie A, Formenti G, Phillippy AM, Harris RS, Wood JMD, Howe K, Kirilenko BM, Munegowda C, Hiller M, Jain A, Kihara D, Johnston JS, Ionkov A, Raja K, Toh H, Lang A, Wolf M, Jarvis ED, Thomson JA, Chaisson MJP, Stewart R. A High-Quality Blue Whale Genome, Segmental Duplications, and Historical Demography. Mol Biol Evol 2024; 41:msae036. [PMID: 38376487 PMCID: PMC10919930 DOI: 10.1093/molbev/msae036] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 01/11/2024] [Accepted: 01/22/2024] [Indexed: 02/21/2024] Open
Abstract
The blue whale, Balaenoptera musculus, is the largest animal known to have ever existed, making it an important case study in longevity and resistance to cancer. To further this and other blue whale-related research, we report a reference-quality, long-read-based genome assembly of this fascinating species. We assembled the genome from PacBio long reads and utilized Illumina/10×, optical maps, and Hi-C data for scaffolding, polishing, and manual curation. We also provided long read RNA-seq data to facilitate the annotation of the assembly by NCBI and Ensembl. Additionally, we annotated both haplotypes using TOGA and measured the genome size by flow cytometry. We then compared the blue whale genome with other cetaceans and artiodactyls, including vaquita (Phocoena sinus), the world's smallest cetacean, to investigate blue whale's unique biological traits. We found a dramatic amplification of several genes in the blue whale genome resulting from a recent burst in segmental duplications, though the possible connection between this amplification and giant body size requires further study. We also discovered sites in the insulin-like growth factor-1 gene correlated with body size in cetaceans. Finally, using our assembly to examine the heterozygosity and historical demography of Pacific and Atlantic blue whale populations, we found that the genomes of both populations are highly heterozygous and that their genetic isolation dates to the last interglacial period. Taken together, these results indicate how a high-quality, annotated blue whale genome will serve as an important resource for biology, evolution, and conservation research.
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Affiliation(s)
- Yury V Bukhman
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Phillip A Morin
- Southwest Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), La Jolla, CA 92037, USA
| | - Susanne Meyer
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Li-Fang Chu
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
- Department of Comparative Biology and Experimental Medicine, University of Calgary, Calgary, Canada
| | | | | | - Daniel Mamott
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Maylie Gonzales
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Cara Argus
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Jennifer Bolin
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Mark E Berres
- University of Wisconsin Biotechnology Center, Bioinformatics Resource Center, University of Wisconsin - Madison, Madison, WI 53706, USA
| | - Olivier Fedrigo
- Vertebrate Genome Lab, The Rockefeller University, New York, NY 10065, USA
| | - John Steill
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Scott A Swanson
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Peng Jiang
- Center for Gene Regulation in Health and Disease (GRHD), Cleveland State University, Cleveland, OH, USA
- Department of Biological, Geological and Environmental Sciences, Cleveland State University, Cleveland, OH, USA
- Center for RNA Science and Therapeutics, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Arang Rhie
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Giulio Formenti
- Laboratory of Neurogenetics of Language, The Rockefeller University/HHMI, New York, NY 10065, USA
| | - Adam M Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Robert S Harris
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | | | - Kerstin Howe
- Tree of Life, Wellcome Sanger Institute, Cambridge CB10 1SA, UK
| | - Bogdan M Kirilenko
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Institute of Cell Biology and Neuroscience, Faculty of Biosciences, Goethe University Frankfurt, 60438 Frankfurt, Germany
| | - Chetan Munegowda
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Institute of Cell Biology and Neuroscience, Faculty of Biosciences, Goethe University Frankfurt, 60438 Frankfurt, Germany
| | - Michael Hiller
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Institute of Cell Biology and Neuroscience, Faculty of Biosciences, Goethe University Frankfurt, 60438 Frankfurt, Germany
| | - Aashish Jain
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
- Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA
| | - J Spencer Johnston
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| | - Alexander Ionkov
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Kalpana Raja
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Huishi Toh
- Neuroscience Research Institute, University of California, Santa Barbara, CA, USA
| | - Aimee Lang
- Southwest Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), La Jolla, CA 92037, USA
| | - Magnus Wolf
- Institute for Evolution and Biodiversity (IEB), University of Muenster, 48149, Muenster, Germany
- Senckenberg Biodiversity and Climate Research Centre (BiK-F), Frankfurt am Main, Germany
| | - Erich D Jarvis
- Vertebrate Genome Lab, The Rockefeller University, New York, NY 10065, USA
- Laboratory of Neurogenetics of Language, The Rockefeller University/HHMI, New York, NY 10065, USA
| | - James A Thomson
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
- Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106, USA
- Department of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA
| | - Mark J P Chaisson
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, Los Angeles, CA 90089, USA
| | - Ron Stewart
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
