1
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Apostol AJ, Bragagnolo NJ, Rodriguez CS, Audette GF. Structural insights into the disulfide isomerase and chaperone activity of TrbB of the F plasmid type IV secretion system. Curr Res Struct Biol 2024; 8:100156. [PMID: 39131116 PMCID: PMC11315126 DOI: 10.1016/j.crstbi.2024.100156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 06/07/2024] [Accepted: 07/10/2024] [Indexed: 08/13/2024] Open
Abstract
Bacteria have evolved elaborate mechanisms to thrive in stressful environments. F-like plasmids in gram-negative bacteria encode for a multi-protein Type IV Secretion System (T4SSF) that is functional for bacterial proliferation and adaptation through the process of conjugation. The periplasmic protein TrbB is believed to have a stabilizing chaperone role in the T4SSF assembly, with TrbB exhibiting disulfide isomerase (DI) activity. In the current report, we demonstrate that the deletion of the disordered N-terminus of TrbBWT, resulting in a truncation construct TrbB37-161, does not affect its catalytic in vitro activity compared to the wild-type protein (p = 0.76). Residues W37-K161, which include the active thioredoxin motif, are sufficient for DI activity. The N-terminus of TrbBWT is disordered as indicated by a structural model of GST-TrbBWT based on ColabFold-AlphaFold2 and Small Angle X-Ray Scattering data and 1H-15N Heteronuclear Single Quantum Correlation (HSQC) spectroscopy of the untagged protein. This disordered region likely contributes to the protein's dynamicity; removal of this region results in a more stable protein based on 1H-15N HSQC and Circular Dichroism Spectroscopies. Lastly, size exclusion chromatography analysis of TrbBWT in the presence of TraW, a T4SSF assembly protein predicted to interact with TrbBWT, does not support the inference of a stable complex forming in vitro. This work advances our understanding of TrbB's structure and function, explores the role of structural disorder in protein dynamics in the context of a T4SSF accessory protein, and highlights the importance of redox-assisted protein folding in the T4SSF.
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Affiliation(s)
- Arnold J. Apostol
- Department of Chemistry, York University, 4700 Keele St, Toronto, ON, Canada, M3J 1P3
- Centre for Research on Biomolecular Interactions, York University, Canada
| | - Nicholas J. Bragagnolo
- Department of Chemistry, York University, 4700 Keele St, Toronto, ON, Canada, M3J 1P3
- Centre for Research on Biomolecular Interactions, York University, Canada
| | - Christina S. Rodriguez
- Department of Chemistry, York University, 4700 Keele St, Toronto, ON, Canada, M3J 1P3
- Centre for Research on Biomolecular Interactions, York University, Canada
| | - Gerald F. Audette
- Department of Chemistry, York University, 4700 Keele St, Toronto, ON, Canada, M3J 1P3
- Centre for Research on Biomolecular Interactions, York University, Canada
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2
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Liu X, Zhang L, Zhang Y, Vakharia VN, Zhang X, Lv X, Sun W. Screening of genes encoding proteins that interact with ISG15: Probing a cDNA library from a snakehead fish cell line using a yeast two-hybrid system. FISH & SHELLFISH IMMUNOLOGY 2022; 128:300-306. [PMID: 35921933 DOI: 10.1016/j.fsi.2022.07.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/20/2022] [Accepted: 07/24/2022] [Indexed: 06/15/2023]
Abstract
Interferon-stimulated gene 15 (ISG15) regulates cellular life processes, including defense responses against infection by a variety of viral pathogens, by binding to target proteins. At present, various fish ISG15s have been identified, but the biological function of ISG15 in snakehead fish is still unclear. In this study, total RNA was extracted from snakehead fish cell line E11, ds cDNA was synthesized and purified using SMART technology, and the resulting cDNA library was screened by co-transforming yeast cells. The library titer was 4.28 × 109 CFU/mL. Using snakehead ISG15 as the bait protein, the recombinant bait vector pGBKT7-ISG15 was constructed and transformed into the yeast strain Y2HGold. The toxicity and self-activation activity of the bait vector were detected on the deficient medium, and the prey proteins interacting with ISG15 were screened. In total, 19 interacting proteins of ISG15 were identified, including mitotic checkpoint protein BUB3, hypothetical protein SnRVgp6, elongation factor 1-beta, 60S ribosomal protein L9, dual specificity protein phosphatase 5-like, eukaryotic translation initiation factor 3 subunit I and ferritin. A yeast spotting assay further probed the interaction between ISG15 and DUSP5. These results increase our understanding of the interaction network of snakehead ISG15 and will aid in exploring the underlying mechanisms of snakehead ISG15 functions in the future.
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Affiliation(s)
- Xiaodan Liu
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China.
| | - Liwen Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Yanbing Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Vikram N Vakharia
- Institute of Marine and Environmental Technology, University of Maryland Baltimore Country, Baltimore, MD, 21202, USA
| | - Xiaojun Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China
| | - Xiaoyang Lv
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China; Jiangsu Co-innovation Center for Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, China
| | - Wei Sun
- College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009, China; Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China; Jiangsu Co-innovation Center for Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, China.
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3
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Walch P, Selkrig J, Knodler LA, Rettel M, Stein F, Fernandez K, Viéitez C, Potel CM, Scholzen K, Geyer M, Rottner K, Steele-Mortimer O, Savitski MM, Holden DW, Typas A. Global mapping of Salmonella enterica-host protein-protein interactions during infection. Cell Host Microbe 2021; 29:1316-1332.e12. [PMID: 34237247 PMCID: PMC8561747 DOI: 10.1016/j.chom.2021.06.004] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 02/24/2021] [Accepted: 05/21/2021] [Indexed: 11/16/2022]
Abstract
Intracellular bacterial pathogens inject effector proteins to hijack host cellular processes and promote their survival and proliferation. To systematically map effector-host protein-protein interactions (PPIs) during infection, we generated a library of 32 Salmonella enterica serovar Typhimurium (STm) strains expressing chromosomally encoded affinity-tagged effectors and quantified PPIs in macrophages and epithelial cells. We identified 446 effector-host PPIs, 25 of which were previously described, and validated 13 by reciprocal co-immunoprecipitation. While effectors converged on the same host cellular processes, most had multiple targets, which often differed between cell types. We demonstrate that SseJ, SseL, and SifA modulate cholesterol accumulation at the Salmonella-containing vacuole (SCV) partially via the cholesterol transporter Niemann-Pick C1 protein. PipB recruits the organelle contact site protein PDZD8 to the SCV, and SteC promotes actin bundling by phosphorylating formin-like proteins. This study provides a method for probing host-pathogen PPIs during infection and a resource for interrogating STm effector mechanisms.
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Affiliation(s)
- Philipp Walch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany; Heidelberg University, Faculty of Biosciences, Heidelberg, Germany
| | - Joel Selkrig
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Leigh A Knodler
- Paul G. Allen School for Global Health, College of Veterinary Medicine, Washington State University, Pullman, USA; Laboratory of Intracellular Parasites, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Mandy Rettel
- EMBL, Proteomics Core Facility, Heidelberg, Germany
| | - Frank Stein
- EMBL, Proteomics Core Facility, Heidelberg, Germany
| | - Keith Fernandez
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Cristina Viéitez
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany; EMBL European Bioinformatics Institute, (EMBL-EBI), Hinxton, UK
| | - Clément M Potel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Karoline Scholzen
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Matthias Geyer
- Institute of Structural Biology, University of Bonn, Bonn, Germany
| | - Klemens Rottner
- Division of Molecular Cell Biology, Zoological Institute, TU Braunschweig, Braunschweig, Germany; Molecular Cell Biology Group, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Olivia Steele-Mortimer
- Laboratory of Intracellular Parasites, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Mikhail M Savitski
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany; EMBL, Proteomics Core Facility, Heidelberg, Germany
| | - David W Holden
- MRC Centre for Molecular Bacteriology and Infection, Imperial College, London, UK
| | - Athanasios Typas
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
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4
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Porras P, Barrera E, Bridge A, Del-Toro N, Cesareni G, Duesbury M, Hermjakob H, Iannuccelli M, Jurisica I, Kotlyar M, Licata L, Lovering RC, Lynn DJ, Meldal B, Nanduri B, Paneerselvam K, Panni S, Pastrello C, Pellegrini M, Perfetto L, Rahimzadeh N, Ratan P, Ricard-Blum S, Salwinski L, Shirodkar G, Shrivastava A, Orchard S. Towards a unified open access dataset of molecular interactions. Nat Commun 2020; 11:6144. [PMID: 33262342 PMCID: PMC7708836 DOI: 10.1038/s41467-020-19942-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 11/09/2020] [Indexed: 12/16/2022] Open
Abstract
The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources.
