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Zhao B, Gong W, Ma A, Chen J, Velegraki M, Dong H, Liu Z, Wang L, Okimoto T, Jones DM, Lei YL, Long M, Oestreich KJ, Ma Q, Xin G, Carbone DP, He K, Li Z, Wen H. SUSD2 suppresses CD8 + T cell antitumor immunity by targeting IL-2 receptor signaling. Nat Immunol 2022; 23:1588-1599. [PMID: 36266363 PMCID: PMC9669207 DOI: 10.1038/s41590-022-01326-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 09/08/2022] [Indexed: 11/09/2022]
Abstract
Dysfunctional CD8+ T cells, which have defective production of antitumor effectors, represent a major mediator of immunosuppression in the tumor microenvironment. Here, we show that SUSD2 is a negative regulator of CD8+ T cell antitumor function. Susd2-/- effector CD8+ T cells showed enhanced production of antitumor molecules, which consequently blunted tumor growth in multiple syngeneic mouse tumor models. Through a quantitative mass spectrometry assay, we found that SUSD2 interacted with interleukin (IL)-2 receptor α through sushi domain-dependent protein interactions and that this interaction suppressed the binding of IL-2, an essential cytokine for the effector functions of CD8+ T cells, to IL-2 receptor α. SUSD2 was not expressed on regulatory CD4+ T cells and did not affect the inhibitory function of these cells. Adoptive transfer of Susd2-/- chimeric antigen receptor T cells induced a robust antitumor response in mice, highlighting the potential of SUSD2 as an immunotherapy target for cancer.
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Affiliation(s)
- Bao Zhao
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Weipeng Gong
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Anjun Ma
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - Jianwen Chen
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Maria Velegraki
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Hong Dong
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Zihao Liu
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Lingling Wang
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, Division of Hematology, The Ohio State University, Columbus, OH, USA
| | - Tamio Okimoto
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University, Columbus, OH, USA
| | - Devin M Jones
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Yu L Lei
- Department of Periodontics and Oral Medicine, University of Michigan School of Dentistry, Ann Arbor, MI, USA
| | - Meixiao Long
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, Division of Hematology, The Ohio State University, Columbus, OH, USA
| | - Kenneth J Oestreich
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
| | - Qin Ma
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
| | - Gang Xin
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - David P Carbone
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University, Columbus, OH, USA
| | - Kai He
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
- Department of Internal Medicine, Division of Medical Oncology, The Ohio State University, Columbus, OH, USA
| | - Zihai Li
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Haitao Wen
- Department of Microbial Infection and Immunity, Infectious Disease Institute, The Ohio State University, Columbus, OH, USA.
- Pelotonia Institute for Immuno-Oncology, The Ohio State University, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.
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2
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Dai C, Rennhack JP, Arnoff TE, Thaker M, Younger ST, Doench JG, Huang AY, Yang A, Aguirre AJ, Wang B, Mun E, O'Connell JT, Huang Y, Labella K, Talamas JA, Li J, Ilic N, Hwang J, Hong AL, Giacomelli AO, Gjoerup O, Root DE, Hahn WC. SMAD4 represses FOSL1 expression and pancreatic cancer metastatic colonization. Cell Rep 2021; 36:109443. [PMID: 34320363 PMCID: PMC8350598 DOI: 10.1016/j.celrep.2021.109443] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 04/26/2021] [Accepted: 07/02/2021] [Indexed: 02/07/2023] Open
Abstract
Metastasis is a complex and poorly understood process. In pancreatic cancer, loss of the transforming growth factor (TGF)-β/BMP effector SMAD4 is correlated with changes in altered histopathological transitions, metastatic disease, and poor prognosis. In this study, we use isogenic cancer cell lines to identify SMAD4 regulated genes that contribute to the development of metastatic colonization. We perform an in vivo screen identifying FOSL1 as both a SMAD4 target and sufficient to drive colonization to the lung. The targeting of these genes early in treatment may provide a therapeutic benefit.
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Affiliation(s)
- Chao Dai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jonathan P Rennhack
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Taylor E Arnoff
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Maneesha Thaker
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Scott T Younger
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - John G Doench
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - August Yue Huang
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115, USA
| | - Annan Yang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Andrew J Aguirre
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Belinda Wang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Evan Mun
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Northeastern University, Boston, MA 02115, USA
| | - Joyce T O'Connell
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ying Huang
- Molecular Pathology Core Lab, Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Katherine Labella
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jessica A Talamas
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ji Li
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nina Ilic
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Justin Hwang
- Masonic Cancer Center and Department of Medicine, University of Minnesota-Twin Cities, Minneapolis, MN 55455, USA
| | - Andrew L Hong
- Department of Pediatrics, Emory University, Atlanta, GA 30322, USA
| | - Andrew O Giacomelli
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Princess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada
| | - Ole Gjoerup
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - David E Root
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - William C Hahn
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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3
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Lai S, Jia L, Subramanian B, Pan S, Zhang J, Dong Y, Chen WH, Zhao XM. mMGE: a database for human metagenomic extrachromosomal mobile genetic elements. Nucleic Acids Res 2021; 49:D783-D791. [PMID: 33074335 PMCID: PMC7778953 DOI: 10.1093/nar/gkaa869] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 09/18/2020] [Accepted: 09/24/2020] [Indexed: 12/15/2022] Open
Abstract
Extrachromosomal mobile genetic elements (eMGEs), including phages and plasmids, that can move across different microbes, play important roles in genome evolution and shaping the structure of microbial communities. However, we still know very little about eMGEs, especially their abundances, distributions and putative functions in microbiomes. Thus, a comprehensive description of eMGEs is of great utility. Here we present mMGE, a comprehensive catalog of 517 251 non-redundant eMGEs, including 92 492 plasmids and 424 759 phages, derived from diverse body sites of 66 425 human metagenomic samples. About half the eMGEs could be further grouped into 70 074 clusters using relaxed criteria (referred as to eMGE clusters below). We provide extensive annotations of the identified eMGEs including sequence characteristics, taxonomy affiliation, gene contents and their prokaryotic hosts. We also calculate the prevalence, both within and across samples for each eMGE and eMGE cluster, enabling users to see putative associations of eMGEs with human phenotypes or their distribution preferences. All eMGE records can be browsed or queried in multiple ways, such as eMGE clusters, metagenomic samples and associated hosts. The mMGE is equipped with a user-friendly interface and a BLAST server, facilitating easy access/queries to all its contents easily. mMGE is freely available for academic use at: https://mgedb.comp-sysbio.org.