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John SV, Seim GL, Erazo-Flores BJ, Steill J, Freeman J, Votava JA, Arp NL, Qing X, Stewart R, Knoll LJ, Fan J. Macrophages undergo functionally significant reprograming of nucleotide metabolism upon classical activation. bioRxiv 2023:2023.12.27.573447. [PMID: 38234794 PMCID: PMC10793465 DOI: 10.1101/2023.12.27.573447] [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: 01/19/2024]
Abstract
During an immune response, macrophages systematically rewire their metabolism in specific ways to support their diversve functions. However, current knowledge of macrophage metabolism is largely concentrated on central carbon metabolism. Using multi-omics analysis, we identified nucleotide metabolism as one of the most significantly rewired pathways upon classical activation. Further isotopic tracing studies revealed several major changes underlying the substantial metabolomic alterations: 1) de novo synthesis of both purines and pyrimidines is shut down at several specific steps; 2) nucleotide degradation activity to nitrogenous bases is increased but complete oxidation of bases is reduced, causing a great accumulation of nucleosides and bases; and 3) cells gradually switch to primarily relying on salvaging the nucleosides and bases for maintaining most nucleotide pools. Mechanistically, the inhibition of purine nucleotide de novo synthesis is mainly caused by nitric oxide (NO)-driven inhibition of the IMP synthesis enzyme ATIC, with NO-independent transcriptional downregulation of purine synthesis genes augmenting the effect. The inhibition of pyrimidine nucleotide de novo synthesis is driven by NO-driven inhibition of CTP synthetase (CTPS) and transcriptional downregulation of thymidylate synthase (TYMS). For the rewiring of degradation, purine nucleoside phosphorylase (PNP) and uridine phosphorylase (UPP) are transcriptionally upregulated, increasing nucleoside degradation activity. However, complete degradation of purine bases by xanthine oxidoreductase (XOR) is inhibited by NO, diverting flux into nucleotide salvage. Inhibiting the activation-induced switch from nucleotide de novo synthesis to salvage by knocking out the purine salvage enzyme hypoxanthine-guanine phosporibosyl transferase (Hprt) significantly alters the expression of genes important for activated macrophage functions, suppresses macrophage migration, and increases pyroptosis. Furthermore, knocking out Hprt or Xor increases proliferation of the intracellular parasite Toxoplasma gondii in macrophages. Together, these studies comprehensively reveal the characteristics, the key regulatory mechanisms, and the functional importance of the dynamic rewiring of nucleotide metabolism in classically activated macrophages.
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Affiliation(s)
- Steven V John
- Morgridge Institute for Research, Madison, WI
- Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI
| | - Gretchen L Seim
- Morgridge Institute for Research, Madison, WI
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI
| | - Billy J Erazo-Flores
- Cellular and Molecular Pathology Graduate Program, University of Wisconsin-Madison, Madison, WI
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI
| | - John Steill
- Morgridge Institute for Research, Madison, WI
| | | | | | - Nicholas L Arp
- Morgridge Institute for Research, Madison, WI
- Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI
| | - Xin Qing
- Morgridge Institute for Research, Madison, WI
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI
| | - Laura J Knoll
- Cellular and Molecular Pathology Graduate Program, University of Wisconsin-Madison, Madison, WI
- Department of Medical Microbiology and Immunology, University of Wisconsin-Madison, Madison, WI
| | - Jing Fan
- Morgridge Institute for Research, Madison, WI
- Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI
- Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, WI
- Lead contact
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3
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Conrad JV, Meyer S, Ramesh PS, Neira JA, Rusteika M, Mamott D, Duffin B, Bautista M, Zhang J, Hiles E, Higgins EM, Steill J, Freeman J, Ni Z, Liu S, Ungrin M, Rancourt D, Clegg DO, Stewart R, Thomson JA, Chu LF. Efficient derivation of transgene-free porcine induced pluripotent stem cells enables in vitro modeling of species-specific developmental timing. Stem Cell Reports 2023; 18:2328-2343. [PMID: 37949072 PMCID: PMC10724057 DOI: 10.1016/j.stemcr.2023.10.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 10/10/2023] [Accepted: 10/10/2023] [Indexed: 11/12/2023] Open
Abstract
Sus scrofa domesticus (pig) has served as a superb large mammalian model for biomedical studies because of its comparable physiology and organ size to humans. The derivation of transgene-free porcine induced pluripotent stem cells (PiPSCs) will, therefore, benefit the development of porcine-specific models for regenerative biology and its medical applications. In the past, this effort has been hampered by a lack of understanding of the signaling milieu that stabilizes the porcine pluripotent state in vitro. Here, we report that transgene-free PiPSCs can be efficiently derived from porcine fibroblasts by episomal vectors along with microRNA-302/367 using optimized protocols tailored for this species. PiPSCs can be differentiated into derivatives representing the primary germ layers in vitro and can form teratomas in immunocompromised mice. Furthermore, the transgene-free PiPSCs preserve intrinsic species-specific developmental timing in culture, known as developmental allochrony. This is demonstrated by establishing a porcine in vitro segmentation clock model that, for the first time, displays a specific periodicity at ∼3.7 h, a timescale recapitulating in vivo porcine somitogenesis. We conclude that the transgene-free PiPSCs can serve as a powerful tool for modeling development and disease and developing transplantation strategies. We also anticipate that they will provide insights into conserved and unique features on the regulations of mammalian pluripotency and developmental timing mechanisms.