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Affiliation(s)
- Pablo Porras
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Elisabet Barrera
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Alan Bridge
- SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire, 1 rue Michel Servet, CH-1211, Geneva, Switzerland
| | - Noemi Del-Toro
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Gianni Cesareni
- University of Rome Tor Vergata, Rome, Italy.,IRCCS Fondazione Santa Lucia, 00143, Rome, Italy
| | - Margaret Duesbury
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK.,UCLA-DOE Institute, University of California, Los Angeles, CA, 90095, USA
| | - Henning Hermjakob
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Igor Jurisica
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, and Krembil Research Institute, University Health Network, 60 Leonard Avenue, 5KD-407, Toronto, ON, M5T 0S8, Canada.,Departments of Medical Biophysics, and Computer Science, University of Toronto, Toronto, ON, Canada.,Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Max Kotlyar
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, and Krembil Research Institute, University Health Network, 60 Leonard Avenue, 5KD-407, Toronto, ON, M5T 0S8, Canada
| | | | - Ruth C Lovering
- Functional Gene Annotation, Preclinical and Fundamental Science, UCL Institute of Cardiovascular Science, University College London, London, WC1E 6JF, UK
| | - David J Lynn
- Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, SA, 5000, Australia.,College of Medicine and Public Health, Flinders University, Bedford Park, SA, 5042, Australia
| | - Birgit Meldal
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Bindu Nanduri
- Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, MS, USA
| | - Kalpana Paneerselvam
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Simona Panni
- Università della Calabria, Dipartimento di Biologia, Ecologia e Scienze della Terra, Via Pietro Bucci Cubo 6/C, Rende, CS, Italy
| | - Chiara Pastrello
- Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute, and Krembil Research Institute, University Health Network, 60 Leonard Avenue, 5KD-407, Toronto, ON, M5T 0S8, Canada
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, UCLA, Box 951606, Los Angeles, CA, 90095-1606, USA
| | - Livia Perfetto
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Negin Rahimzadeh
- UCLA-DOE Institute, University of California, Los Angeles, CA, 90095, USA
| | - Prashansa Ratan
- UCLA-DOE Institute, University of California, Los Angeles, CA, 90095, USA
| | - Sylvie Ricard-Blum
- ICBMS, UMR 5246 University Lyon 1 - CNRS, Univ. Lyon, 69622, Villeurbanne, France
| | - Lukasz Salwinski
- UCLA-DOE Institute, University of California, Los Angeles, CA, 90095, USA
| | - Gautam Shirodkar
- UCLA-DOE Institute, University of California, Los Angeles, CA, 90095, USA
| | - Anjalia Shrivastava
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK.,Open Targets, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Sandra Orchard
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Campus, Hinxton, Cambridge, CB10 1SD, UK.
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5
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Wu J, Mohamed D, Dowhanik S, Petrella R, Gregis V, Li J, Wu L, Gazzarrini S. Spatiotemporal Restriction of FUSCA3 Expression by Class I BPCs Promotes Ovule Development and Coordinates Embryo and Endosperm Growth. THE PLANT CELL 2020; 32:1886-1904. [PMID: 32265266 PMCID: PMC7268797 DOI: 10.1105/tpc.19.00764] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/10/2020] [Accepted: 04/03/2020] [Indexed: 05/06/2023]
Abstract
Spatiotemporal regulation of gene expression is critical for proper developmental timing in plants and animals. The transcription factor FUSCA3 (FUS3) regulates developmental phase transitions by acting as a link between hormonal pathways in Arabidopsis (Arabidopsis thaliana). However, the mechanisms governing its spatiotemporal expression pattern are poorly understood. Here, we show that FUS3 is repressed in the ovule integuments and seed endosperm. FUS3 repression requires class I BASIC PENTACYSTEINE (BPC) proteins, which directly bind GA/CT cis-elements in FUS3 and restrict its expression pattern. During vegetative and reproductive development, FUS3 derepression in bpc1-1 bpc2 (bpc1/2) double mutant or misexpression in ProML1:FUS3 lines causes dwarf plants carrying defective flowers and aborted ovules. After fertilization, ectopic FUS3 expression in bpc1/2 endosperm or ProML1:FUS3 endosperm and endothelium increases endosperm nuclei proliferation and seed size, causing delayed or arrested embryo development. These phenotypes are rescued in bpc1/2 fus3-3 Finally, class I BPCs interact with FIS-PRC2 (FERTILIZATION-INDEPENDENT SEED-Polycomb Repressive Complex2), which represses FUS3 in the endosperm during early seed development. We propose that BPC1 and 2 promote the transition from reproductive to seed development by repressing FUS3 in ovule integuments. After fertilization, BPC1 and 2 and FIS-PRC2 repress FUS3 in the endosperm to coordinate early endosperm and embryo growth.
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Affiliation(s)
- Jian Wu
- Beijing Key Laboratory of Development and Quality Control of Ornamental Crops, Department of Ornamental Horticulture and Landscape Architecture, China Agricultural University, Beijing 100193, China
- Department of Biological Sciences, University of Toronto Scarborough, Ontario M1C 1A4, Canada
| | - Deka Mohamed
- Department of Biological Sciences, University of Toronto Scarborough, Ontario M1C 1A4, Canada
- Department of Cell and Systems Biology, University of Toronto, Ontario M5S 3G5, Canada
| | - Sebastian Dowhanik
- Department of Biological Sciences, University of Toronto Scarborough, Ontario M1C 1A4, Canada
| | - Rosanna Petrella
- Dipartimento di Bioscienze, Università degli Studi di Milano, Via Celoria 26, 20133, Milano, Italy
| | - Veronica Gregis
- Dipartimento di Bioscienze, Università degli Studi di Milano, Via Celoria 26, 20133, Milano, Italy
| | - Jingru Li
- Beijing Key Laboratory of Development and Quality Control of Ornamental Crops, Department of Ornamental Horticulture and Landscape Architecture, China Agricultural University, Beijing 100193, China
| | - Lin Wu
- Department of Biological Sciences, University of Toronto Scarborough, Ontario M1C 1A4, Canada
- Chongqing Key Laboratory of Economic Plant Biotechnology, Institute of Special Plants, Chongqing University of Arts and Sciences, Yongchuan, Chongqing 402160, China
| | - Sonia Gazzarrini
- Department of Biological Sciences, University of Toronto Scarborough, Ontario M1C 1A4, Canada
- Department of Cell and Systems Biology, University of Toronto, Ontario M5S 3G5, Canada
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6
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Screening Arrayed Libraries with DNA and Protein Baits to Identify Interacting Proteins. Methods Mol Biol 2019; 1794:131-149. [PMID: 29855955 DOI: 10.1007/978-1-4939-7871-7_9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Molecular interactions are an integral part of the regulatory mechanisms controlling gene expression. The yeast one- and two-hybrid systems (Y1H/Y2H) have been widely used by many laboratories to detect DNA-protein (Y1H) and protein-protein interactions (Y2H). The development of efficient cloning systems have promoted the generation of large open reading frame (ORF) clone collections (libraries) for several organisms. Functional analyses of such large collections require the establishment of adequate protocols. Here, we describe a simple straightforward procedure for high-throughput screenings of arrayed libraries with DNA or protein baits that can be carried out by one person with minimal labor and not requiring robotics. The protocol can also be scaled up or down and is compatible with several library formats. Procedures to make yeast stocks for long-term storage (tube and microplate formats) are also provided.
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7
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Abstract
Comprehensive mapping of protein-DNA interactions is essential to uncover the mechanisms involved in gene regulation. However, the data generated has been sparse given the number of regulatory elements and transcription factors (TFs) encoded in the genomes of metazoan organisms. Yeast one-hybrid (Y1H) assays provide a powerful "DNA-centered" method, complementary to "TF-centered" methods such as chromatin immunoprecipitation, to identify the TFs that can bind a DNA sequence of interest. Here, we present different technical variations that should be considered when using a Y1H system, including the type of DNA sequence to test, source of TF clones, as well as types of vectors and screening format. Finally, we discuss limitations of the assay and future challenges.
