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Developments and Applications of Functional Protein Microarrays*

  • Guan-Da Syu
    Correspondence
    To whom correspondence may be addressed: Room 89A07, Department of Biotechnology and Bioindustry Sciences, No.1, University Road, Tainan City 701, Taiwan (R.O.C). Tel.: +886-6-275-7575#58231; Fax: +886-6-276-6490;
    Affiliations
    Department of Biotechnology and Bioindustry Sciences, National Cheng Kung University, Tainan 701, Taiwan R.O.C.
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  • Jessica Dunn
    Affiliations
    Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
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  • Heng Zhu
    Correspondence
    To whom correspondence may be addressed: Room 327, Edward D. Miller Research Building, 733 N. Broadway, Baltimore, MD 21205. Tel.: +1-410-502-0878; Fax: +1-410-502-1872
    Affiliations
    Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

    Center for High-Throughput Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

    Viral Oncology Program, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231
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  • Author Footnotes
    * This work was supported in part by the NIH/NCI IMAT R33-CA186790-01A1, MOST Taiwan fellowship 105-2917-I-564-078, and MOST Taiwan 108-2320-B-006-054-MY2. JD was supported in part by the CBI program (NIH 2T32GM080189-11) at The Johns Hopkins University. The authors declare that they have no conflicts of interest with the contents of this article.
Open AccessPublished:April 17, 2020DOI:https://doi.org/10.1074/mcp.R120.001936
      Protein microarrays are crucial tools in the study of proteins in an unbiased, high-throughput manner, as they allow for characterization of up to thousands of individually purified proteins in parallel. The adaptability of this technology has enabled its use in a wide variety of applications, including the study of proteome-wide molecular interactions, analysis of post-translational modifications, identification of novel drug targets, and examination of pathogen-host interactions. In addition, the technology has also been shown to be useful in profiling antibody specificity, as well as in the discovery of novel biomarkers, especially for autoimmune diseases and cancers. In this review, we will summarize the developments that have been made in protein microarray technology in both in basic and translational research over the past decade. We will also introduce a novel membrane protein array, the GPCR-VirD array, and discuss the future directions of functional protein microarrays.

      Graphical Abstract

      Proteins are diverse biomolecules with a wide variety of structures and functions, and as such, it is a challenge to study them in a high-throughput fashion. There are three major types of protein microarrays: functional, analytical, and reverse phase. Functional protein microarrays are constructed with proteins purified/synthesized in a high-throughput fashion, enabling hundreds, and even thousands of different proteins to be probed for their biochemical properties in parallel. Analytical protein microarrays use affinity reagents that are immobilized on the array to detect or quantify complex biological samples. Finally, reverse phase protein microarrays utilize complex biological samples immobilized on the array and use affinity reagents for detection (
      • Moore C.D.
      • Ajala O.Z.
      • Zhu H.
      Applications in high-content functional protein microarrays.
      ). In this short review, we focus on functional protein microarrays, summarize the recent developments in functional microarray technology, and discuss potential future applications.
      Compared with other methods, such as mass spectrometry, functional protein microarrays are more capable of detecting weak interactions, more flexible with low abundancy proteins, and more amenable to analyzing crude samples such as serum. However, there are still some limitations for protein microarrays. The binding events observed during microarray experiments may not reflect the binding events that occur in the context of a cellular environment. Also, most of the detection methods involve labels and thus require proper controls (
      • Neiswinger J.
      • Uzoma I.
      • Cox E.
      • Rho H.
      • Song G.
      • Paul C.
      • Jeong J.S.
      • Lu K.Y.
      • Chen C.S.
      • Zhu H.
      Protein microarrays: flexible tools for scientific innovation.
      ). To date, many different types of functional protein microarrays have been developed in terms of differences in proteome coverage, protein lengths, and production pipelines. Some notable examples of the different categories of protein microarrays include purified proteome microarrays for full-length proteins, purified protein family microarrays for different protein categories, purified protein domain microarrays for user-defined domains/epitopes, and cell-free protein/peptide microarrays for in vitro translation from cDNA or in vitro synthesis. In Table I, we summarize the current developments in functional protein microarrays and divide them into these four categories. We also introduce a new concept, a membrane protein microarray (i.e. VirD
      The abbreviations used are:
      VirD
      Virion Display
      PrEST
      Protein Epitope Signature Tag
      IVTT
      in vitro transcription and translation
      NAPPA
      Nucleic Acid Programmable Protein Array
      PTM
      post-translational modifications
      HBMEC
      human brain microvascular endothelial cells.