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Affiliation(s)
- J Vanessa Conrad
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada
| | - Susanne Meyer
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Pranav S Ramesh
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada
| | - Jaime A Neira
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada; Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Margaret Rusteika
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada; Department of Biomedical Engineering, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Daniel Mamott
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Bret Duffin
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Monica Bautista
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada
| | - Jue Zhang
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Emily Hiles
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada
| | - Eve M Higgins
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada
| | - John Steill
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Jack Freeman
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Zijian Ni
- Department of Statistics, University of Wisconsin, Madison, WI 53706, USA
| | - Shiying Liu
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Mark Ungrin
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada; Department of Biomedical Engineering, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Derrick Rancourt
- Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada; Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Dennis O Clegg
- Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA 93106, USA; Department of Molecular, Cellular, & Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - James A Thomson
- Morgridge Institute for Research, Madison, WI 53715, USA; Department of Molecular, Cellular, & Developmental Biology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
| | - Li-Fang Chu
- Faculty of Veterinary Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada; Reproductive Biology and Regenerative Medicine Research Group, University of Calgary, Calgary, AB T2N 4N1, Canada; Alberta Children's Hospital Research Institute, Calgary, AB T2N 4N1, Canada; Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada.
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4
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Millikin RJ, Raja K, Steill J, Lock C, Tu X, Ross I, Tsoi LC, Kuusisto F, Ni Z, Livny M, Bockelman B, Thomson J, Stewart R. Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models. BMC Bioinformatics 2023; 24:412. [PMID: 37915001 PMCID: PMC10619245 DOI: 10.1186/s12859-023-05539-y] [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: 05/24/2023] [Accepted: 10/19/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND The PubMed archive contains more than 34 million articles; consequently, it is becoming increasingly difficult for a biomedical researcher to keep up-to-date with different knowledge domains. Computationally efficient and interpretable tools are needed to help researchers find and understand associations between biomedical concepts. The goal of literature-based discovery (LBD) is to connect concepts in isolated literature domains that would normally go undiscovered. This usually takes the form of an A-B-C relationship, where A and C terms are linked through a B term intermediate. Here we describe Serial KinderMiner (SKiM), an LBD algorithm for finding statistically significant links between an A term and one or more C terms through some B term intermediate(s). The development of SKiM is motivated by the observation that there are only a few LBD tools that provide a functional web interface, and that the available tools are limited in one or more of the following ways: (1) they identify a relationship but not the type of relationship, (2) they do not allow the user to provide their own lists of B or C terms, hindering flexibility, (3) they do not allow for querying thousands of C terms (which is crucial if, for instance, the user wants to query connections between a disease and the thousands of available drugs), or (4) they are specific for a particular biomedical domain (such as cancer). We provide an open-source tool and web interface that improves on all of these issues. RESULTS We demonstrate SKiM's ability to discover useful A-B-C linkages in three control experiments: classic LBD discoveries, drug repurposing, and finding associations related to cancer. Furthermore, we supplement SKiM with a knowledge graph built with transformer machine-learning models to aid in interpreting the relationships between terms found by SKiM. Finally, we provide a simple and intuitive open-source web interface ( https://skim.morgridge.org ) with comprehensive lists of drugs, diseases, phenotypes, and symptoms so that anyone can easily perform SKiM searches. CONCLUSIONS SKiM is a simple algorithm that can perform LBD searches to discover relationships between arbitrary user-defined concepts. SKiM is generalized for any domain, can perform searches with many thousands of C term concepts, and moves beyond the simple identification of an existence of a relationship; many relationships are given relationship type labels from our knowledge graph.