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Affiliation(s)
- Senying Lai
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Longhao Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Balakrishnan Subramanian
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
| | - Shaojun Pan
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Jinglong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Yanqi Dong
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Wei-Hua Chen
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
- College of Life Science, Henan Normal University, Xinxiang, Henan 453007, China
| | - Xing-Ming Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Shanghai 200433, China
- Research Institute of Intelligent Complex System, Fudan University, Shanghai 200433, China
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4
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Abstract
There was an explosion in the amount of commercially available DNA in sequence repositories over the last decade. The number of such plasmids increased from 12,000 to over 300,000 among three of the largest repositories: iGEM, Addgene, and DNASU. A challenge in biodesign remains how to use these and other repository-based sequences effectively, correctly, and seamlessly. This work describes an approach to plasmid design where a plasmid is specified as simply a DNA sequence or list of features. The proposed software then finds the most cost-effective combination of synthetic and PCR-prepared repository fragments to build the plasmid via Gibson assembly®. It finds existing DNA sequences in both user-specified and public DNA databases: iGEM, Addgene, and DNASU. Such a software application is introduced and characterized against all post-2005 iGEM composite parts and all Addgene vectors submitted in 2018 and found to reduce costs by 34% versus a purely synthetic plasmid design approach. The described software will improve current plasmid assembly workflows by shortening design times, improving build quality, and reducing costs.
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Affiliation(s)
- Joshua J. Timmons
- Lattice Automation Inc., Boston, Massachusetts, United States of America
| | - Doug Densmore
- Lattice Automation Inc., Boston, Massachusetts, United States of America
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts, United States of America
- Biological Design Center, Boston University, Boston, Massachusetts, United States of America
- * E-mail:
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5
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Dhaliwal NK, Abatti LE, Mitchell JA. KLF4 protein stability regulated by interaction with pluripotency transcription factors overrides transcriptional control. Genes Dev 2019; 33:1069-1082. [PMID: 31221664 PMCID: PMC6672055 DOI: 10.1101/gad.324319.119] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 05/13/2019] [Indexed: 12/14/2022]
Abstract
Embryonic stem (ES) cells are regulated by a network of transcription factors that maintain the pluripotent state. Differentiation relies on down-regulation of pluripotency transcription factors disrupting this network. While investigating transcriptional regulation of the pluripotency transcription factor Kruppel-like factor 4 (Klf4), we observed that homozygous deletion of distal enhancers caused a 17-fold decrease in Klf4 transcript but surprisingly decreased protein levels by less than twofold, indicating that posttranscriptional control of KLF4 protein overrides transcriptional control. The lack of sensitivity of KLF4 to transcription is due to high protein stability (half-life >24 h). This stability is context-dependent and is disrupted during differentiation, as evidenced by a shift to a half-life of <2 h. KLF4 protein stability is maintained through interaction with other pluripotency transcription factors (NANOG, SOX2, and STAT3) that together facilitate association of KLF4 with RNA polymerase II. In addition, the KLF4 DNA-binding and transactivation domains are required for optimal KLF4 protein stability. Posttranslational modification of KLF4 destabilizes the protein as cells exit the pluripotent state, and mutations that prevent this destabilization also prevent differentiation. These data indicate that the core pluripotency transcription factors are integrated by posttranslational mechanisms to maintain the pluripotent state and identify mutations that increase KLF4 protein stability while maintaining transcription factor function.
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Affiliation(s)
- Navroop K Dhaliwal
- Department of Cell and Systems Biology, University of Toronto, Toronto, Ontaria M5S3G5, Canada
| | - Luis E Abatti
- Department of Cell and Systems Biology, University of Toronto, Toronto, Ontaria M5S3G5, Canada
| | - Jennifer A Mitchell
- Department of Cell and Systems Biology, University of Toronto, Toronto, Ontaria M5S3G5, Canada
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6
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Abstract
One of the most powerful ways to develop hypotheses regarding the biological functions of conserved genes in a given species, such as humans, is to first look at what is known about their function in another species. Model organism databases and other resources are rich with functional information but difficult to mine. Gene2Function addresses a broad need by integrating information about conserved genes in a single online resource.
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7
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Thomas CM, Thomson NR, Cerdeño-Tárraga AM, Brown CJ, Top EM, Frost LS. Annotation of plasmid genes. Plasmid 2017; 91:61-67. [PMID: 28365184 DOI: 10.1016/j.plasmid.2017.03.006] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Accepted: 03/23/2017] [Indexed: 10/19/2022]
Abstract
Good annotation of plasmid genomes is essential to maximise the value of the rapidly increasing volume of plasmid sequences. This short review highlights some of the current issues and suggests some ways forward. Where a well-studied related plasmid system exists we recommend that new annotation adheres to the convention already established for that system, so long as it is based on sound principles and solid experimental evidence, even if some of the new genes are more similar to homologues in different systems. Where a well-established model does not exist we provide generic gene names that reflect likely biochemical activity rather than overall purpose particularly, for example, where genes clearly belong to a type IV secretion system but it is not known whether they function in conjugative transfer or virulence. We also recommend that annotators use a whole system naming approach to avoid ending up with an illogical mixture of names from other systems based on the highest scoring match from a BLAST search. In addition, where function has not been experimentally established we recommend using just the locus tag, rather than a function-related gene name, while recording possible functions as notes rather than in a provisional name.