      1The abbreviations used are:VirD
      Virion Display
      PrEST
      Protein Epitope Signature Tag
      IVTT
      in vitro transcription and translation
      NAPPA
      Nucleic Acid Programmable Protein Array
      PTM
      post-translational modifications
      HBMEC
      human brain microvascular endothelial cells.
      array), and discuss the possible future directions of VirD array technology.
      Table ISummary of high-content functional protein microarrays
      Organism/Protein classificationProtein No.CoverageExpression systemRefs.
      Purified proteome microarray
      Homo sapiens
      Commercialized with the trademark HuProtTM by CDI Laboratories and expended to >21,000 proteins in version 4.
      21,00081%S. cerevisiae(
      • Jeong J.S.
      • Jiang L.
      • Albino E.
      • Marrero J.
      • Rho H.S.
      • Hu J.
      • Hu S.
      • Vera C.
      • Bayron-Poueymiroy D.
      • Rivera-Pacheco Z.A.
      • Ramos L.
      • Torres-Castro C.
      • Qian J.
      • Bonaventura J.
      • Boeke J.D.
      • Yap W.Y.
      • Pino I.
      • Eichinger D.J.
      • Zhu H.
      • Blackshaw S.
      Rapid identification of monospecific monoclonal antibodies using a human proteome microarray.
      ,
      • Hu S.
      • Xie Z.
      • Onishi A.
      • Yu X.
      • Jiang L.
      • Lin J.
      • Rho H.S.
      • Woodard C.
      • Wang H.
      • Jeong J.S.
      • Long S.
      • He X.
      • Wade H.
      • Blackshaw S.
      • Qian J.
      • Zhu H.
      Profiling the human protein-DNA interactome reveals ERK2 as a transcriptional repressor of interferon signaling.
      )
      S. cerevisiae580080%S. cerevisiae(
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      )
      E. coli K12425690%E. coli(
      • Chen C.S.
      • Korobkova E.
      • Chen H.
      • Zhu J.
      • Jian X.
      • Tao S.C.
      • He C.
      • Zhu H.
      A proteome chip approach reveals new DNA damage recognition activities in Escherichia coli.
      )
      Arabidopsis thaliana15,00056%N. benthamiana(
      • Popescu S.C.
      • Popescu G.V.
      • Bachan S.
      • Zhang Z.
      • Seay M.
      • Gerstein M.
      • Snyder M.
      • Dinesh-Kumar S.P.
      Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays.
      ,
      • Manohar M.
      • Tian M.
      • Moreau M.
      • Park S.W.
      • Choi H.W.
      • Fei Z.
      • Friso G.
      • Asif M.
      • Manosalva P.
      • von Dahl C.C.
      • Shi K.
      • Ma S.
      • Dinesh-Kumar S.P.
      • O'Doherty I.
      • Schroeder F.C.
      • van Wijk K.J.
      • Klessig D.F.
      Identification of multiple salicylic acid-binding proteins using two high throughput screens.
      )
      M. tuberculosis426295%S. cerevisiae(
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      )
       Coronavirus8275%S. cerevisiae(
      • Zhu H.
      • Hu S.
      • Jona G.
      • Zhu X.
      • Kreiswirth N.
      • Willey B.M.
      • Mazzulli T.
      • Liu G.
      • Song Q.
      • Chen P.
      • Cameron M.
      • Tyler A.
      • Wang J.
      • Wen J.
      • Chen W.
      • Compton S.
      • Snyder M.
      Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray.
      )
       Epstein-Barr virus6066%S. cerevisiae(
      • Zhu J.
      • Liao G.
      • Shan L.
      • Zhang J.
      • Chen M.R.
      • Hayward G.S.
      • Hayward S.D.
      • Desai P.
      • Zhu H.
      Protein array identification of substrates of the Epstein-Barr virus protein kinase BGLF4.
      )
       Zika and dengue viruses4886%S. cerevisiae(
      • Song G.
      • Rho H.S.
      • Pan J.
      • Ramos P.
      • Yoon K.J.
      • Medina F.A.
      • Lee E.M.
      • Eichinger D.
      • Ming G.L.
      • Munoz-Jordan J.L.
      • Tang H.
      • Pino I.
      • Song H.
      • Qian J.
      • Zhu H.
      Multiplexed biomarker panels discriminate Zika and Dengue virus infection in humans.
      )
       Herpes simplex virus-1/27250%E. coli(
      • Kalantari-Dehaghi M.
      • Chun S.
      • Chentoufi A.A.
      • Pablo J.
      • Liang L.
      • Dasgupta G.
      • Molina D.M.