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Affiliation(s)
| | - Kalpana Raja
- Morgridge Institute for Research, Madison, WI, USA
- Currently at Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA
| | - John Steill
- Morgridge Institute for Research, Madison, WI, USA
| | - Cannon Lock
- Morgridge Institute for Research, Madison, WI, USA
| | - Xuancheng Tu
- Morgridge Institute for Research, Madison, WI, USA
| | - Ian Ross
- Center for High Throughput Computing, Computer Sciences Department, University of Wisconsin, Madison, WI, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Finn Kuusisto
- Morgridge Institute for Research, Madison, WI, USA
- Currently at Data Science Institute, University of Wisconsin, Madison, WI, USA
| | - Zijian Ni
- Department of Statistics, University of Wisconsin, Madison, WI, USA
- Currently at Amazon, Seattle, WA, USA
| | - Miron Livny
- Morgridge Institute for Research, Madison, WI, USA
- Center for High Throughput Computing, Computer Sciences Department, University of Wisconsin, Madison, WI, USA
| | | | - James Thomson
- Morgridge Institute for Research, Madison, WI, USA
- Department of Cell and Regenerative Biology, University of Wisconsin, Madison, WI, USA
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI, USA.
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5
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Tattersall MC, Esnault S, Stewart R, Vereide DT, Swanson S, Zhang J, Steill J, Jarjour N, Hansen KM, Korcarz CE, Baker TB, Stein JH. Effects of an In Vivo Vaping Challenge on In Vitro Interleukin-6 Biosynthesis Pathways in Arterial Endothelial Cells Derived From Human Embryonic Stem Cells. J Am Heart Assoc 2023:e030139. [PMID: 37449574 PMCID: PMC10382107 DOI: 10.1161/jaha.123.030139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023]
Affiliation(s)
- Matthew C Tattersall
- Department of Medicine, Division of Cardiovascular Medicine University of Wisconsin School of Medicine and Public Health Madison WI
| | - Stephane Esnault
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine The University of Wisconsin-Madison School of Medicine and Public Health Madison WI
| | | | | | | | - Jue Zhang
- Morgridge Institute for Research Madison WI
| | | | - Nizar Jarjour
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine The University of Wisconsin-Madison School of Medicine and Public Health Madison WI
| | - Kristin M Hansen
- Department of Medicine, Division of Cardiovascular Medicine University of Wisconsin School of Medicine and Public Health Madison WI
| | - Claudia E Korcarz
- Department of Medicine, Division of Cardiovascular Medicine University of Wisconsin School of Medicine and Public Health Madison WI
| | - Timothy B Baker
- University of Wisconsin Center for Tobacco Research and Intervention (UW-CTRI) University of Wisconsin School of Medicine and Public Health Madison WI
| | - James H Stein
- Department of Medicine, Division of Cardiovascular Medicine University of Wisconsin School of Medicine and Public Health Madison WI
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6
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Millikin RJ, Raja K, Steill J, Lock C, Tu X, Ross I, Tsoi LC, Kuusisto F, Ni Z, Livny M, Bockelman B, Thomson J, Stewart R. Serial KinderMiner (SKiM) Discovers and Annotates Biomedical Knowledge Using Co-Occurrence and Transformer Models. bioRxiv 2023:2023.05.30.542911. [PMID: 37397987 PMCID: PMC10312590 DOI: 10.1101/2023.05.30.542911] [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: 07/04/2023]
Abstract
Background The PubMed database contains more than 34 million articles; consequently, it is becoming increasingly difficult for a biomedical researcher to keep up-to-date with different knowledge domains. Computationally efficient and interpretable tools are needed to help researchers find and understand associations between biomedical concepts. The goal of literature-based discovery (LBD) is to connect concepts in isolated literature domains that would normally go undiscovered. This usually takes the form of an A-B-C relationship, where A and C terms are linked through a B term intermediate. Here we describe Serial KinderMiner (SKiM), an LBD algorithm for finding statistically significant links between an A term and one or more C terms through some B term intermediate(s). The development of SKiM is motivated by the the observation that there are only a few LBD tools that provide a functional web interface, and that the available tools are limited in one or more of the following ways: 1) they identify a relationship but not the type of relationship, 2) they do not allow the user to provide their own lists of B or C terms, hindering flexibility, 3) they do not allow for querying thousands of C terms (which is crucial if, for instance, the user wants to query connections between a disease and the thousands of available drugs), or 4) they are specific for a particular biomedical domain (such as cancer). We provide an open-source tool and web interface that improves on all of these issues. Results We demonstrate SKiM's ability to discover useful A-B-C linkages in three control experiments: classic LBD discoveries, drug repurposing, and finding associations related to cancer. Furthermore, we supplement SKiM with a knowledge graph built with transformer machine-learning models to aid in interpreting the relationships between terms found by SKiM. Finally, we provide a simple and intuitive open-source web interface ( https://skim.morgridge.org ) with comprehensive lists of drugs, diseases, phenotypes, and symptoms so that anyone can easily perform SKiM searches. Conclusions SKiM is a simple algorithm that can perform LBD searches to discover relationships between arbitrary user-defined concepts. SKiM is generalized for any domain, can perform searches with many thousands of C term concepts, and moves beyond the simple identification of an existence of a relationship; many relationships are given relationship type labels from our knowledge graph.