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Affiliation(s)
- Christopher M Thomas
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK.
| | | | | | - Celeste J Brown
- Department of Biological Sciences, University of Idaho, Moscow, ID 83844-3051, United States
| | - Eva M Top
- Department of Biological Sciences, University of Idaho, Moscow, ID 83844-3051, United States
| | - Laura S Frost
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada
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8
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Yu X, Bian X, Throop A, Song L, Moral LD, Park J, Seiler C, Fiacco M, Steel J, Hunter P, Saul J, Wang J, Qiu J, Pipas JM, LaBaer J. Exploration of panviral proteome: high-throughput cloning and functional implications in virus-host interactions. Am J Cancer Res 2014; 4:808-22. [PMID: 24955142 PMCID: PMC4063979 DOI: 10.7150/thno.8255] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2013] [Accepted: 04/27/2014] [Indexed: 12/24/2022] Open
Abstract
Throughout the long history of virus-host co-evolution, viruses have developed delicate strategies to facilitate their invasion and replication of their genome, while silencing the host immune responses through various mechanisms. The systematic characterization of viral protein-host interactions would yield invaluable information in the understanding of viral invasion/evasion, diagnosis and therapeutic treatment of a viral infection, and mechanisms of host biology. With more than 2,000 viral genomes sequenced, only a small percent of them are well investigated. The access of these viral open reading frames (ORFs) in a flexible cloning format would greatly facilitate both in vitro and in vivo virus-host interaction studies. However, the overall progress of viral ORF cloning has been slow. To facilitate viral studies, we are releasing the initiation of our panviral proteome collection of 2,035 ORF clones from 830 viral genes in the Gateway® recombinational cloning system. Here, we demonstrate several uses of our viral collection including highly efficient production of viral proteins using human cell-free expression system in vitro, global identification of host targets for rubella virus using Nucleic Acid Programmable Protein Arrays (NAPPA) containing 10,000 unique human proteins, and detection of host serological responses using micro-fluidic multiplexed immunoassays. The studies presented here begin to elucidate host-viral protein interactions with our systemic utilization of viral ORFs, high-throughput cloning, and proteomic technologies. These valuable plasmid resources will be available to the research community to enable continued viral functional studies.
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Abstract
Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, "meta" information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.
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Seiler CY, Park JG, Sharma A, Hunter P, Surapaneni P, Sedillo C, Field J, Algar R, Price A, Steel J, Throop A, Fiacco M, LaBaer J. DNASU plasmid and PSI:Biology-Materials repositories: resources to accelerate biological research. Nucleic Acids Res 2013; 42:D1253-60. [PMID: 24225319 PMCID: PMC3964992 DOI: 10.1093/nar/gkt1060] [Citation(s) in RCA: 166] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The mission of the DNASU Plasmid Repository is to accelerate research by providing high-quality, annotated plasmid samples and online plasmid resources to the research community through the curated DNASU database, website and repository (http://dnasu.asu.edu or http://dnasu.org). The collection includes plasmids from grant-funded, high-throughput cloning projects performed in our laboratory, plasmids from external researchers, and large collections from consortia such as the ORFeome Collaboration and the NIGMS-funded Protein Structure Initiative: Biology (PSI:Biology). Through DNASU, researchers can search for and access detailed information about each plasmid such as the full length gene insert sequence, vector information, associated publications, and links to external resources that provide additional protein annotations and experimental protocols. Plasmids can be requested directly through the DNASU website. DNASU and the PSI:Biology-Materials Repositories were previously described in the 2010 NAR Database Issue (Cormier, C.Y., Mohr, S.E., Zuo, D., Hu, Y., Rolfs, A., Kramer, J., Taycher, E., Kelley, F., Fiacco, M., Turnbull, G. et al. (2010) Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community. Nucleic Acids Res., 38, D743-D749.). In this update we will describe the plasmid collection and highlight the new features in the website redesign, including new browse/search options, plasmid annotations and a dynamic vector mapping feature that was developed in collaboration with LabGenius. Overall, these plasmid resources continue to enable research with the goal of elucidating the role of proteins in both normal biological processes and disease.
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Affiliation(s)
- Catherine Y Seiler
- Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, 1001 S. McAllister Dr. Tempe, AZ 85287-6401, USA and LabGenius, 20-22 Bedford Row, London, WC1R 4JS, UK
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11
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Dieteren CEJ, Koopman WJH, Swarts HG, Peters JGP, Maczuga P, van Gemst JJ, Masereeuw R, Smeitink JAM, Nijtmans LGJ, Willems PHGM. Subunit-specific incorporation efficiency and kinetics in mitochondrial complex I homeostasis. J Biol Chem 2012; 287:41851-60. [PMID: 23038253 DOI: 10.1074/jbc.m112.391151] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Studies employing native PAGE suggest that most nDNA-encoded CI subunits form subassemblies before assembling into holo-CI. In addition, in vitro evidence suggests that some subunits can directly exchange in holo-CI. Presently, data on the kinetics of these two incorporation modes for individual CI subunits during CI maintenance are sparse. Here, we used inducible HEK293 cell lines stably expressing AcGFP1-tagged CI subunits and quantified the amount of tagged subunit in mitoplasts and holo-CI by non-native and native PAGE, respectively, to determine their CI incorporation efficiency. Analysis of time courses of induction revealed three subunit-specific patterns. A first pattern, represented by NDUFS1, showed overlapping time courses, indicating that imported subunits predominantly incorporate into holo-CI. A second pattern, represented by NDUFV1, consisted of parallel time courses, which were, however, not quantitatively overlapping, suggesting that imported subunits incorporate at similar rates into holo-CI and CI assembly intermediates. The third pattern, represented by NDUFS3 and NDUFA2, revealed a delayed incorporation into holo-CI, suggesting their prior appearance in CI assembly intermediates and/or as free monomers. Our analysis showed the same maximum incorporation into holo-CI for NDUFV1, NDUFV2, NDUFS1, NDUFS3, NDUFS4, NDUFA2, and NDUFA12 with nearly complete loss of endogenous subunit at 24 h of induction, indicative of an equimolar stoichiometry and unexpectedly rapid turnover. In conclusion, the results presented demonstrate that newly formed nDNA-encoded CI subunits rapidly incorporate into holo-CI in a subunit-specific manner.