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8
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Peterson TA, Stamnes MA, Piper RC. A Yeast 2-Hybrid Screen in Batch to Compare Protein Interactions. J Vis Exp 2018. [PMID: 29939176 DOI: 10.3791/57801] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Screening for protein-protein interactions using the yeast 2-hybrid assay has long been an effective tool, but its use has largely been limited to the discovery of high-affinity interactors that are highly enriched in the library of interacting candidates. In a traditional format, the yeast 2-hybrid assay can yield too many colonies to analyze when conducted at low stringency where low affinity interactors might be found. Moreover, without a comprehensive and complete interrogation of the same library against different bait plasmids, a comparative analysis cannot be achieved. Although some of these problems can be addressed using arrayed prey libraries, the cost and infrastructure required to operate such screens can be prohibitive. As an alternative, we have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing a strategy termed DEEPN (Dynamic Enrichment for Evaluation of Protein Networks), which incorporates high-throughput DNA sequencing and computation to follow the evolution of a population of plasmids that encode interacting partners. Here, we describe customized reagents and protocols that allow a DEEPN screen to be executed easily and cost-effectively.
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Affiliation(s)
| | | | - Robert C Piper
- Molecular Physiology and Biophysics, University of Iowa;
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9
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Abstract
Two-hybrid methods remain among the most preferred choices for detecting protein-protein interactions (PPIs) and much of the PPI data in databases have been produced using yeast two-hybrid (Y2H) screens. The Y2H methods are extensively used to detect PPIs because of their scalability and accessibility. Several variants of Y2H methods have been developed and used by different research groups, increasing the accessibility of these methods and their applications in detecting different types of PPIs. However, the availability of variations on the same core methodology emphasizes the need to have a systematic comparison of available Y2H methods in the context of their applicability, coverage and efficiency. In this chapter, we discuss the key parameters of Y2H methods, namely proteins of interest, vectors, libraries, screening strategies, data analysis, and provide a flowchart that should help to decide which Y2H strategy is most appropriate for a protein interaction screen.
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10
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Wallqvist A, Wang H, Zavaljevski N, Memišević V, Kwon K, Pieper R, Rajagopala SV, Reifman J. Mechanisms of action of Coxiella burnetii effectors inferred from host-pathogen protein interactions. PLoS One 2017; 12:e0188071. [PMID: 29176882 PMCID: PMC5703456 DOI: 10.1371/journal.pone.0188071] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/31/2017] [Indexed: 02/06/2023] Open
Abstract
Coxiella burnetii is an obligate Gram-negative intracellular pathogen and the etiological agent of Q fever. Successful infection requires a functional Type IV secretion system, which translocates more than 100 effector proteins into the host cytosol to establish the infection, restructure the intracellular host environment, and create a parasitophorous vacuole where the replicating bacteria reside. We used yeast two-hybrid (Y2H) screening of 33 selected C. burnetii effectors against whole genome human and murine proteome libraries to generate a map of potential host-pathogen protein-protein interactions (PPIs). We detected 273 unique interactions between 20 pathogen and 247 human proteins, and 157 between 17 pathogen and 137 murine proteins. We used orthology to combine the data and create a single host-pathogen interaction network containing 415 unique interactions between 25 C. burnetii and 363 human proteins. We further performed complementary pairwise Y2H testing of 43 out of 91 C. burnetii-human interactions involving five pathogen proteins. We used the combined data to 1) perform enrichment analyses of target host cellular processes and pathways, 2) examine effectors with known infection phenotypes, and 3) infer potential mechanisms of action for four effectors with uncharacterized functions. The host-pathogen interaction profiles supported known Coxiella phenotypes, such as adapting cell morphology through cytoskeletal re-arrangements, protein processing and trafficking, organelle generation, cholesterol processing, innate immune modulation, and interactions with the ubiquitin and proteasome pathways. The generated dataset of PPIs-the largest collection of unbiased Coxiella host-pathogen interactions to date-represents a rich source of information with respect to secreted pathogen effector proteins and their interactions with human host proteins.
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Affiliation(s)
- Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Hao Wang
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Nela Zavaljevski
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Vesna Memišević
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
| | - Keehwan Kwon
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | - Rembert Pieper
- J. Craig Venter Institute, Rockville, Maryland, United States of America
| | | | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, United States of America
- * E-mail:
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11
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Mehla J, Caufield JH, Sakhawalkar N, Uetz P. A Comparison of Two-Hybrid Approaches for Detecting Protein-Protein Interactions. Methods Enzymol 2017; 586:333-358. [PMID: 28137570 DOI: 10.1016/bs.mie.2016.10.020] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Two-hybrid systems are one of the most popular, preferred, cost effective, and scalable in vivo genetic approaches for screening protein-protein interactions. A number of variants of yeast and bacterial two-hybrid systems exist, rendering them ideal for modern, flexible proteomics-driven studies. For mapping protein interactions at genome scales (that is, constructing an interactome), the yeast two-hybrid system has been extensively tested and is preferred over bacterial two-hybrid systems, given that users have created more resources such as a variety of vectors and other modifications. Each system has its own advantages and limitations and thus needs to be compared directly. For instance, the bacterial two-hybrid method seems a better fit than the yeast two-hybrid system to screen membrane-associated proteins. In this chapter, we provide detailed protocols for yeast and bacterial two-hybrid systems as well as a comparison of outcomes for each approach using our own and published data.
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Affiliation(s)
- J Mehla
- Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA, United States.
| | - J H Caufield
- Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA, United States
| | - N Sakhawalkar
- Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA, United States
| | - P Uetz
- Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, VA, United States.
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12
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Sánchez-Montesino R, Oñate-Sánchez L. Yeast One- and Two-Hybrid High-Throughput Screenings Using Arrayed Libraries. Methods Mol Biol 2017. [PMID: 28623579 DOI: 10.1007/978-1-4939-7125-1_5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Since their original description more than 25 years ago, the yeast one- and two-hybrid systems (Y1H/Y2H) have been used by many laboratories to detect DNA-protein (Y1H) and protein-protein interactions (Y2H). These systems use yeast cells (Saccharomyces cerevisiae) as a eukaryotic "test tube" and are amenable for most labs in the world. The development of highly efficient cloning methods has fostered the generation of large collections of open reading frames (ORFs) for several organisms that have been used for yeast screenings. Here, we describe a simple mating based method for high-throughput screenings of arrayed ORF libraries with DNA (Y1H) or protein (Y2H) baits not requiring robotics. One person can easily carry out this protocol in approximately 10 h of labor spread over 5 days. It can also be scaled down to test one-to-one (few) interactions, scaled up (i.e., robotization) and is compatible with several library formats (i.e., 96, 384-well microtiter plates).
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Affiliation(s)
- Rocío Sánchez-Montesino
- Centro de Biotecnología y Genómica de Plantas (UPM-INIA), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, 28223, Madrid, Spain
| | - Luis Oñate-Sánchez
- Centro de Biotecnología y Genómica de Plantas (UPM-INIA), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, 28223, Madrid, Spain.
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Mazur MJ, Spears BJ, Djajasaputra A, van der Gragt M, Vlachakis G, Beerens B, Gassmann W, van den Burg HA. Arabidopsis TCP Transcription Factors Interact with the SUMO Conjugating Machinery in Nuclear Foci. FRONTIERS IN PLANT SCIENCE 2017; 8:2043. [PMID: 29250092 PMCID: PMC5714883 DOI: 10.3389/fpls.2017.02043] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Accepted: 11/15/2017] [Indexed: 05/20/2023]
Abstract
In Arabidopsis more than 400 proteins have been identified as SUMO targets, both in vivo and in vitro. Among others, transcription factors (TFs) are common targets for SUMO conjugation. Here we aimed to exhaustively screen for TFs that interact with the SUMO machinery using an arrayed yeast two-hybrid library containing more than 1,100 TFs. We identified 76 interactors that foremost interact with the SUMO conjugation enzyme SCE1 and/or the SUMO E3 ligase SIZ1. These interactors belong to various TF families, which control a wide range of processes in plant development and stress signaling. Amongst these interactors, the TCP family was overrepresented with several TCPs interacting with different proteins of the SUMO conjugation cycle. For a subset of these TCPs we confirmed that the catalytic site of SCE1 is essential for this interaction. In agreement, TCP1, TCP3, TCP8, TCP14, and TCP15 were readily SUMO modified in an E. coli sumoylation assay. Strikingly, these TCP-SCE1 interactions were found to redistribute these TCPs into nuclear foci/speckles, suggesting that these TCP foci represent sites for SUMO (conjugation) activity.