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7
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Zhang J, Webster S, Duffin B, Bernstein MN, Steill J, Swanson S, Forsberg MH, Bolin J, Brown ME, Majumder A, Capitini CM, Stewart R, Thomson JA, Slukvin II. Generation of anti-GD2 CAR macrophages from human pluripotent stem cells for cancer immunotherapies. Stem Cell Reports 2023; 18:585-596. [PMID: 36638788 PMCID: PMC9968983 DOI: 10.1016/j.stemcr.2022.12.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [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: 08/30/2022] [Revised: 12/14/2022] [Accepted: 12/14/2022] [Indexed: 01/15/2023] Open
Abstract
Macrophages armed with chimeric antigen receptors (CARs) provide a potent new option for treating solid tumors. However, genetic engineering and scalable production of somatic macrophages remains significant challenges. Here, we used CRISPR-Cas9 gene editing methods to integrate an anti-GD2 CAR into the AAVS1 locus of human pluripotent stem cells (hPSCs). We then established a serum- and feeder-free differentiation protocol for generating CAR macrophages (CAR-Ms) through arterial endothelial-to-hematopoietic transition (EHT). CAR-M produced by this method displayed a potent cytotoxic activity against GD2-expressing neuroblastoma and melanoma in vitro and neuroblastoma in vivo. This study provides a new platform for the efficient generation of off-the-shelf CAR-Ms for antitumor immunotherapy.
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Affiliation(s)
- Jue Zhang
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Sarah Webster
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Bret Duffin
- Morgridge Institute for Research, Madison, WI 53715, USA
| | | | - John Steill
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Scott Swanson
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Matthew H Forsberg
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Jennifer Bolin
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Matthew E Brown
- Department of Surgery, University of Wisconsin-Madison, Madison, WI 53792, USA
| | - Aditi Majumder
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Christian M Capitini
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI 53792, USA; Carbone Cancer Center, University of Wisconsin-Madison, Madison 53705, WI, USA
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI 53715, USA
| | | | - Igor I Slukvin
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA; Department of Cell & Regenerative Biology, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI 53705, USA.
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8
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Kuusisto F, Ng D, Steill J, Ross I, Livny M, Thomson J, Page D, Stewart R. KinderMiner Web: a simple web tool for ranking pairwise associations in biomedical applications. F1000Res 2021; 9:832. [PMID: 35083039 PMCID: PMC8756297 DOI: 10.12688/f1000research.25523.2] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/14/2021] [Indexed: 11/21/2022] Open
Abstract
Many important scientific discoveries require lengthy experimental processes of trial and error and could benefit from intelligent prioritization based on deep domain understanding. While exponential growth in the scientific literature makes it difficult to keep current in even a single domain, that same rapid growth in literature also presents an opportunity for automated extraction of knowledge via text mining. We have developed a web application implementation of the KinderMiner algorithm for proposing ranked associations between a list of target terms and a key phrase. Any key phrase and target term list can be used for biomedical inquiry. We built the web application around a text index derived from PubMed. It is the first publicly available implementation of the algorithm, is fast and easy to use, and includes an interactive analysis tool. The KinderMiner web application is a public resource offering scientists a cohesive summary of what is currently known about a particular topic within the literature, and helping them to prioritize experiments around that topic. It performs comparably or better to similar state-of-the-art text mining tools, is more flexible, and can be applied to any biomedical topic of interest. It is also continually improving with quarterly updates to the underlying text index and through response to suggestions from the community. The web application is available at
https://www.kinderminer.org.
