Multiplexed Nucleic Acid Programmable Protein Arrays

Rationale: Cell-free protein microarrays display naturally-folded proteins based on just-in-time in situ synthesis, and have made important contributions to basic and translational research. However, the risk of spot-to-spot cross-talk from protein diffusion during expression has limited the feature density of these arrays. Methods: In this work, we developed the Multiplexed Nucleic Acid Programmable Protein Array (M-NAPPA), which significantly increases the number of displayed proteins by multiplexing as many as five different gene plasmids within a printed spot. Results: Even when proteins of different sizes were displayed within the same feature, they were readily detected using protein-specific antibodies. Protein-protein interactions and serological antibody assays using human viral proteome microarrays demonstrated that comparable hits were detected by M-NAPPA and non-multiplexed NAPPA arrays. An ultra-high density proteome microarray displaying > 16k proteins on a single microscope slide was produced by combining M-NAPPA with a photolithography-based silicon nano-well platform. Finally, four new tuberculosis-related antigens in guinea pigs vaccinated with Bacillus Calmette-Guerin (BCG) were identified with M-NAPPA and validated with ELISA. Conclusion: All data demonstrate that multiplexing features on a protein microarray offer a cost-effective fabrication approach and have the potential to facilitate high throughput translational research.

[1]  Xiaobo Yu,et al.  Identification of Antibody Targets for Tuberculosis Serology using High-Density Nucleic Acid Programmable Protein Arrays* , 2017, Molecular & Cellular Proteomics.

[2]  Joshua LaBaer,et al.  Serological autoantibody profiling of type 1 diabetes by protein arrays. , 2013, Journal of proteomics.

[3]  M. Taussig,et al.  Single step generation of protein arrays from DNA by cell-free expression and in situ immobilisation (PISA method). , 2001, Nucleic acids research.

[4]  Xiaobo Yu,et al.  Antiviral antibody profiling by high‐density protein arrays , 2015, Proteomics.

[5]  T. Joos,et al.  Protein microarray technology. , 2002, Trends in biotechnology.

[6]  Heng Zhu,et al.  Identification of Serum Biomarkers for Gastric Cancer Diagnosis Using a Human Proteome Microarray* , 2015, Molecular & Cellular Proteomics.

[7]  Peter Wiktor,et al.  High density diffusion-free nanowell arrays. , 2012, Journal of proteome research.

[8]  David E. Misek,et al.  Development of natural protein microarrays for diagnosing cancer based on an antibody response to tumor antigens. , 2004, Journal of proteome research.

[9]  Dan Wang,et al.  AAgAtlas 1.0: a human autoantigen database , 2016, Nucleic Acids Res..

[10]  Xiaobo Yu,et al.  Advancing translational research with next‐generation protein microarrays , 2016, Proteomics.

[11]  Manuel Fuentes,et al.  NAPPA as a Real New Method for Protein Microarray Generation , 2015, Microarrays.

[12]  M. Taussig,et al.  Optimised 'on demand' protein arraying from DNA by cell free expression with the 'DNA to Protein Array' (DAPA) technology. , 2013, Journal of proteomics.

[13]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[14]  Alan B Hollingsworth,et al.  Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer , 2016, PloS one.

[15]  David E Hill,et al.  Mapping transcription factor interactome networks using HaloTag protein arrays , 2016, Proceedings of the National Academy of Sciences.

[16]  F. Carlotti,et al.  Functional studies of E7 proteins from different HPV types. , 1994, Oncogene.

[17]  J. LaBaer,et al.  High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays , 2015, Nature Protocols.

[18]  Bhupinder Bhullar,et al.  Self-Assembling Protein Microarrays , 2004, Science.

[19]  Heng Zhu,et al.  Protein chip fabrication by capture of nascent polypeptides , 2006, Nature Biotechnology.

[20]  Philip L Felgner,et al.  Dynamic antibody responses to the Mycobacterium tuberculosis proteome , 2010, Proceedings of the National Academy of Sciences.