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Affiliation(s)
- Magdalena J. Mazur
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Benjamin J. Spears
- Division of Plant Sciences, C.S. Bond Life Sciences Center and Interdisciplinary Plant Group, University of Missouri, Columbia, SC, United States
| | - André Djajasaputra
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Michelle van der Gragt
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Georgios Vlachakis
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Bas Beerens
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Walter Gassmann
- Division of Plant Sciences, C.S. Bond Life Sciences Center and Interdisciplinary Plant Group, University of Missouri, Columbia, SC, United States
| | - Harrold A. van den Burg
- Molecular Plant Pathology, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
- *Correspondence: Harrold A. van den Burg
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Scribano D, Damico R, Ambrosi C, Superti F, Marazzato M, Conte MP, Longhi C, Palamara AT, Zagaglia C, Nicoletti M. The Shigella flexneri OmpA amino acid residues 188EVQ 190 are essential for the interaction with the virulence factor PhoN2. Biochem Biophys Rep 2016; 8:168-173. [PMID: 28955953 PMCID: PMC5613738 DOI: 10.1016/j.bbrep.2016.08.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Revised: 07/27/2016] [Accepted: 08/01/2016] [Indexed: 01/07/2023] Open
Abstract
Shigella flexneri is an intracellular pathogen that deploys an arsenal of virulence factors promoting host cell invasion, intracellular multiplication and intra- and inter-cellular dissemination. We have previously reported that the interaction between apyrase (PhoN2), a periplasmic ATP-diphosphohydrolase, and the C-terminal domain of the outer membrane (OM) protein OmpA is likely required for proper IcsA exposition at the old bacterial pole and thus for full virulence expression of Shigella flexneri (Scribano et al., 2014). OmpA, that is the major OM protein of Gram-negative bacteria, is a multifaceted protein that plays many different roles both in the OM structural integrity and in the virulence of several pathogens. Here, by using yeast two-hybrid technology and by constructing an in silico 3D model of OmpA from S. flexneri 5a strain M90T, we observed that the OmpA residues 188EVQ190 are likely essential for PhoN2-OmpA interaction. The 188EVQ190 amino acids are located within a flexible region of the OmpA protein that could represent a scaffold for protein-protein interaction.
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Affiliation(s)
- Daniela Scribano
- Dip. Scienze Mediche, Orali e Biotecnologiche, Università "G. D'Annunzio" di Chieti, Chieti, Italy.,Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Rosanna Damico
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Cecilia Ambrosi
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Fabiana Superti
- Reparto Patologia Infettiva Ultrastrutturale, Dipartimento di Tecnologie e Salute, Istituto Superiore di Sanità, Rome, Italy
| | - Massimiliano Marazzato
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Maria Pia Conte
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Catia Longhi
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Anna Teresa Palamara
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Carlo Zagaglia
- Dip. di Sanità Pubblica e Malattie Infettive, Università "Sapienza" di Roma, Rome, Italy
| | - Mauro Nicoletti
- Dip. Scienze Mediche, Orali e Biotecnologiche, Università "G. D'Annunzio" di Chieti, Chieti, Italy
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Krogan, PhD NJ, Babu, PhD M. Mapping the Protein-Protein Interactome Networks Using Yeast Two-Hybrid Screens. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2015; 883:187-214. [PMID: 26621469 PMCID: PMC7120425 DOI: 10.1007/978-3-319-23603-2_11] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The yeast two-hybrid system (Y2H) is a powerful method to identify binary protein-protein interactions in vivo. Here we describe Y2H screening strategies that use defined libraries of open reading frames (ORFs) and cDNA libraries. The array-based Y2H system is well suited for interactome studies of small genomes with an existing ORFeome clones preferentially in a recombination based cloning system. For large genomes, pooled library screening followed by Y2H pairwise retests may be more efficient in terms of time and resources, but multiple sampling is necessary to ensure comprehensive screening. While the Y2H false positives can be efficiently reduced by using built-in controls, retesting, and evaluation of background activation; implementing the multiple variants of the Y2H vector systems is essential to reduce the false negatives and ensure comprehensive coverage of an interactome.
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Affiliation(s)
- Nevan J. Krogan, PhD
- grid.266102.10000000122976811Cellular and Molecular Pharmacology, Univ of California, San Francisco, SAN FRANCISCO, California USA
| | - Mohan Babu, PhD
- grid.57926.3f0000000419369131Department of Biochemistry, University of Regina, Regina, Saskatchewan Canada
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Abstract
As a large, nonmembrane bound organelle, the centrosome must rely heavily on protein-protein interactions to assemble itself in the cytoplasm and perform its functions as a microtubule-organizing center. Therefore, to understand how this organelle is built and functions, one must understand the protein-protein interactions made by each centrosome protein. Unfortunately, the highly interconnected nature of the centrosome, combined with its predicted unstructured, coil-rich proteins, has made the use of many standard approaches to studying protein-protein interactions very challenging. The yeast-two hybrid (Y2H) system is well suited for studying the centrosome and is an important complement to other biochemical approaches. In this chapter we describe how to carry out a directed Y2H screen to identify the direct interactions between a given centrosome protein and a library of others. Specifically, we detail using a bioinformatics-based approach (structure prediction programs) to subdivide proteins and screen for interactions using an array-based Y2H approach. We also describe how to use the interaction information garnered from this screen to generate mutations to disrupt specific interactions using mutagenic-PCR and a "reverse" Y2H screen. Finally, we discuss how information from such a screen can be integrated into existing models of centrosome assembly and how it can initiate and guide extensive in vitro and in vivo experimentation to test these models.
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Abstract
ABSTRACT Bacterial ParA and ParB proteins are best known for their contribution to plasmid and chromosome segregation, but they may also contribute to other cell functions. In segregation, ParA interacts with ParB, which binds to parS centromere-analogous sites. In transcription, plasmid Par proteins can serve as repressors by specifically binding to their own promoters and, additionally, in the case of ParB, by spreading from a parS site to nearby promoters. Here, we have asked whether chromosomal Par proteins can likewise control transcription. Analysis of genome-wide ParB1 binding in Vibrio cholerae revealed preferential binding to the three known parS1 sites and limited spreading of ParB1 beyond the parS1 sites. Comparison of wild-type transcriptomes with those of ΔparA1, ΔparB1, and ΔparAB1 mutants revealed that two out of 20 genes (VC0067 and VC0069) covered by ParB1 spreading are repressed by both ParB1 and ParA1. A third gene (VC0076) at the outskirts of the spreading area and a few genes further away were also repressed, particularly the gene for an outer membrane protein, ompU (VC0633). Since ParA1 or ParB1 binding was not evident near VC0076 and ompU genes, the repression may require participation of additional factors. Indeed, both ParA1 and ParB1 proteins were found to interact with several V. cholerae proteins in bacterial and yeast two-hybrid screens. These studies demonstrate that chromosomal Par proteins can repress genes unlinked to parS and can do so without direct binding to the cognate promoter DNA. IMPORTANCE Directed segregation of chromosomes is essential for their maintenance in dividing cells. Many bacteria have genes (par) that were thought to be dedicated to segregation based on analogy to their roles in plasmid maintenance. It is becoming clear that chromosomal par genes are pleiotropic and that they contribute to diverse processes such as DNA replication, cell division, cell growth, and motility. One way to explain the pleiotropy is to suggest that Par proteins serve as or control other transcription factors. We tested this model by determining how Par proteins affect genome-wide transcription activity. We found that genes implicated in drug resistance, stress response, and pathogenesis were repressed by Par. Unexpectedly, the repression did not involve direct Par binding to cognate promoter DNA, indicating that the repression may involve Par interactions with other regulators. This pleiotropy highlights the degree of integration of chromosomal Par proteins into cellular control circuitries.
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Häuser R, Ceol A, Rajagopala SV, Mosca R, Siszler G, Wermke N, Sikorski P, Schwarz F, Schick M, Wuchty S, Aloy P, Uetz P. A second-generation protein-protein interaction network of Helicobacter pylori. Mol Cell Proteomics 2014; 13:1318-29. [PMID: 24627523 DOI: 10.1074/mcp.o113.033571] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.
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Affiliation(s)
- Roman Häuser
- German Cancer Research Center (Deutsches Krebsforschungszentrum), Technologiepark 3, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
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Feala JD, Abdulhameed MDM, Yu C, Dutta B, Yu X, Schmid K, Dave J, Tortella F, Reifman J. Systems biology approaches for discovering biomarkers for traumatic brain injury. J Neurotrauma 2014; 30:1101-16. [PMID: 23510232 DOI: 10.1089/neu.2012.2631] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates.