      • Jasinskas A.
      • Nakajima-Sasaki R.
      • Felgner J.
      • Hermanson G.
      • BenMohamed L.
      • Felgner P.L.
      • Davies D.H.
      Discovery of potential diagnostic and vaccine antigens in herpes simplex virus 1 and 2 by proteome-wide antibody profiling.
      )
      Purified protein family microarray
       G protein-coupled receptors31584%Mammalian cell lines(
      • Syu G.D.
      • Wang S.C.
      • Ma G.
      • Liu S.
      • Pearce D.
      • Prakash A.
      • Henson B.
      • Weng L.C.
      • Ghosh D.
      • Ramos P.
      • Eichinger D.
      • Pino I.
      • Dong X.
      • Xiao J.
      • Wang S.
      • Tao N.
      • Kim K.S.
      • Desai P.J.
      • Zhu H.
      Development and application of a high-content virion display human GPCR array.
      )
       Membrane and secrete proteins
      The authors select proteins for expression based on a secretion signal peptide or at least one transmembrane domain. They express 505 proteins in full-length and 1121 protein fragments.
      505/1121<19%E. coli(
      • Zingaretti C.
      • Arigo M.
      • Cardaci A.
      • Moro M.
      • Crosti M.
      • Sinisi A.
      • Sugliano E.
      • Cheroni C.
      • Marabita F.
      • Nogarotto R.
      • Bonnal R.J.
      • Marcatili P.
      • Marconi M.
      • Zignego A.
      • Muratori P.
      • Invernizzi P.
      • Colombatto P.
      • Brunetto M.
      • Bonino F.
      • De Francesco R.
      • Geginat J.
      • Pagani M.
      • Muratori L.
      • Abrignani S.
      • Bombaci M.
      Identification of new autoantigens by protein array indicates a role for IL4 neutralization in autoimmune hepatitis.
      )
       Influenza (HA antigens)283NABaculovirus or human cell(
      • Nakajima R.
      • Supnet M.
      • Jasinskas A.
      • Jain A.
      • Taghavian O.
      • Obiero J.
      • Milton D.K.
      • Chen W.H.
      • Grantham M.
      • Webby R.
      • Krammer F.
      • Carter D.
      • Felgner P.L.
      • Davies D.H.
      Protein microarray analysis of the specificity and cross-reactivity of influenza virus hemagglutinin-specific antibodies.
      ,
      • Desbien A.L.
      • Van Hoeven N.
      • Reed S.J.
      • Casey A.C.
      • Laurance J.D.
      • Baldwin S.L.
      • Duthie M.S.
      • Reed S.G.
      • Carter D.
      Development of a high density hemagglutinin protein microarray to determine the breadth of influenza antibody responses.
      )
       HIV (gp120 and gp140)10NAMammalian or insect cell(
      • Dotsey E.Y.
      • Gorlani A.
      • Ingale S.
      • Achenbach C.J.
      • Forthal D.N.
      • Felgner P.L.
      • Gach J.S.
      A high throughput protein microarray approach to classify HIV monoclonal antibodies and variant antigens.
      )
      Purified protein domain microarray
       Protein domains∼400NAE. coli(
      • Jones R.B.
      • Gordus A.
      • Krall J.A.
      • MacBeath G.
      A quantitative protein interaction network for the ErbB receptors using protein microarrays.
      ,
      • Sjoberg R.
      • Sundberg M.
      • Gundberg A.
      • Sivertsson A.
      • Schwenk J.M.
      • Uhlen M.
      • Nilsson P.
      Validation of affinity reagents using antigen microarrays.
      )
       Protein epitope signature tags21,120NAE. coli(
      • Ayoglu B.
      • Haggmark A.
      • Khademi M.
      • Olsson T.
      • Uhlen M.
      • Schwenk J.M.
      • Nilsson P.
      Autoantibody profiling in multiple sclerosis using arrays of human protein fragments.
      ,
      • Sjoberg R.
      • Mattsson C.
      • Andersson E.
      • Hellstrom C.
      • Uhlen M.
      • Schwenk J.M.
      • Ayoglu B.
      • Nilsson P.
      Exploration of high-density protein microarrays for antibody validation and autoimmunity profiling.
      )
       Consensus sequence
      Designed 44 consensus coding sequences from 3,604 different dengue strains.
      44NAE. coli(
      • Qi H.
      • Zhou H.
      • Czajkowsky D.M.
      • Guo S.
      • Li Y.
      • Wang N.
      • Shi Y.
      • Lin L.
      • Wang J.
      • Wu Tao S.C.