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Affiliation(s)
- Cindy E J Dieteren
- Department of Biochemistry, Radboud University Nijmegen Medical Centre, 6500 HB Nijmegen, The Netherlands
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12
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Dugué GP, Akemann W, Knöpfel T. A comprehensive concept of optogenetics. PROGRESS IN BRAIN RESEARCH 2012; 196:1-28. [PMID: 22341318 DOI: 10.1016/b978-0-444-59426-6.00001-x] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Fundamental questions that neuroscientists have previously approached with classical biochemical and electrophysiological techniques can now be addressed using optogenetics. The term optogenetics reflects the key program of this emerging field, namely, combining optical and genetic techniques. With the already impressively successful application of light-driven actuator proteins such as microbial opsins to interact with intact neural circuits, optogenetics rose to a key technology over the past few years. While spearheaded by tools to control membrane voltage, the more general concept of optogenetics includes the use of a variety of genetically encoded probes for physiological parameters ranging from membrane voltage and calcium concentration to metabolism. Here, we provide a comprehensive overview of the state of the art in this rapidly growing discipline and attempt to sketch some of its future prospects and challenges.
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Affiliation(s)
- Guillaume P Dugué
- Champalimaud Neuroscience Programme, Instituto Gulbenkian de Ciência, Oeiras, Portugal.
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13
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Katchman BA, Antwi K, Hostetter G, Demeure MJ, Watanabe A, Decker GA, Miller LJ, Von Hoff DD, Lake DF. Quiescin Sulfhydryl Oxidase 1 Promotes Invasion of Pancreatic Tumor Cells Mediated by Matrix Metalloproteinases. Mol Cancer Res 2011; 9:1621-31. [DOI: 10.1158/1541-7786.mcr-11-0018] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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14
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Design and Construction of a First-Generation High-Throughput Integrated Robotic Molecular Biology Platform for Bioenergy Applications. ACTA ACUST UNITED AC 2011; 16:292-307. [DOI: 10.1016/j.jala.2011.04.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2011] [Indexed: 01/01/2023]
Abstract
The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains Published by Elsevier Inc. on behalf of the Society for Laboratory Automation and Screening for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries.
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15
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NDUFB7 and NDUFA8 are located at the intermembrane surface of complex I. FEBS Lett 2011; 585:737-43. [PMID: 21310150 DOI: 10.1016/j.febslet.2011.01.046] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2010] [Revised: 01/21/2011] [Accepted: 01/31/2011] [Indexed: 01/15/2023]
Abstract
Complex I (NADH:ubiquinone oxidoreductase) is the first and largest protein complex of the oxidative phosphorylation. Crystal structures have elucidated the positions of most subunits of bacterial evolutionary origin in the complex, but the positions of the eukaryotic subunits are unknown. Based on the analysis of sequence conservation we propose intra-molecular disulfide bridges and the inter-membrane space localization of three Cx(9)C-containing subunits in human: NDUFS5, NDUFB7 and NDUFA8. We experimentally confirm the localization of the latter two, while our data are consistent with disulfide bridges in NDUFA8. We propose these subunits stabilize the membrane domain of complex I.
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16
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Hughes SR, Moser BR, Harmsen AJ, Bischoff KM, Jones MA, Pinkelman R, Bang SS, Tasaki K, Doll KM, Qureshi N, Saha BC, Liu S, Jackson JS, Robinson S, Cotta MC, Rich JO, Caimi P. Production of Candida antarctica lipase B gene open reading frame using automated PCR gene assembly protocol on robotic workcell and expression in an ethanologenic yeast for use as resin-bound biocatalyst in biodiesel production. ACTA ACUST UNITED AC 2010; 16:17-37. [PMID: 21609683 DOI: 10.1016/j.jala.2010.04.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2009] [Indexed: 11/27/2022]
Abstract
A synthetic Candida antarctica lipase B (CALB) gene open reading frame (ORF) for expression in yeast was constructed, and the lycotoxin-1 (Lyt-1) C3 variant gene ORF, potentially to improve the availability of the active enzyme at the surface of the yeast cell, was added in frame with the CALB ORF using an automated PCR assembly and DNA purification protocol on an integrated robotic workcell. Saccharomyces cerevisiae strains expressing CALB protein or CALB Lyt-1 fusion protein were first grown on 2% (w/v) glucose, producing 9.3 g/L ethanol during fermentation. The carbon source was switched to galactose for GAL1-driven expression, and the CALB and CALB Lyt-1 enzymes expressed were tested for fatty acid ethyl ester (biodiesel) production. The synthetic enzymes catalyzed the formation of fatty acid ethyl esters from ethanol and either corn or soybean oil. It was further demonstrated that a one-step-charging resin, specifically selected for binding to lipase, was capable of covalent attachment of the CALB Lyt-1 enzyme, and that the resin-bound enzyme catalyzed the production of biodiesel. High-level expression of lipase in an ethanologenic yeast strain has the potential to increase the profitability of an integrated biorefinery by combining bioethanol production with coproduction of a low-cost biocatalyst that converts corn oil to biodiesel.
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Affiliation(s)
- Stephen R Hughes
- Renewable Product Technology Research Unit, United States Department of Agriculture (USDA), Agricultural Research Service (ARS), National Center for Agricultural Utilization Research (NCAUR), Peoria, IL 61604, USA.