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Affiliation(s)
- Jacob D Feala
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland, USA
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21
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Blasche S, Wuchty S, Rajagopala SV, Uetz P. The protein interaction network of bacteriophage lambda with its host, Escherichia coli. J Virol 2013; 87:12745-55. [PMID: 24049175 PMCID: PMC3838138 DOI: 10.1128/jvi.02495-13] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2013] [Accepted: 09/10/2013] [Indexed: 11/20/2022] Open
Abstract
Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens.
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Affiliation(s)
- Sonja Blasche
- Genomics and Proteomics Core Facilities, German Cancer Research Center, Heidelberg, Germany
| | - Stefan Wuchty
- National Center of Biotechnology Information, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Peter Uetz
- Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, USA
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Wang X, Schröder HC, Schloßmacher U, Jiang L, Korzhev M, Müller WE. Biosilica aging: From enzyme-driven gelation via syneresis to chemical/biochemical hardening. Biochim Biophys Acta Gen Subj 2013; 1830:3437-46. [DOI: 10.1016/j.bbagen.2013.02.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2012] [Revised: 02/02/2013] [Accepted: 02/05/2013] [Indexed: 11/26/2022]
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Jin Y, Turaev D, Weinmaier T, Rattei T, Makse HA. The evolutionary dynamics of protein-protein interaction networks inferred from the reconstruction of ancient networks. PLoS One 2013; 8:e58134. [PMID: 23526967 PMCID: PMC3603955 DOI: 10.1371/journal.pone.0058134] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2012] [Accepted: 01/30/2013] [Indexed: 11/18/2022] Open
Abstract
Cellular functions are based on the complex interplay of proteins, therefore the structure and dynamics of these protein-protein interaction (PPI) networks are the key to the functional understanding of cells. In the last years, large-scale PPI networks of several model organisms were investigated. A number of theoretical models have been developed to explain both the network formation and the current structure. Favored are models based on duplication and divergence of genes, as they most closely represent the biological foundation of network evolution. However, studies are often based on simulated instead of empirical data or they cover only single organisms. Methodological improvements now allow the analysis of PPI networks of multiple organisms simultaneously as well as the direct modeling of ancestral networks. This provides the opportunity to challenge existing assumptions on network evolution. We utilized present-day PPI networks from integrated datasets of seven model organisms and developed a theoretical and bioinformatic framework for studying the evolutionary dynamics of PPI networks. A novel filtering approach using percolation analysis was developed to remove low confidence interactions based on topological constraints. We then reconstructed the ancient PPI networks of different ancestors, for which the ancestral proteomes, as well as the ancestral interactions, were inferred. Ancestral proteins were reconstructed using orthologous groups on different evolutionary levels. A stochastic approach, using the duplication-divergence model, was developed for estimating the probabilities of ancient interactions from today's PPI networks. The growth rates for nodes, edges, sizes and modularities of the networks indicate multiplicative growth and are consistent with the results from independent static analysis. Our results support the duplication-divergence model of evolution and indicate fractality and multiplicative growth as general properties of the PPI network structure and dynamics.
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Affiliation(s)
- Yuliang Jin
- Levich Institute and Physics Department, City College of New York, New York, New York, United States of America
| | - Dmitrij Turaev
- Department of Computational Systems Biology, University of Vienna, Vienna, Austria
| | - Thomas Weinmaier
- Department of Computational Systems Biology, University of Vienna, Vienna, Austria
| | - Thomas Rattei
- Department of Computational Systems Biology, University of Vienna, Vienna, Austria
| | - Hernán A. Makse
- Levich Institute and Physics Department, City College of New York, New York, New York, United States of America
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Cuéllar AP, Pauwels L, De Clercq R, Goossens A. Yeast two-hybrid analysis of jasmonate signaling proteins. Methods Mol Biol 2013; 1011:173-85. [PMID: 23615996 DOI: 10.1007/978-1-62703-414-2_14] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Protein-protein interaction studies are crucial to unravel how jasmonate (JA) signals are transduced. Among the different techniques available, yeast two-hybrid (Y2H) is commonly used within the JA research community to identify proteins belonging to the core JA signaling module. The technique is based on the reconstitution of a transcriptional activator that drives the reporter gene expression upon protein-protein interactions. The method is sensitive and straightforward and can be adapted for different approaches. In this chapter, we provide a detailed protocol to perform targeted Y2H assays to test known proteins and/or protein domains for direct interaction in a pairwise manner and present the possibility to study ternary protein complexes through Y3H.
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Suter B, Fontaine JF, Yildirimman R, Raskó T, Schaefer MH, Rasche A, Porras P, Vázquez-Álvarez BM, Russ J, Rau K, Foulle R, Zenkner M, Saar K, Herwig R, Andrade-Navarro MA, Wanker EE. Development and application of a DNA microarray-based yeast two-hybrid system. Nucleic Acids Res 2012; 41:1496-507. [PMID: 23275563 PMCID: PMC3561971 DOI: 10.1093/nar/gks1329] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms.
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Affiliation(s)
- Bernhard Suter
- Max Delbrueck Center for Molecular Medicine, Berlin 13125, Germany.
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26
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A comparison and optimization of yeast two-hybrid systems. Methods 2012; 58:317-24. [PMID: 23231818 DOI: 10.1016/j.ymeth.2012.12.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2012] [Revised: 12/01/2012] [Accepted: 12/03/2012] [Indexed: 11/20/2022] Open
Abstract
Two-hybrid (Y2H) assays are available in a variety of different versions, including bacterial, yeast, and mammalian systems. However, even when done exclusively in yeast, multiple different host strains, vectors, reporter genes, or protocols can be used. Here we systematically compare protein-protein interactions (PPIs) from several previously published Y2H datasets. PPIs of a human gold-standard dataset were generated by Y2H assays as well as other methods such as LUMIER or protein fragment complementation assays (PCAs). Different Y2H methods detect substantially different subsets of these PPIs, even when protocols are standardized. In order to maximize the number of interactions found and to minimize the number of false positive interactions we recommend to combine multiple vectors and protocols. While the combined results of all 18 methods detected about 92% of a gold-standard interaction set, a combination of just three Y2H assays detected up to 78% of these protein pairs, or up to 83% when a fourth assay was included. These findings indicate that three or four separate assays may be sufficient to detect the majority of protein-protein interactions in many systems.
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Efficient prediction of co-complexed proteins based on coevolution. PLoS One 2012; 7:e48728. [PMID: 23152796 PMCID: PMC3494725 DOI: 10.1371/journal.pone.0048728] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2012] [Accepted: 09/28/2012] [Indexed: 11/19/2022] Open
Abstract
The prediction of the network of protein-protein interactions (PPI) of an organism is crucial for the understanding of biological processes and for the development of new drugs. Machine learning methods have been successfully applied to the prediction of PPI in yeast by the integration of multiple direct and indirect biological data sources. However, experimental data are not available for most organisms. We propose here an ensemble machine learning approach for the prediction of PPI that depends solely on features independent from experimental data. We developed new estimators of the coevolution between proteins and combined them in an ensemble learning procedure. We applied this method to a dataset of known co-complexed proteins in Escherichia coli and compared it to previously published methods. We show that our method allows prediction of PPI with an unprecedented precision of 95.5% for the first 200 sorted pairs of proteins compared to 28.5% on the same dataset with the previous best method. A close inspection of the best predicted pairs allowed us to detect new or recently discovered interactions between chemotactic components, the flagellar apparatus and RNA polymerase complexes in E. coli.
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Armean IM, Lilley KS, Trotter MWB. Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments. Mol Cell Proteomics 2012; 12:1-13. [PMID: 23071097 DOI: 10.1074/mcp.r112.019554] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Advances in sensitivity, resolution, mass accuracy, and throughput have considerably increased the number of protein identifications made via mass spectrometry. Despite these advances, state-of-the-art experimental methods for the study of protein-protein interactions yield more candidate interactions than may be expected biologically owing to biases and limitations in the experimental methodology. In silico methods, which distinguish between true and false interactions, have been developed and applied successfully to reduce the number of false positive results yielded by physical interaction assays. Such methods may be grouped according to: (1) the type of data used: methods based on experiment-specific measurements (e.g., spectral counts or identification scores) versus methods that extract knowledge encoded in external annotations (e.g., public interaction and functional categorisation databases); (2) the type of algorithm applied: the statistical description and estimation of physical protein properties versus predictive supervised machine learning or text-mining algorithms; (3) the type of protein relation evaluated: direct (binary) interaction of two proteins in a cocomplex versus probability of any functional relationship between two proteins (e.g., co-occurrence in a pathway, sub cellular compartment); and (4) initial motivation: elucidation of experimental data by evaluation versus prediction of novel protein-protein interaction, to be experimentally validated a posteriori. This work reviews several popular computational scoring methods and software platforms for protein-protein interactions evaluation according to their methodology, comparative strengths and weaknesses, data representation, accessibility, and availability. The scoring methods and platforms described include: CompPASS, SAINT, Decontaminator, MINT, IntAct, STRING, and FunCoup. References to related work are provided throughout in order to provide a concise but thorough introduction to a rapidly growing interdisciplinary field of investigation.