      Rapid production of virus protein microarray using protein microarray fabrication through gene synthesis (PAGES).
      )
      Cell-free protein/peptide microarray
       Various pathogen antigens
      Pathogens included: Borrelia burgdorferi, Coxiella burnetiid, Burkholderia pseudomallei, Schistosoma japonicum, Chlamydia trachomatis, Bartonella henselae, Brucella melitensis, Hookworm Necator americanus, Leptospira interrogans, Plasmodium vivax, Schistosoma mansoni, Francisella tularensis, Toxoplasma gondii, Cytauxzoon felis, Plasmodium falciparum, Candida albicans, Mycobacterium tuberculosis, Salmonella enterica Typhi, Human papillomaviruses, and herpes simplex viruses 1&2.
      100–750010–90%In vitro expression(
      • Liang L.
      • Felgner P.L.
      A systems biology approach for diagnostic and vaccine antigen discovery in tropical infectious diseases.
      ,
      • Vigil A.
      • Davies D.H.
      • Felgner P.L.
      Defining the humoral immune response to infectious agents using high-density protein microarrays.
      )
       Nucleic acid programmable∼10,000NAIn vitro expression(
      • Miersch S.
      • Bian X.
      • Wallstrom G.
      • Sibani S.
      • Logvinenko T.
      • Wasserfall C.H.
      • Schatz D.
      • Atkinson M.
      • Qiu J.
      • LaBaer J.
      Serological autoantibody profiling of type 1 diabetes by protein arrays.
      • Ramachandran N.
      • Hainsworth E.
      • Bhullar B.
      • Eisenstein S.
      • Rosen B.
      • Lau A.Y.
      • Walter J.C.
      • LaBaer J.
      Self-assembling protein microarrays.
      )
      a Commercialized with the trademark HuProtTM by CDI Laboratories and expended to >21,000 proteins in version 4.
      b The authors select proteins for expression based on a secretion signal peptide or at least one transmembrane domain. They express 505 proteins in full-length and 1121 protein fragments.
      c Designed 44 consensus coding sequences from 3,604 different dengue strains.
      d Pathogens included: Borrelia burgdorferi, Coxiella burnetiid, Burkholderia pseudomallei, Schistosoma japonicum, Chlamydia trachomatis, Bartonella henselae, Brucella melitensis, Hookworm Necator americanus, Leptospira interrogans, Plasmodium vivax, Schistosoma mansoni, Francisella tularensis, Toxoplasma gondii, Cytauxzoon felis, Plasmodium falciparum, Candida albicans, Mycobacterium tuberculosis, Salmonella enterica Typhi, Human papillomaviruses, and herpes simplex viruses 1&2.

      Development of the Functional Protein Microarray

      The proteome is the entire set of proteins that can be expressed by a genome. The development of a purified proteome microarray usually requires assembly of a genome-wide collection of open reading frames (ORFs) cloned into an expression vector, expression of the encoded proteins in cells, individual protein purification in a high-throughput fashion, and immobilization of the proteins on a microarray. Advances in purified proteome microarrays for model organisms, such as S. cerevisiae, E. coli, humans, and Arabidopsis thaliana, have propelled functional and biochemical studies of proteins to a proteomic level. The first of its kind is the S. cerevisiae (budding yeast) proteome array, developed by the Snyder group in 2001 and containing 5,800 full length yeast proteins (
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      ). Currently, there are many purified proteome microarrays covering a wide variety of model systems, including coronaviruses (
      • Zhu H.
      • Hu S.
      • Jona G.
      • Zhu X.
      • Kreiswirth N.
      • Willey B.M.
      • Mazzulli T.
      • Liu G.
      • Song Q.
      • Chen P.
      • Cameron M.
      • Tyler A.
      • Wang J.
      • Wen J.
      • Chen W.
      • Compton S.
      • Snyder M.
      Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray.
      ), flaviviruses (
      • Song G.
      • Rho H.S.
      • Pan J.
      • Ramos P.
      • Yoon K.J.
      • Medina F.A.
      • Lee E.M.
      • Eichinger D.
      • Ming G.L.
      • Munoz-Jordan J.L.
      • Tang H.
      • Pino I.
      • Song H.
      • Qian J.
      • Zhu H.
      Multiplexed biomarker panels discriminate Zika and Dengue virus infection in humans.
      ), human herpesviruses (
      • Zhu J.
      • Liao G.
      • Shan L.
      • Zhang J.
      • Chen M.R.
      • Hayward G.S.
      • Hayward S.D.
      • Desai P.
      • Zhu H.