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Affiliation(s)
- Finn Kuusisto
- Morgridge Institute for Research, Madison, WI, 53715, USA
| | - Daniel Ng
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - John Steill
- Morgridge Institute for Research, Madison, WI, 53715, USA
| | - Ian Ross
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Miron Livny
- Morgridge Institute for Research, Madison, WI, 53715, USA
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - James Thomson
- Morgridge Institute for Research, Madison, WI, 53715, USA
- Department of Molecular and Cellular Biology, University of California, Santa Barbara, Santa Barbara, CA, 93117, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - David Page
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, 27710, USA
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI, 53715, USA
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9
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Brown J, Barry C, Schmitz MT, Argus C, Bolin JM, Schwartz MP, Van Aartsen A, Steill J, Swanson S, Stewart R, Thomson JA, Kendziorski C. Interspecies chimeric conditions affect the developmental rate of human pluripotent stem cells. PLoS Comput Biol 2021; 17:e1008778. [PMID: 33647016 PMCID: PMC7951976 DOI: 10.1371/journal.pcbi.1008778] [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] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 03/11/2021] [Accepted: 02/08/2021] [Indexed: 12/17/2022] Open
Abstract
Human pluripotent stem cells hold significant promise for regenerative medicine. However, long differentiation protocols and immature characteristics of stem cell-derived cell types remain challenges to the development of many therapeutic applications. In contrast to the slow differentiation of human stem cells in vitro that mirrors a nine-month gestation period, mouse stem cells develop according to a much faster three-week gestation timeline. Here, we tested if co-differentiation with mouse pluripotent stem cells could accelerate the differentiation speed of human embryonic stem cells. Following a six-week RNA-sequencing time course of neural differentiation, we identified 929 human genes that were upregulated earlier and 535 genes that exhibited earlier peaked expression profiles in chimeric cell cultures than in human cell cultures alone. Genes with accelerated upregulation were significantly enriched in Gene Ontology terms associated with neurogenesis, neuron differentiation and maturation, and synapse signaling. Moreover, chimeric mixed samples correlated with in utero human embryonic samples earlier than human cells alone, and acceleration was dose-dependent on human-mouse co-culture ratios. The altered gene expression patterns and developmental rates described in this report have implications for accelerating human stem cell differentiation and the use of interspecies chimeric embryos in developing human organs for transplantation.
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Affiliation(s)
- Jared Brown
- Department of Statistics, University of Wisconsin-Madison, Wisconsin, United States of America
- * E-mail: (JB); (CK)
| | - Christopher Barry
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Matthew T. Schmitz
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Cara Argus
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Jennifer M. Bolin
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Michael P. Schwartz
- NSF Center for Sustainable Nanotechnology, Department of Chemistry, University of Wisconsin-Madison, Wisconsin, United States of America
| | - Amy Van Aartsen
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - John Steill
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Scott Swanson
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - Ron Stewart
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
| | - James A. Thomson
- Morgridge Institute for Research, Madison, Wisconsin, United States of America
- Department of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, United States of America
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, California, United States of America
| | - Christina Kendziorski
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Wisconsin, United States of America
- * E-mail: (JB); (CK)
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Kuusisto F, Ng D, Steill J, Ross I, Livny M, Thomson J, Page D, Stewart R. KinderMiner Web: a simple web tool for ranking pairwise associations in biomedical applications. F1000Res 2020; 9:832. [PMID: 35083039 PMCID: PMC8756297 DOI: 10.12688/f1000research.25523.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/14/2021] [Indexed: 11/03/2023] Open
Abstract
Many important scientific discoveries require lengthy experimental processes of trial and error and could benefit from intelligent prioritization based on deep domain understanding. While exponential growth in the scientific literature makes it difficult to keep current in even a single domain, that same rapid growth in literature also presents an opportunity for automated extraction of knowledge via text mining. We have developed a web application implementation of the KinderMiner algorithm for proposing ranked associations between a list of target terms and a key phrase. Any key phrase and target term list can be used for biomedical inquiry. We built the web application around a text index derived from PubMed. It is the first publicly available implementation of the algorithm, is fast and easy to use, and includes an interactive analysis tool. The KinderMiner web application is a public resource offering scientists a cohesive summary of what is currently known about a particular topic within the literature, and helping them to prioritize experiments around that topic. It performs comparably or better to similar state-of-the-art text mining tools, is more flexible, and can be applied to any biomedical topic of interest. It is also continually improving with quarterly updates to the underlying text index and through response to suggestions from the community. The web application is available at https://www.kinderminer.org.