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Affiliation(s)
- Irina M Armean
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, CB2 1GA, UK
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Diversity in genetic in vivo methods for protein-protein interaction studies: from the yeast two-hybrid system to the mammalian split-luciferase system. Microbiol Mol Biol Rev 2012; 76:331-82. [PMID: 22688816 DOI: 10.1128/mmbr.05021-11] [Citation(s) in RCA: 134] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays.
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Trabuco LG, Betts MJ, Russell RB. Negative protein-protein interaction datasets derived from large-scale two-hybrid experiments. Methods 2012; 58:343-8. [PMID: 22884951 DOI: 10.1016/j.ymeth.2012.07.028] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Revised: 06/27/2012] [Accepted: 07/28/2012] [Indexed: 01/05/2023] Open
Abstract
Negative protein-protein interaction datasets are needed for training and evaluation of interaction prediction methods, as well as validation of high-throughput interaction discovery experiments. In large-scale two-hybrid assays, the direct interaction of a large number of protein pairs is systematically probed. We present a simple method to harness two-hybrid data to obtain negative protein-protein interaction datasets, which we validated using other available experimental data. The method identifies interactions that were likely tested but not observed in a two-hybrid screen. For each negative interaction, a confidence score is defined as the shortest-path length between the two proteins in the interaction network derived from the two-hybrid experiment. We show that these high-quality negative datasets are particularly important when a specific biological context is considered, such as in the study of protein interaction specificity. We also illustrate the use of a negative dataset in the evaluation of the InterPreTS interaction prediction method.
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Reece-Hoyes JS, Marian Walhout AJ. Yeast one-hybrid assays: a historical and technical perspective. Methods 2012; 57:441-7. [PMID: 22884952 DOI: 10.1016/j.ymeth.2012.07.027] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2012] [Revised: 07/25/2012] [Accepted: 07/27/2012] [Indexed: 01/07/2023] Open
Abstract
Since its development about two decades ago, the yeast one-hybrid (Y1H) assay has become an important technique for detecting physical interactions between sequence-specific regulatory transcription factor proteins (TFs) and their DNA target sites. Multiple versions of the Y1H methodology have been developed, each with technical differences and unique advantages. We will discuss several of these technical variations in detail, and also provide some ideas for how Y1H assays can be further improved.
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Affiliation(s)
- John S Reece-Hoyes
- Program in Systems Biology, University of Massachusetts Medical School, 364 Plantation Street, Worcester, MA 01605, USA.
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Rajagopala SV, Sikorski P, Caufield JH, Tovchigrechko A, Uetz P. Studying protein complexes by the yeast two-hybrid system. Methods 2012; 58:392-9. [PMID: 22841565 DOI: 10.1016/j.ymeth.2012.07.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2012] [Revised: 07/10/2012] [Accepted: 07/12/2012] [Indexed: 01/13/2023] Open
Abstract
Protein complexes are typically analyzed by affinity purification and subsequent mass spectrometric analysis. However, in most cases the structure and topology of the complexes remains elusive from such studies. Here we investigate how the yeast two-hybrid system can be used to analyze direct interactions among proteins in a complex. First we tested all pairwise interactions among the seven proteins of Escherichia coli DNA polymerase III as well as an uncharacterized complex that includes MntR and PerR. Four and seven interactions were identified in these two complexes, respectively. In addition, we review Y2H data for three other complexes of known structure which serve as "gold-standards", namely Varicella Zoster Virus (VZV) ribonucleotide reductase (RNR), the yeast proteasome, and bacteriophage lambda. Finally, we review an Y2H analysis of the human spliceosome which may serve as an example for a dynamic mega-complex.
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Woodsmith J, Jenn RC, Sanderson CM. Systematic analysis of dimeric E3-RING interactions reveals increased combinatorial complexity in human ubiquitination networks. Mol Cell Proteomics 2012; 11:M111.016162. [PMID: 22493164 PMCID: PMC3394952 DOI: 10.1074/mcp.m111.016162] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Ubiquitination controls the stability or function of many human proteins, thereby regulating a wide range of physiological processes. In most cases the combinatorial pattern of protein interactions that facilitate substrate recognition or modification remain unclear. Moreover, the efficiency of ubiquitination reactions can be altered by the formation of homo- and heterotypic E3-RING complexes. To establish the prevalence and nature of binary E3-RING/E3-RING interactions systematic yeast two-hybrid screens were performed to test 7269 potential interactions between 124 human E3-RING proteins. These studies identified 228 dimeric interactions between 100 E3-RINGs, of which 205 were novel. Complementary co-immunoprecipitation studies were performed to test predicted network interactions, showing a high correlation (64%) with primary yeast two-hybrid data. This data was integrated with known E3-RING interactions, tissue expression profiles and proteomic ubiquitination datasets to facilitate identification of subnetworks in which E3-RING dimerization events have the potential to alter network structure. These results reveal a widespread yet selective pattern of E3-RING dimerization events, which have the potential to confer further combinatorial complexity within human ubiquitination cascades.
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Affiliation(s)
- Jonathan Woodsmith
- Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, L69 3BX, UK
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Rajagopala SV, Uetz P. Analysis of protein-protein interactions using high-throughput yeast two-hybrid screens. Methods Mol Biol 2012; 781:1-29. [PMID: 21877274 DOI: 10.1007/978-1-61779-276-2_1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
The yeast two-hybrid (Y2H) system is a powerful tool to identify binary protein-protein interactions. Here, we describe array-based two-hybrid methods that use defined libraries of open reading frames (ORFs) and pooled prey library screenings that use random genomic or cDNA libraries. The array-based Y2H system is well-suited for interactome studies of existing ORFeomes or subsets thereof, preferentially in a recombination-based cloning system. Array-based Y2H screens efficiently reduce false positives by using built-in controls, retesting, and evaluation of background activation. Hands-on time and the amount of used resources grow exponentially with the number of tested proteins; this is a disadvantage for large genome sizes. For large genomes, random library screen may be more efficient in terms of time and resources, but not as comprehensive as array screens, and it requires significant sequencing capacity. Furthermore, multiple variants of the Y2H vector systems detect markedly different subsets of interactions in the same interactome. Hence, only multiple variations of the Y2H systems ensure comprehensive coverage of an interactome.
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Worseck JM, Grossmann A, Weimann M, Hegele A, Stelzl U. A stringent yeast two-hybrid matrix screening approach for protein-protein interaction discovery. Methods Mol Biol 2012; 812:63-87. [PMID: 22218854 DOI: 10.1007/978-1-61779-455-1_4] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
The yeast two-hybrid (Y2H) system is currently one of the most important techniques for protein-protein interaction (PPI) discovery. Here, we describe a stringent three-step Y2H matrix interaction approach that is suitable for systematic PPI screening on a proteome scale. We start with the identification and elimination of autoactivating strains that would lead to false-positive signals and prevent the identification of interactions. Nonautoactivating strains are used for the primary PPI screen that is carried out in quadruplicate with arrayed preys. Interacting pairs of baits and preys are identified in a pairwise retest step. Only PPI pairs that pass the retest step are regarded as potentially biologically relevant interactions and are considered for further analysis.
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Häuser R, Stellberger T, Rajagopala SV, Uetz P. Matrix-based yeast two-hybrid screen strategies and comparison of systems. Methods Mol Biol 2012; 812:1-20. [PMID: 22218851 DOI: 10.1007/978-1-61779-455-1_1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Today, matrix-based screens are used primarily for smaller and medium-size clone collections in combination with automation and cloning techniques that allow for reliable and fast interaction screening. Matrix-based yeast two-hybrid screens are an alternative to library-based screens. However, intermediary forms are possible too and we compare both strategies, including a detailed discussion of matrix-based screens. Recent improvement of matrix screens (also called array screens) uses various pooling strategies as well as novel vectors that increase their efficiency while decreasing false-negative rates and increasing reliability.