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17
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Marina O, Hainz U, Biernacki MA, Zhang W, Cai A, Duke-Cohan JS, Liu F, Brusic V, Neuberg D, Kutok JL, Alyea EP, Canning CM, Soiffer RJ, Ritz J, Wu CJ. Serologic markers of effective tumor immunity against chronic lymphocytic leukemia include nonmutated B-cell antigens. Cancer Res 2010; 70:1344-55. [PMID: 20124481 PMCID: PMC2852266 DOI: 10.1158/0008-5472.can-09-3143] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Patients with chronic lymphocytic leukemia (CLL) who relapse after allogeneic transplant may achieve durable remission following donor lymphocyte infusion (DLI), showing the potency of donor-derived immunity in eradicating tumors. We sought to elucidate the antigenic basis of the effective graft-versus-leukemia (GvL) responses associated with DLI for the treatment of CLL by analyzing the specificity of plasma antibody responses developing in two DLI-treated patients who achieved long-term remission without graft-versus-host disease. By probing high-density protein microarrays with patient plasma, we discovered 35 predominantly intracellular antigens that elicited high-titer antibody reactivity greater in post-DLI than in pre-DLI plasma. Three antigens-C6orf130, MDS032, and ZFYVE19-were identified by both patients. Along with additional candidate antigens DAPK3, SERBP1, and OGFOD1, these proteins showed higher transcript and protein expression in B cells and CLL cells compared with normal peripheral blood mononuclear cells. DAPK3 and the shared antigens do not represent minor histocompatibility antigens, as their sequences are identical in both donor and tumor. Although ZFYVE19, DAPK3, and OGFOD1 elicited minimal antibody reactivity in 12 normal subjects and 12 chemotherapy-treated CLL patients, 5 of 12 CLL patients with clinical GvL responses were serologically reactive to these antigens. Moreover, antibody reactivity against these antigens was temporally correlated with clinical disease regression. These B-cell antigens represent promising biomarkers of effective anti-CLL immunity.
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MESH Headings
- Antigens, Surface/analysis
- Antigens, Surface/blood
- Antigens, Surface/genetics
- Antigens, Surface/metabolism
- B-Lymphocytes/immunology
- B-Lymphocytes/metabolism
- B-Lymphocytes/pathology
- Biomarkers, Tumor/analysis
- Biomarkers, Tumor/blood
- Biomarkers, Tumor/genetics
- Bone Marrow Transplantation/immunology
- Cell Lineage/immunology
- Female
- Humans
- Immunity, Innate/genetics
- Immunity, Innate/immunology
- Immunodominant Epitopes/analysis
- Immunodominant Epitopes/blood
- Leukemia, Lymphocytic, Chronic, B-Cell/blood
- Leukemia, Lymphocytic, Chronic, B-Cell/diagnosis
- Leukemia, Lymphocytic, Chronic, B-Cell/immunology
- Leukemia, Lymphocytic, Chronic, B-Cell/therapy
- Male
- Middle Aged
- Mutation/physiology
- Prognosis
- Protein Array Analysis
- Treatment Outcome
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Affiliation(s)
- Ovidiu Marina
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
- William Beaumont Hospital, Transitional Year Program, Royal Oak, MI
| | - Ursula Hainz
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
| | - Melinda A. Biernacki
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- University of Connecticut School of Medicine, Farmington, CT
| | - Wandi Zhang
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
| | - Ann Cai
- Harvard Medical School, Boston MA
| | - Jonathan S. Duke-Cohan
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- Harvard Medical School, Boston MA
| | - Fenglong Liu
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston MA
| | - Vladimir Brusic
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
| | - Donna Neuberg
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston MA
| | - Jeffery L. Kutok
- Harvard Medical School, Boston MA
- Department of Pathology, Brigham and Women’s Hospital, Boston MA
| | - Edwin P. Alyea
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- Harvard Medical School, Boston MA
- Department of Medicine, Brigham and Women's Hospital, Boston MA
| | - Christine M. Canning
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
| | - Robert J. Soiffer
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- Harvard Medical School, Boston MA
- Department of Medicine, Brigham and Women's Hospital, Boston MA
| | - Jerome Ritz
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- Harvard Medical School, Boston MA
- Department of Medicine, Brigham and Women's Hospital, Boston MA
| | - Catherine J. Wu
- Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston MA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston MA
- Harvard Medical School, Boston MA
- Department of Medicine, Brigham and Women's Hospital, Boston MA
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18
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Cormier CY, Mohr SE, Zuo D, Hu Y, Rolfs A, Kramer J, Taycher E, Kelley F, Fiacco M, Turnbull G, LaBaer J. Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community. Nucleic Acids Res 2009; 38:D743-9. [PMID: 19906724 PMCID: PMC2808882 DOI: 10.1093/nar/gkp999] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The Protein Structure Initiative Material Repository (PSI-MR; http://psimr.asu.edu) provides centralized storage and distribution for the protein expression plasmids created by PSI researchers. These plasmids are a resource that allows the research community to dissect the biological function of proteins whose structures have been identified by the PSI. The plasmid annotation, which includes the full length sequence, vector information and associated publications, is stored in a freely available, searchable database called DNASU (http://dnasu.asu.edu). Each PSI plasmid is also linked to a variety of additional resources, which facilitates cross-referencing of a particular plasmid to protein annotations and experimental data. Plasmid samples can be requested directly through the website. We have also developed a novel strategy to avoid the most common concern encountered when distributing plasmids namely, the complexity of material transfer agreement (MTA) processing and the resulting delays this causes. The Expedited Process MTA, in which we created a network of institutions that agree to the terms of transfer in advance of a material request, eliminates these delays. Our hope is that by creating a repository of expression-ready plasmids and expediting the process for receiving these plasmids, we will help accelerate the accessibility and pace of scientific discovery.