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Affiliation(s)
- Finn Kuusisto
- Morgridge Institute for Research, Madison, WI, 53715, USA
| | - Daniel Ng
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - John Steill
- Morgridge Institute for Research, Madison, WI, 53715, USA
| | - Ian Ross
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Miron Livny
- Morgridge Institute for Research, Madison, WI, 53715, USA
- Computer Sciences Department, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - James Thomson
- Morgridge Institute for Research, Madison, WI, 53715, USA
- Department of Molecular and Cellular Biology, University of California, Santa Barbara, Santa Barbara, CA, 93117, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - David Page
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, 27710, USA
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI, 53715, USA
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11
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Barry C, Schmitz MT, Argus C, Bolin JM, Probasco MD, Leng N, Duffin BM, Steill J, Swanson S, McIntosh BE, Stewart R, Kendziorski C, Thomson JA, Bacher R. Automated minute scale RNA-seq of pluripotent stem cell differentiation reveals early divergence of human and mouse gene expression kinetics. PLoS Comput Biol 2019; 15:e1007543. [PMID: 31815944 PMCID: PMC6922475 DOI: 10.1371/journal.pcbi.1007543] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 12/19/2019] [Accepted: 11/12/2019] [Indexed: 12/22/2022] Open
Abstract
Pluripotent stem cells retain the developmental timing of their species of origin in vitro, an observation that suggests the existence of a cell-intrinsic developmental clock, yet the nature and machinery of the clock remain a mystery. We hypothesize that one possible component may lie in species-specific differences in the kinetics of transcriptional responses to differentiation signals. Using a liquid-handling robot, mouse and human pluripotent stem cells were exposed to identical neural differentiation conditions and sampled for RNA-sequencing at high frequency, every 4 or 10 minutes, for the first 10 hours of differentiation to test for differences in transcriptomic response rates. The majority of initial transcriptional responses occurred within a rapid window in the first minutes of differentiation for both human and mouse stem cells. Despite similarly early onsets of gene expression changes, we observed shortened and condensed gene expression patterns in mouse pluripotent stem cells compared to protracted trends in human pluripotent stem cells. Moreover, the speed at which individual genes were upregulated, as measured by the slopes of gene expression changes over time, was significantly faster in mouse compared to human cells. These results suggest that downstream transcriptomic response kinetics to signaling cues are faster in mouse versus human cells, and may offer a partial account for the vast differences in developmental rates across species.
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Affiliation(s)
- Christopher Barry
- Morgridge Institute for Research, Madison, WI, United States of America
| | | | - Cara Argus
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Jennifer M. Bolin
- Morgridge Institute for Research, Madison, WI, United States of America
| | | | - Ning Leng
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Bret M. Duffin
- Morgridge Institute for Research, Madison, WI, United States of America
| | - John Steill
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Scott Swanson
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Brian E. McIntosh
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Ron Stewart
- Morgridge Institute for Research, Madison, WI, United States of America
| | - Christina Kendziorski
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States of America
| | - James A. Thomson
- Morgridge Institute for Research, Madison, WI, United States of America
- Department of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States of America
- Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, United States of America
| | - Rhonda Bacher
- Department of Biostatistics, University of Florida, Gainesville, FL, United States of America
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12
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Kuusisto F, Steill J, Kuang Z, Thomson J, Page D, Stewart R. A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications. AMIA Jt Summits Transl Sci Proc 2017; 2017:166-174. [PMID: 28815126 PMCID: PMC5543342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
We present a simple text mining method that is easy to implement, requires minimal data collection and preparation, and is easy to use for proposing ranked associations between a list of target terms and a key phrase. We call this method KinderMiner, and apply it to two biomedical applications. The first application is to identify relevant transcription factors for cell reprogramming, and the second is to identify potential drugs for investigation in drug repositioning. We compare the results from our algorithm to existing data and state-of-the-art algorithms, demonstrating compelling results for both application areas. While we apply the algorithm here for biomedical applications, we argue that the method is generalizable to any available corpus of sufficient size.