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Affiliation(s)
- Roman Häuser
- Karlsruhe Institute of Technology, Karlsruhe, Germany
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Causier B, Ashworth M, Guo W, Davies B. The TOPLESS interactome: a framework for gene repression in Arabidopsis. PLANT PHYSIOLOGY 2012; 158:423-38. [PMID: 22065421 PMCID: PMC3252085 DOI: 10.1104/pp.111.186999] [Citation(s) in RCA: 365] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2011] [Accepted: 11/04/2011] [Indexed: 05/17/2023]
Abstract
Transcription factors activate or repress target gene expression or switch between activation and repression. In animals and yeast, Groucho/Tup1 corepressor proteins are recruited by diverse transcription factors to induce context-specific transcriptional repression. Two groups of Groucho/Tup1-like corepressors have been described in plants. LEUNIG and LEUNIG_HOMOLOG constitute one group and TOPLESS (TPL) and the four TPL-related (TPR) corepressors form the other. To discover the processes in which TPL and the TPR corepressors operate, high-throughput yeast two-hybrid approaches were used to identify interacting proteins. We found that TPL/TPR corepressors predominantly interact directly with specific transcription factors, many of which were previously implicated in transcriptional repression. The interacting transcription factors reveal that the TPL/TPR family has been coopted multiple times to modulate gene expression in diverse processes, including hormone signaling, stress responses, and the control of flowering time, for which we also show biological validation. The interaction data suggest novel mechanisms for the involvement of TPL/TPR corepressors in auxin and jasmonic acid signaling. A number of short repression domain (RD) sequences have previously been identified in Arabidopsis (Arabidopsis thaliana) transcription factors. All known RD sequences were enriched among the TPL/TPR interactors, and novel TPL-RD interactions were identified. We show that the presence of RD sequences is essential for TPL/TPR recruitment. These data provide a framework for TPL/TPR-dependent transcriptional repression. They allow for predictions about new repressive transcription factors, corepressor interactions, and repression mechanisms and identify a wide range of plant processes that utilize TPL/TPR-mediated gene repression.
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Reece-Hoyes JS, Diallo A, Lajoie B, Kent A, Shrestha S, Kadreppa S, Pesyna C, Dekker J, Myers CL, Walhout AJM. Enhanced yeast one-hybrid assays for high-throughput gene-centered regulatory network mapping. Nat Methods 2011; 8:1059-64. [PMID: 22037705 PMCID: PMC3235803 DOI: 10.1038/nmeth.1748] [Citation(s) in RCA: 87] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2011] [Accepted: 08/19/2011] [Indexed: 12/17/2022]
Abstract
A major challenge in systems biology is to understand the gene regulatory networks that drive development, physiology and pathology. Interactions between transcription factors and regulatory genomic regions provide the first level of gene control. Gateway-compatible yeast one-hybrid (Y1H) assays present a convenient method to identify and characterize the repertoire of transcription factors that can bind a DNA sequence of interest. To delineate genome-scale regulatory networks, however, large sets of DNA fragments need to be processed at high throughput and high coverage. Here we present enhanced Y1H (eY1H) assays that use a robotic mating platform with a set of improved Y1H reagents and automated readout quantification. We demonstrate that eY1H assays provide excellent coverage and identify interacting transcription factors for multiple DNA fragments in a short time. eY1H assays will be an important tool for mapping gene regulatory networks in Caenorhabditis elegans and other model organisms as well as in humans.
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Affiliation(s)
- John S Reece-Hoyes
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
| | - Alos Diallo
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
| | - Bryan Lajoie
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Department of Biochemistry and Molecular Pharmacology University of Massachusetts Medical School, Worcester, MA, USA
| | - Amanda Kent
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
| | - Shaleen Shrestha
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
| | - Sreenath Kadreppa
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
| | - Colin Pesyna
- Department of Computer Science and Engineering, University of Minnesota–Twin Cities, Minneapolis, MN, USA
| | - Job Dekker
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Department of Biochemistry and Molecular Pharmacology University of Massachusetts Medical School, Worcester, MA, USA
| | - Chad L Myers
- Department of Computer Science and Engineering, University of Minnesota–Twin Cities, Minneapolis, MN, USA
| | - Albertha J M Walhout
- Program in Systems Biology, Worcester, MA, USA
- Program in Gene Function and Expression, Worcester, MA, USA
- Program in Molecular Medicine, Worcester, MA, USA
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Lee S, Salwinski L, Zhang C, Chu D, Sampankanpanich C, Reyes NA, Vangeloff A, Xing F, Li X, Wu TT, Sahasrabudhe S, Deng H, LaCount DJ, Sun R. An integrated approach to elucidate the intra-viral and viral-cellular protein interaction networks of a gamma-herpesvirus. PLoS Pathog 2011; 7:e1002297. [PMID: 22028648 PMCID: PMC3197595 DOI: 10.1371/journal.ppat.1002297] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2011] [Accepted: 08/17/2011] [Indexed: 12/22/2022] Open
Abstract
Genome-wide yeast two-hybrid (Y2H) screens were conducted to elucidate the molecular functions of open reading frames (ORFs) encoded by murine γ-herpesvirus 68 (MHV-68). A library of 84 MHV-68 genes and gene fragments was generated in a Gateway entry plasmid and transferred to Y2H vectors. All possible pair-wise interactions between viral proteins were tested in the Y2H assay, resulting in the identification of 23 intra-viral protein-protein interactions (PPIs). Seventy percent of the interactions between viral proteins were confirmed by co-immunoprecipitation experiments. To systematically investigate virus-cellular protein interactions, the MHV-68 Y2H constructs were screened against a cellular cDNA library, yielding 243 viral-cellular PPIs involving 197 distinct cellar proteins. Network analyses indicated that cellular proteins targeted by MHV-68 had more partners in the cellular PPI network and were located closer to each other than expected by chance. Taking advantage of this observation, we scored the cellular proteins based on their network distances from other MHV-68-interacting proteins and segregated them into high (Y2H-HP) and low priority/not-scored (Y2H-LP/NS) groups. Significantly more genes from Y2H-HP altered MHV-68 replication when their expression was inhibited with siRNAs (53% of genes from Y2H-HP, 21% of genes from Y2H-LP/NS, and 16% of genes randomly chosen from the human PPI network; p<0.05). Enriched Gene Ontology (GO) terms in the Y2H-HP group included regulation of apoptosis, protein kinase cascade, post-translational protein modification, transcription from RNA polymerase II promoter, and IκB kinase/NFκB cascade. Functional validation assays indicated that PCBP1, which interacted with MHV-68 ORF34, may be involved in regulating late virus gene expression in a manner consistent with the effects of its viral interacting partner. Our study integrated Y2H screening with multiple functional validation approaches to create γ-herpes viral-viral and viral-cellular protein interaction networks. Persistent infections by the herpesviruses Epstein Barr virus (EBV) and Kaposi's sarcoma herpesvirus (KSHV) are associated with tumor formation. To better understand how these and other related viruses interact with their host cells to promote virus replication and cause disease, we studied murine gamma-herpesvirus 68 (MHV-68). MHV-68 belongs to the same group of herpesviruses as EBV and KSHV, but has the advantage of being able to replicate efficiently in cell culture. Our study used genome-wide screens to identify 23 protein-protein interactions between the 80 MHV-68 proteins. Several of these interactions are likely to be important for assembling new viruses. We also discovered 243 interactions between MHV-68 and cellular proteins. To help prioritize cellular proteins for follow up studies, we developed a new computational tool to analyze our data. Proteins with high priority scores were more likely to affect viral replication than low priority proteins. Among the cellular proteins that had the greatest effect on MHV-68 replication was PCBP1, which negatively regulated MHV-68 late gene expression. This study identified many novel cellular proteins involved in MHV-68 replication and established a method to identify important proteins from high-throughput virus-cellular protein-protein interaction data sets.