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Affiliation(s)
- Catherine Y Cormier
- Arizona State University, Biodesign Institute, Virginia G Piper Center for Personalized Diagnostics, 1001 S McAllister Dr Tempe, AZ 85287-6401, USA
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19
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Lorimer D, Raymond A, Walchli J, Mixon M, Barrow A, Wallace E, Grice R, Burgin A, Stewart L. Gene composer: database software for protein construct design, codon engineering, and gene synthesis. BMC Biotechnol 2009; 9:36. [PMID: 19383142 PMCID: PMC2681465 DOI: 10.1186/1472-6750-9-36] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2008] [Accepted: 04/21/2009] [Indexed: 12/18/2022] Open
Abstract
Background To improve efficiency in high throughput protein structure determination, we have developed a database software package, Gene Composer, which facilitates the information-rich design of protein constructs and their codon engineered synthetic gene sequences. With its modular workflow design and numerous graphical user interfaces, Gene Composer enables researchers to perform all common bio-informatics steps used in modern structure guided protein engineering and synthetic gene engineering. Results An interactive Alignment Viewer allows the researcher to simultaneously visualize sequence conservation in the context of known protein secondary structure, ligand contacts, water contacts, crystal contacts, B-factors, solvent accessible area, residue property type and several other useful property views. The Construct Design Module enables the facile design of novel protein constructs with altered N- and C-termini, internal insertions or deletions, point mutations, and desired affinity tags. The modifications can be combined and permuted into multiple protein constructs, and then virtually cloned in silico into defined expression vectors. The Gene Design Module uses a protein-to-gene algorithm that automates the back-translation of a protein amino acid sequence into a codon engineered nucleic acid gene sequence according to a selected codon usage table with minimal codon usage threshold, defined G:C% content, and desired sequence features achieved through synonymous codon selection that is optimized for the intended expression system. The gene-to-oligo algorithm of the Gene Design Module plans out all of the required overlapping oligonucleotides and mutagenic primers needed to synthesize the desired gene constructs by PCR, and for physically cloning them into selected vectors by the most popular subcloning strategies. Conclusion We present a complete description of Gene Composer functionality, and an efficient PCR-based synthetic gene assembly procedure with mis-match specific endonuclease error correction in combination with PIPE cloning. In a sister manuscript we present data on how Gene Composer designed genes and protein constructs can result in improved protein production for structural studies.
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Affiliation(s)
- Don Lorimer
- deCODE biostructures, Inc 7869 NE Day Road West, Bainbridge Island, WA 98110, USA.
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20
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Hughes SR, Dowd PF, Hector RE, Panavas T, Sterner DE, Qureshi N, Bischoff KM, Bang SS, Mertens JA, Johnson ET, Li XL, Jackson JS, Caughey RJ, Riedmuller SB, Bartolett S, Liu S, Rich JO, Farrelly PJ, Butt TR, Labaer J, Cotta MA. Lycotoxin-1 insecticidal peptide optimized by amino acid scanning mutagenesis and expressed as a coproduct in an ethanologenic Saccharomyces cerevisiae strain. J Pept Sci 2008; 14:1039-50. [PMID: 18465835 DOI: 10.1002/psc.1040] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
New methods of safe biological pest control are required as a result of evolution of insect resistance to current biopesticides. Yeast strains being developed for conversion of cellulosic biomass to ethanol are potential host systems for expression of commercially valuable peptides, such as bioinsecticides, to increase the cost-effectiveness of the process. Spider venom is one of many potential sources of novel insect-specific peptide toxins. Libraries of mutants of the small amphipathic peptide lycotoxin-1 from the wolf spider were produced in high throughput using an automated integrated plasmid-based functional proteomic platform and screened for ability to kill fall armyworms, a significant cause of damage to corn (maize) and other crops in the United States. Using amino acid scanning mutagenesis (AASM) we generated a library of mutagenized lycotoxin-1 open reading frames (ORF) in a novel small ubiquitin-like modifier (SUMO) yeast expression system. The SUMO technology enhanced expression and improved generation of active lycotoxins. The mutants were engineered to be expressed at high level inside the yeast and ingested by the insect before being cleaved to the active form (so-called Trojan horse strategy). These yeast strains expressing mutant toxin ORFs were also carrying the xylose isomerase (XI) gene and were capable of aerobic growth on xylose. Yeast cultures expressing the peptide toxins were prepared and fed to armyworm larvae to identify the mutant toxins with greatest lethality. The most lethal mutations appeared to increase the ability of the toxin alpha-helix to interact with insect cell membranes or to increase its pore-forming ability, leading to cell lysis. The toxin peptides have potential as value-added coproducts to increase the cost-effectiveness of fuel ethanol bioproduction.
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Affiliation(s)
- Stephen R Hughes
- United States Department of Agriculture, Agricultural Research Service, National Center for Agricultural Utilization Research, Bioproducts and Biocatalysis Research Unit, Peoria, IL 61604, USA.
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21
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Dieteren CEJ, Willems PHGM, Vogel RO, Swarts HG, Fransen J, Roepman R, Crienen G, Smeitink JAM, Nijtmans LGJ, Koopman WJH. Subunits of mitochondrial complex I exist as part of matrix- and membrane-associated subcomplexes in living cells. J Biol Chem 2008; 283:34753-61. [PMID: 18826940 PMCID: PMC3259887 DOI: 10.1074/jbc.m807323200] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2008] [Indexed: 01/25/2023] Open
Abstract
Mitochondrial complex I (CI) is a large assembly of 45 different subunits, and defects in its biogenesis are the most frequent cause of mitochondrial disorders. In vitro evidence suggests a stepwise assembly process involving pre-assembled modules. However, whether these modules also exist in vivo is as yet unresolved. To answer this question, we here applied submitochondrial fluorescence recovery after photobleaching to HEK293 cells expressing 6 GFP-tagged subunits selected on the basis of current CI assembly models. We established that each subunit was partially present in a virtually immobile fraction, possibly representing the holo-enzyme. Four subunits (NDUFV1, NDUFV2, NDUFA2, and NDUFA12) were also present as highly mobile matrix-soluble monomers, whereas, in sharp contrast, the other two subunits (NDUFB6 and NDUFS3) were additionally present in a slowly mobile fraction. In the case of the integral membrane protein NDUFB6, this fraction most likely represented one or more membrane-bound subassemblies, whereas biochemical evidence suggested that for the NDUFS3 protein this fraction most probably corresponded to a matrix-soluble subassembly. Our results provide first time evidence for the existence of CI subassemblies in mitochondria of living cells.