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Affiliation(s)
| | - John Steill
- Morgridge Institute for Research, Madison, USA
| | | | - James Thomson
- Morgridge Institute for Research, Madison, USA;,University of Wisconsin, Madison, USA
| | | | - Ron Stewart
- Morgridge Institute for Research, Madison, USA
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13
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Zhang J, Schwartz MP, Hou Z, Bai Y, Ardalani H, Swanson S, Steill J, Ruotti V, Elwell A, Nguyen BK, Bolin J, Stewart R, Thomson JA, Murphy WL. A Genome-wide Analysis of Human Pluripotent Stem Cell-Derived Endothelial Cells in 2D or 3D Culture. Stem Cell Reports 2017; 8:907-918. [PMID: 28343999 PMCID: PMC5390115 DOI: 10.1016/j.stemcr.2017.02.014] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [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: 09/07/2016] [Revised: 02/15/2017] [Accepted: 02/16/2017] [Indexed: 02/07/2023] Open
Abstract
A defined protocol for efficiently deriving endothelial cells from human pluripotent stem cells was established and vascular morphogenesis was used as a model system to understand how synthetic hydrogels influence global biological function compared with common 2D and 3D culture platforms. RNA sequencing demonstrated that gene expression profiles were similar for endothelial cells and pericytes cocultured in polyethylene glycol (PEG) hydrogels or Matrigel, while monoculture comparisons identified distinct vascular signatures for each cell type. Endothelial cells cultured on tissue-culture polystyrene adopted a proliferative phenotype compared with cells cultured on or encapsulated in PEG hydrogels. The proliferative phenotype correlated to increased FAK-ERK activity, and knockdown or inhibition of ERK signaling reduced proliferation and expression for cell-cycle genes while increasing expression for “3D-like” vasculature development genes. Our results provide insight into the influence of 2D and 3D culture formats on global biological processes that regulate cell function. Defined, high-efficiency differentiation of human PSCs to endothelial cell Comprehensive genome-wide comparisons of 2D and 3D cell-culture formats Gene expression profiles for endothelial cells and pericytes in 3D cell culture Highly proliferative phenotypes on tissue-culture polystyrene surfaces
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Affiliation(s)
- Jue Zhang
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Michael P Schwartz
- Department of Biomedical Engineering, University of Wisconsin-Madison, Wisconsin Institute for Medical Research, Room 5405, Madison, WI 53706, USA.
| | - Zhonggang Hou
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Yongsheng Bai
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Hamisha Ardalani
- Department of Biomedical Engineering, University of Wisconsin-Madison, Wisconsin Institute for Medical Research, Room 5405, Madison, WI 53706, USA
| | - Scott Swanson
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - John Steill
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Victor Ruotti
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Angela Elwell
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Bao Kim Nguyen
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Jennifer Bolin
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - Ron Stewart
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA
| | - James A Thomson
- Regenerative Biology, Morgridge Institute for Research, Madison, WI 53715, USA; Department of Cell & Regenerative Biology, University of Wisconsin-Madison, Madison, WI 53705, USA; Department of Molecular, Cellular, & Developmental Biology, University of California, Santa Barbara, CA 93117, USA
| | - William L Murphy
- Department of Biomedical Engineering, University of Wisconsin-Madison, Wisconsin Institute for Medical Research, Room 5405, Madison, WI 53706, USA; Materials Science Program, University of Wisconsin-Madison, Madison, WI 53706, USA; Department of Orthopedics and Rehabilitation, University of Wisconsin-Madison, Madison, WI 53705, USA.
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Kirkegaard MC, Langford J, Steill J, Anderson B, Miskowiec A. Vibrational properties of anhydrous and partially hydrated uranyl fluoride. J Chem Phys 2017; 146:024502. [DOI: 10.1063/1.4973430] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Affiliation(s)
- M. C. Kirkegaard
- University of Tennessee–Knoxville, Knoxville, Tennessee 37996, USA
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - J. Langford
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - J. Steill
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - B. Anderson
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - A. Miskowiec
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
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Downar TJ, Wu JY, Steill J, Janardhan R. Parallel and Serial Applications of the RETRAN-03 Power Plant Simulation Code Using Domain Decomposition and Krylov Subspace Methods. NUCL TECHNOL 1997. [DOI: 10.13182/nt97-a35320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Thomas J. Downar
- Purdue University School of Nuclear Engineering, West Lafayette, Indiana 47907-1290
| | - Jen-Ying Wu
- Purdue University School of Nuclear Engineering, West Lafayette, Indiana 47907-1290
| | - John Steill
- Purdue University School of Nuclear Engineering, West Lafayette, Indiana 47907-1290
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