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Affiliation(s)
- Shaoying Lee
- School of Dentistry, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Lukasz Salwinski
- UCLA DOE-Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, California, United States of America
| | - Chaoying Zhang
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West LaFayette, Indiana, United States of America
| | - Derrick Chu
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Claire Sampankanpanich
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Nichole A. Reyes
- Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Abbey Vangeloff
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West LaFayette, Indiana, United States of America
| | - Fangfang Xing
- Department of Molecular Cell and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Xudong Li
- Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, United States of America
| | - Ting-Ting Wu
- Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, United States of America
| | | | - Hongyu Deng
- School of Dentistry, University of California Los Angeles, Los Angeles, California, United States of America
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Douglas J. LaCount
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West LaFayette, Indiana, United States of America
- * E-mail: (DJL); (RS)
| | - Ren Sun
- Department of Molecular and Medical Pharmacology, University of California Los Angeles, Los Angeles, California, United States of America
- * E-mail: (DJL); (RS)
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Rajagopala SV, Casjens S, Uetz P. The protein interaction map of bacteriophage lambda. BMC Microbiol 2011; 11:213. [PMID: 21943085 PMCID: PMC3224144 DOI: 10.1186/1471-2180-11-213] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2011] [Accepted: 09/26/2011] [Indexed: 11/25/2022] Open
Abstract
Background Bacteriophage lambda is a model phage for most other dsDNA phages and has been studied for over 60 years. Although it is probably the best-characterized phage there are still about 20 poorly understood open reading frames in its 48-kb genome. For a complete understanding we need to know all interactions among its proteins. We have manually curated the lambda literature and compiled a total of 33 interactions that have been found among lambda proteins. We set out to find out how many protein-protein interactions remain to be found in this phage. Results In order to map lambda's interactions, we have cloned 68 out of 73 lambda open reading frames (the "ORFeome") into Gateway vectors and systematically tested all proteins for interactions using exhaustive array-based yeast two-hybrid screens. These screens identified 97 interactions. We found 16 out of 30 previously published interactions (53%). We have also found at least 18 new plausible interactions among functionally related proteins. All previously found and new interactions are combined into structural and network models of phage lambda. Conclusions Phage lambda serves as a benchmark for future studies of protein interactions among phage, viruses in general, or large protein assemblies. We conclude that we could not find all the known interactions because they require chaperones, post-translational modifications, or multiple proteins for their interactions. The lambda protein network connects 12 proteins of unknown function with well characterized proteins, which should shed light on the functional associations of these uncharacterized proteins.
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Yu X, Ivanic J, Memisević V, Wallqvist A, Reifman J. Categorizing biases in high-confidence high-throughput protein-protein interaction data sets. Mol Cell Proteomics 2011; 10:M111.012500. [PMID: 21876202 DOI: 10.1074/mcp.m111.012500] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not necessarily imply that one detection methodology was better or worse, but rather that, to a large extent, the insights reflected the methodological biases themselves. Consequently, interpreting the protein interaction data within their experimental or cellular context provided the best avenue for overcoming biases and inferring biological knowledge.
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Affiliation(s)
- Xueping Yu
- Biotechnology HPC Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Ft. Detrick, MD 21702, USA
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Abstract
Mass spectrometry analysis of Streptococcus pneumoniae bacteriophage Cp-1 identified a total of 12 proteins, and proteome-wide yeast two-hybrid screens revealed 17 binary interactions mainly among these structural proteins. On the basis of the resulting linkage map, we suggest an improved structural model of the Cp-1 virion.
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Wiens M, Schröder HC, Wang X, Link T, Steindorf D, Müller WEG. Isolation of the Silicatein-α Interactor Silintaphin-2 by a Novel Solid-Phase Pull-Down Assay. Biochemistry 2011; 50:1981-90. [DOI: 10.1021/bi101429x] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Matthias Wiens
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
| | - Heinz-C. Schröder
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
| | - Xiaohong Wang
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
- National Research Center for Geoanalysis, 26 Baiwanzhuang Dajie, CHN-100037 Beijing, China
| | - Thorben Link
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
| | - Dominik Steindorf
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
| | - Werner E. G. Müller
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University, Duesbergweg 6, D-55128 Mainz, Germany
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Chen YC, Rajagopala SV, Stellberger T, Uetz P. Exhaustive benchmarking of the yeast two-hybrid system. Nat Methods 2010; 7:667-8; author reply 668. [DOI: 10.1038/nmeth0910-667] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Rajagopala SV, Yamamoto N, Zweifel AE, Nakamichi T, Huang HK, Mendez-Rios JD, Franca-Koh J, Boorgula MP, Fujita K, Suzuki KI, Hu JC, Wanner BL, Mori H, Uetz P. The Escherichia coli K-12 ORFeome: a resource for comparative molecular microbiology. BMC Genomics 2010; 11:470. [PMID: 20701780 PMCID: PMC3091666 DOI: 10.1186/1471-2164-11-470] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2010] [Accepted: 08/11/2010] [Indexed: 01/20/2023] Open
Abstract
Background Systems biology and functional genomics require genome-wide datasets and resources. Complete sets of cloned open reading frames (ORFs) have been made for about a dozen bacterial species and allow researchers to express and study complete proteomes in a high-throughput fashion. Results We have constructed an open reading frame (ORFeome) collection of 3974 or 94% of the known Escherichia coli K-12 ORFs in Gateway® entry vector pENTR/Zeo. The collection has been used for protein expression and protein interaction studies. For example, we have compared interactions among YgjD, YjeE and YeaZ proteins in E. coli, Streptococcus pneumoniae, and Staphylococcus aureus. We also compare this ORFeome with other Gateway-compatible bacterial ORFeomes and show its utility for comparative functional genomics. Conclusions The E. coli ORFeome provides a useful resource for functional genomics and other areas of protein research in a highly flexible format. Our comparison with other ORFeomes makes comparative analyses straighforward and facilitates direct comparisons of many proteins across many genomes.
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Mendez-Rios J, Uetz P. Global approaches to study protein-protein interactions among viruses and hosts. Future Microbiol 2010; 5:289-301. [PMID: 20143950 DOI: 10.2217/fmb.10.7] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
While high-throughput protein-protein interaction screens were first published approximately 10 years ago, systematic attempts to map interactions among viruses and hosts started only a few years ago. HIV-human interactions dominate host-pathogen interaction databases (with approximately 2000 interactions) despite the fact that probably none of these interactions have been identified in systematic interaction screens. Recently, combinations of protein interaction data with RNAi and other functional genomics data allowed researchers to model more complex interaction networks. The rapid progress in this area promises a flood of new data in the near future, with clinical applications as soon as structural and functional genomics catches up with next-generation sequencing of human variation and structure-based drug design.
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Affiliation(s)
- Jorge Mendez-Rios
- J Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA.
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Stellberger T, Häuser R, Baiker A, Pothineni VR, Haas J, Uetz P. Improving the yeast two-hybrid system with permutated fusions proteins: the Varicella Zoster Virus interactome. Proteome Sci 2010; 8:8. [PMID: 20205919 PMCID: PMC2832230 DOI: 10.1186/1477-5956-8-8] [Citation(s) in RCA: 106] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2009] [Accepted: 02/15/2010] [Indexed: 11/24/2022] Open
Abstract
Background Yeast two-hybrid (Y2H) screens have been among the most powerful methods to detect and analyze protein-protein interactions. However, they suffer from a significant degree of false negatives, i.e. true interactions that are not detected, and to a certain degree from false positives, i.e. interactions that appear to take place only in the context of the Y2H assay. While the fraction of false positives remains difficult to estimate, the fraction of false negatives in typical Y2H screens is on the order of 70-90%. Here we present novel Y2H vectors that significantly decrease the number of false negatives and help to mitigate the false positive problem. Results We have constructed two new vectors (pGBKCg and pGADCg) that allow us to make both C-terminal fusion proteins of DNA-binding and activation domains. Both vectors can be combined with existing vectors for N-terminal fusions and thus allow four different bait-prey combinations: NN, CC, NC, and CN. We have tested all ~4,900 pairwise combinations of the 70 Varicella-Zoster-Virus (VZV) proteins for interactions, using all possible combinations. About ~20,000 individual Y2H tests resulted in 182 NN, 89 NC, 149 CN, and 144 CC interactions. Overlap between screens ranged from 17% (NC-CN) to 43% (CN-CC). Performing four screens (i.e. permutations) instead of one resulted in about twice as many interactions and thus much fewer false negatives. In addition, interactions that are found in multiple combinations confirm each other and thus provide a quality score. This study is the first systematic analysis of such N- and C-terminal Y2H vectors. Conclusions Permutations of C- and N-terminal Y2H vectors dramatically increase the coverage of interactome studies and thus significantly reduce the number of false negatives. We suggest that future interaction screens should use such vector combinations on a routine basis, not the least because they provide a built-in quality score for Y2H interactions that can provide a measure of reproducibility without additional assays.
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Affiliation(s)
- Thorsten Stellberger
- Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, PO Box 3640, D-76021 Karlsruhe, Germany.
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