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Affiliation(s)
- Cindy E. J. Dieteren
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Peter H. G. M. Willems
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Rutger O. Vogel
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Herman G. Swarts
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Jack Fransen
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Ronald Roepman
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Gijs Crienen
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Jan A. M. Smeitink
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Leo G. J. Nijtmans
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
| | - Werner J. H. Koopman
- Departments of Biochemistry,
Cell Biology, and Human
Genetics, and the Microscopical Imaging Centre
of the Nijmegen Centre for Molecular Life Sciences, the Department of
Pediatrics of the Nijmegen Centre for
Mitochondrial Disorders, Radboud University Nijmegen Medical Centre, 6500 HB,
Nijmegen, The Netherlands
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22
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Engineered Saccharomyces cerevisiae strain for improved xylose utilization with a three-plasmid SUMO yeast expression system. Plasmid 2008; 61:22-38. [PMID: 18831987 DOI: 10.1016/j.plasmid.2008.09.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2008] [Revised: 09/02/2008] [Accepted: 09/02/2008] [Indexed: 12/18/2022]
Abstract
A three-plasmid yeast expression system utilizing the portable small ubiquitin-like modifier (SUMO) vector set combined with the efficient endogenous yeast protease Ulp1 was developed for production of large amounts of soluble functional protein in Saccharomyces cerevisiae. Each vector has a different selectable marker (URA, TRP, or LEU), and the system provides high expression levels of three different proteins simultaneously. This system was integrated into the protocols on a fully automated plasmid-based robotic platform to screen engineered strains of S. cerevisiae for improved growth on xylose. First, a novel PCR assembly strategy was used to clone a xylose isomerase (XI) gene into the URA-selectable SUMO vector and the plasmid was placed into the S. cerevisiae INVSc1 strain to give the strain designated INVSc1-XI. Second, amino acid scanning mutagenesis was used to generate a library of mutagenized genes encoding the bioinsecticidal peptide lycotoxin-1 (Lyt-1) and the library was cloned into the TRP-selectable SUMO vector and placed into INVSc1-XI to give the strain designated INVSc1-XI-Lyt-1. Third, the Yersinia pestis xylulokinase gene was cloned into the LEU-selectable SUMO vector and placed into the INVSc1-XI-Lyt-1 yeast. Yeast strains expressing XI and xylulokinase with or without Lyt-1 showed improved growth on xylose compared to INVSc1-XI yeast.
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23
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Ramachandran N, Srivastava S, Labaer J. Applications of protein microarrays for biomarker discovery. Proteomics Clin Appl 2008; 2:1444-59. [PMID: 21136793 DOI: 10.1002/prca.200800032] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2008] [Indexed: 01/18/2023]
Abstract
The search for new biomarkers for diagnosis, prognosis, and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large-scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers.
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Affiliation(s)
- Niroshan Ramachandran
- Harvard Institute of Proteomics, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Cambridge, MA, USA
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24
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Marina O, Biernacki MA, Brusic V, Wu CJ. A concentration-dependent analysis method for high density protein microarrays. J Proteome Res 2008; 7:2059-68. [PMID: 18393456 DOI: 10.1021/pr700892h] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Protein microarray technology is rapidly growing and has the potential to accelerate the discovery of targets of serum antibody responses in cancer, autoimmunity and infectious disease. Analytical tools for interpreting this high-throughput array data, however, are not well-established. We developed a concentration-dependent analysis (CDA) method which normalizes protein microarray data based on the concentration of spotted probes. We show that this analysis samples a data space that is complementary to other commonly employed analyses, and demonstrate experimental validation of 92% of hits identified by the intersection of CDA with other tools. These data support the use of CDA either as a preprocessing step for a more complete proteomic microarray data analysis or as a stand-alone analysis method.
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Affiliation(s)
- Ovidiu Marina
- Cancer Vaccine Center and Division of Hematologic Neoplasia, Dana-Farber Cancer Institute, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard Institutes of Medicine, Boston, MA 02115, USA
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25
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Slagowski NL, Kramer RW, Morrison MF, LaBaer J, Lesser CF. A functional genomic yeast screen to identify pathogenic bacterial proteins. PLoS Pathog 2008; 4:e9. [PMID: 18208325 PMCID: PMC2211553 DOI: 10.1371/journal.ppat.0040009] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2007] [Accepted: 12/10/2007] [Indexed: 11/19/2022] Open
Abstract
Many bacterial pathogens promote infection and cause disease by directly injecting into host cells proteins that manipulate eukaryotic cellular processes. Identification of these translocated proteins is essential to understanding pathogenesis. Yet, their identification remains limited. This, in part, is due to their general sequence uniqueness, which confounds homology-based identification by comparative genomic methods. In addition, their absence often does not result in phenotypes in virulence assays limiting functional genetic screens. Translocated proteins have been observed to confer toxic phenotypes when expressed in the yeast Saccharomyces cerevisiae. This observation suggests that yeast growth inhibition can be used as an indicator of protein translocation in functional genomic screens. However, limited information is available regarding the behavior of non-translocated proteins in yeast. We developed a semi-automated quantitative assay to monitor the growth of hundreds of yeast strains in parallel. We observed that expression of half of the 19 Shigella translocated proteins tested but almost none of the 20 non-translocated Shigella proteins nor ∼1,000 Francisella tularensis proteins significantly inhibited yeast growth. Not only does this study establish that yeast growth inhibition is a sensitive and specific indicator of translocated proteins, but we also identified a new substrate of the Shigella type III secretion system (TTSS), IpaJ, previously missed by other experimental approaches. In those cases where the mechanisms of action of the translocated proteins are known, significant yeast growth inhibition correlated with the targeting of conserved cellular processes. By providing positive rather than negative indication of activity our assay complements existing approaches for identification of translocated proteins. In addition, because this assay only requires genomic DNA it is particularly valuable for studying pathogens that are difficult to genetically manipulate or dangerous to culture. Many bacterial pathogens promote infection and ultimately cause disease, in part, through the actions of proteins that the bacteria directly inject into host cells. These proteins subvert host cell processes to favor survival of the pathogen. The identification of such proteins can be limited since many of the injected proteins lack homology with other virulence proteins and pathogens that no longer express the proteins are often unimpaired in conventional assays of pathogenesis. Many of these proteins target cellular processes conserved from mammals to yeast, and overexpression of these proteins in yeast results in growth inhibition. We have established a high throughput growth assay amenable to systematically screening open reading frames from bacterial pathogens for those that inhibit yeast growth. We observe that yeast growth inhibition is a sensitive and specific indicator of proteins that are injected into host cells. Expression of about half of the injected bacterial proteins but almost none of the bacteria-confined proteins results in yeast growth inhibition. Since this assay only requires genomic DNA it is particularly valuable for studying pathogens that are difficult to genetically manipulate or dangerous to grow in the laboratory.