[21]  Joshua LaBaer,et al.  Plasma Autoantibodies Associated with Basal-like Breast Cancers , 2015, Cancer Epidemiology, Biomarkers & Prevention.

[22]  Peter Nilsson,et al.  Anoctamin 2 identified as an autoimmune target in multiple sclerosis , 2016, Proceedings of the National Academy of Sciences.

[23]  D. Czajkowsky,et al.  Systematic identification of arsenic-binding proteins reveals that hexokinase-2 is inhibited by arsenic , 2015, Proceedings of the National Academy of Sciences.

[24]  Tasneem H. Patwa,et al.  The identification of phosphoglycerate kinase‐1 and histone H4 autoantibodies in pancreatic cancer patient serum using a natural protein microarray , 2009, Electrophoresis.

[25]  Shaohui Hu,et al.  Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[26]  J. Pipas,et al.  Exploration of Panviral Proteome: High-Throughput Cloning and Functional Implications in Virus-host Interactions , 2014, Theranostics.

[27]  Michael J Taussig,et al.  Printing protein arrays from DNA arrays , 2008, Nature Methods.

[28]  J. LaBaer,et al.  Copper-catalyzed azide-alkyne cycloaddition (click chemistry)-based Detection of Global Pathogen-host AMPylation on Self-assembled Human Protein Microarrays* , 2014, Molecular & Cellular Proteomics.

[29]  Shan X. Wang,et al.  Emerging protein array technologies for proteomics , 2013, Expert review of proteomics.

[30]  Yanhui Hu,et al.  Next generation high density self assembling functional protein arrays , 2008, Nature Methods.

[31]  Xiaobo Yu,et al.  Host-pathogen interaction profiling using self-assembling human protein arrays. , 2015, Journal of proteome research.

[32]  Hans Lehrach,et al.  Cell-free protein expression and functional assay in nanowell chip format. , 2004, Analytical chemistry.

[33]  Joshua Labaer,et al.  Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer. , 2011, Journal of proteome research.

[34]  Jun Wan,et al.  Protein Acetylation Microarray Reveals that NuA4 Controls Key Metabolic Target Regulating Gluconeogenesis , 2009, Cell.

[35]  Xiaobo Yu,et al.  Protein Microarrays for Personalized Medicine , 2010, Clinical chemistry.

[36]  Matthew A. Kayala,et al.  A Burkholderia pseudomallei protein microarray reveals serodiagnostic and cross-reactive antigens , 2009, Proceedings of the National Academy of Sciences.

[37]  Peter Wiktor,et al.  A Contra Capture Protein Array Platform for Studying Post-translationally Modified (PTM) Auto-antigenomes* , 2016, Molecular & Cellular Proteomics.

[38]  J. Nevins,et al.  Adenovirus E1A, simian virus 40 tumor antigen, and human papillomavirus E7 protein share the capacity to disrupt the interaction between transcription factor E2F and the retinoblastoma gene product. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[39]  M. Sowa,et al.  Systematic identification of interactions between host cell proteins and E7 oncoproteins from diverse human papillomaviruses , 2012, Proceedings of the National Academy of Sciences.

[40]  H. Hang,et al.  Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity. , 2014, Cell reports.

[41]  S. Fields,et al.  Protein analysis on a proteomic scale , 2003, Nature.

[42]  M. Taussig,et al.  Cell free expression put on the spot: advances in repeatable protein arraying from DNA (DAPA). , 2011, New biotechnology.

[43]  Joshua LaBaer,et al.  Autoantibody Signature for the Serologic Detection of Ovarian Cancer , 2014, Journal of proteome research.

[44]  G. Wallstrom,et al.  Immunoproteomic Profiling of Antiviral Antibodies in New-Onset Type 1 Diabetes Using Protein Arrays , 2015, Diabetes.

[45]  A. Casadevall,et al.  Mycobacterial Membrane Vesicles Administered Systemically in Mice Induce a Protective Immune Response to Surface Compartments of Mycobacterium tuberculosis , 2014, mBio.