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Affiliation(s)
- Naomi L Slagowski
- Department of Medicine, Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Roger W Kramer
- Department of Medicine, Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Monica F Morrison
- Department of Medicine, Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Joshua LaBaer
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Cammie F Lesser
- Department of Medicine, Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Cambridge, Massachusetts, United States of America
- * To whom correspondence should be addressed. E-mail:
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A novel approach to sequence validating protein expression clones with automated decision making. BMC Bioinformatics 2007; 8:198. [PMID: 17567908 PMCID: PMC1914086 DOI: 10.1186/1471-2105-8-198] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2007] [Accepted: 06/13/2007] [Indexed: 02/02/2023] Open
Abstract
Background Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation. Results We have developed an Automated Clone Evaluation (ACE) system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set. Conclusion ACE was designed to facilitate high throughput clone sequence verification projects. The software has been used successfully to evaluate more than 55,000 clones at the Harvard Institute of Proteomics. The software dramatically reduced the amount of time and labor required to evaluate clone sequences and decreased the number of missed sequence discrepancies, which commonly occur during manual evaluation. In addition, ACE helped to reduce the number of sequencing reads needed to achieve adequate coverage for making decisions on clones.
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Hu Y, Rolfs A, Bhullar B, Murthy TVS, Zhu C, Berger MF, Camargo AA, Kelley F, McCarron S, Jepson D, Richardson A, Raphael J, Moreira D, Taycher E, Zuo D, Mohr S, Kane MF, Williamson J, Simpson A, Bulyk ML, Harlow E, Marsischky G, Kolodner RD, LaBaer J. Approaching a complete repository of sequence-verified protein-encoding clones for Saccharomyces cerevisiae. Genes Dev 2007; 17:536-43. [PMID: 17322287 PMCID: PMC1832101 DOI: 10.1101/gr.6037607] [Citation(s) in RCA: 85] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2006] [Accepted: 01/03/2007] [Indexed: 01/21/2023]
Abstract
The availability of an annotated genome sequence for the yeast Saccharomyces cerevisiae has made possible the proteome-scale study of protein function and protein-protein interactions. These studies rely on availability of cloned open reading frame (ORF) collections that can be used for cell-free or cell-based protein expression. Several yeast ORF collections are available, but their use and data interpretation can be hindered by reliance on now out-of-date annotations, the inflexible presence of N- or C-terminal tags, and/or the unknown presence of mutations introduced during the cloning process. High-throughput biochemical and genetic analyses would benefit from a "gold standard" (fully sequence-verified, high-quality) ORF collection, which allows for high confidence in and reproducibility of experimental results. Here, we describe Yeast FLEXGene, a S. cerevisiae protein-coding clone collection that covers over 5000 predicted protein-coding sequences. The clone set covers 87% of the current S. cerevisiae genome annotation and includes full sequencing of each ORF insert. Availability of this collection makes possible a wide variety of studies from purified proteins to mutation suppression analysis, which should contribute to a global understanding of yeast protein function.
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Affiliation(s)
- Yanhui Hu
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Andreas Rolfs
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Bhupinder Bhullar
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Tellamraju V. S. Murthy
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Cong Zhu
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Masschusetts 02115, USA
| | - Michael F. Berger
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Masschusetts 02115, USA
- Harvard University Graduate Biophysics Program, Cambridge, Massachusetts 02138, USA
| | | | - Fontina Kelley
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Seamus McCarron
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Daniel Jepson
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Aaron Richardson
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Jacob Raphael
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Donna Moreira
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Elena Taycher
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Dongmei Zuo
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Stephanie Mohr
- DF/HCC DNA Resource Core, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Michael F. Kane
- Ludwig Institute for Cancer Research, University of California San Diego, School of Medicine, La Jolla, California 92093, USA
| | - Janice Williamson
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Andrew Simpson
- Ludwig Institute for Cancer Research, New York, New York 10158, USA
| | - Martha L. Bulyk
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital, Harvard Medical School, Boston, Masschusetts 02115, USA
- Harvard University Graduate Biophysics Program, Cambridge, Massachusetts 02138, USA
- Department of Pathology, Brigham & Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Harvard-MIT Division of Health Sciences & Technology (HST), Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Edward Harlow
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Gerald Marsischky
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
| | - Richard D. Kolodner
- Ludwig Institute for Cancer Research, University of California San Diego, School of Medicine, La Jolla, California 92093, USA
| | - Joshua LaBaer
- Harvard Institute of Proteomics, Harvard Medical School, Cambridge, Massachusetts 02141, USA
- DF/HCC DNA Resource Core, Harvard Medical School, Cambridge, Massachusetts 02141, USA
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