      Protein array identification of substrates of the Epstein-Barr virus protein kinase BGLF4.
      ), M. tuberculosis (
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      ), E. coli K12 (
      • Chen C.S.
      • Korobkova E.
      • Chen H.
      • Zhu J.
      • Jian X.
      • Tao S.C.
      • He C.
      • Zhu H.
      A proteome chip approach reveals new DNA damage recognition activities in Escherichia coli.
      ), S. cerevisiae (
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      ), Arabidopsis thaliana (
      • Popescu S.C.
      • Popescu G.V.
      • Bachan S.
      • Zhang Z.
      • Seay M.
      • Gerstein M.
      • Snyder M.
      • Dinesh-Kumar S.P.
      Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays.
      ,
      • Manohar M.
      • Tian M.
      • Moreau M.
      • Park S.W.
      • Choi H.W.
      • Fei Z.
      • Friso G.
      • Asif M.
      • Manosalva P.
      • von Dahl C.C.
      • Shi K.
      • Ma S.
      • Dinesh-Kumar S.P.
      • O'Doherty I.
      • Schroeder F.C.
      • van Wijk K.J.
      • Klessig D.F.
      Identification of multiple salicylic acid-binding proteins using two high throughput screens.
      ), and humans (
      • Jeong J.S.
      • Jiang L.
      • Albino E.
      • Marrero J.
      • Rho H.S.
      • Hu J.
      • Hu S.
      • Vera C.
      • Bayron-Poueymiroy D.
      • Rivera-Pacheco Z.A.
      • Ramos L.
      • Torres-Castro C.
      • Qian J.
      • Bonaventura J.
      • Boeke J.D.
      • Yap W.Y.
      • Pino I.
      • Eichinger D.J.
      • Zhu H.
      • Blackshaw S.
      Rapid identification of monospecific monoclonal antibodies using a human proteome microarray.
      ,
      • Hu S.
      • Xie Z.
      • Onishi A.
      • Yu X.
      • Jiang L.
      • Lin J.
      • Rho H.S.
      • Woodard C.
      • Wang H.
      • Jeong J.S.
      • Long S.
      • He X.
      • Wade H.
      • Blackshaw S.
      • Qian J.
      • Zhu H.
      Profiling the human protein-DNA interactome reveals ERK2 as a transcriptional repressor of interferon signaling.
      ). Because of the coverage of ORF collections and the efficiency of protein expression/purification, the proteome coverage on such arrays ranges from 56% to 95% (Table I). The choice of protein expression system greatly influences post-translational modifications and can affect the success rate of protein purification. For example, because of a lack of eukaryotic posttranslational modifications and chaperones, proteins encoded by C. elegans were poorly expressed in E. coli, with an expression rate of 48%. Of this 48%, only 15% were soluble (
      • Luan C.H.
      • Qiu S.
      • Finley J.B.
      • Carson M.
      • Gray R.J.
      • Huang W.
      • Johnson D.
      • Tsao J.
      • Reboul J.
      • Vaglio P.
      • Hill D.E.
      • Vidal M.
      • Delucas L.J.
      • Luo M.
      High-throughput expression of C. elegans proteins.
      ). Therefore, homologous expression systems are generally preferred to obtain the highest protein activity and expression efficiency. The S. cerevisiae, E. coli, and Arabidopsis thaliana proteome arrays are three of the best examples for use as homologues expression systems. In some cases, especially with mammalian cells, it is difficult and expensive to transfect cells, and thus one can use an alternative expression system, such as budding yeast, to accommodate protein production pipelines. Indeed, the human proteome microarray (i.e. HuProt) is one of the best examples to use a heterologous expression system, as it exhibits the most comprehensive human proteome collection purified from yeast (81% proteome coverage). Another commercial human proteome microarray, called ProtoArray, contained >9,000 human proteins purified from insect cells (43% proteome coverage), but was discontinued in 2018.
      A protein family microarray is designed to interrogate specialized groups of proteins for their biochemical functions. Today, there are many different protein family microarrays, each used for different purposes. For example, one can utilize a G-protein coupled receptor (GPCR) array for pharmaceutical applications (
      • Syu G.D.
      • Wang S.C.
      • Ma G.
      • Liu S.
      • Pearce D.
      • Prakash A.
      • Henson B.
      • Weng L.C.
      • Ghosh D.
      • Ramos P.
      • Eichinger D.
      • Pino I.
      • Dong X.
      • Xiao J.
      • Wang S.
      • Tao N.
      • Kim K.S.
      • Desai P.J.
      • Zhu H.
      Development and application of a high-content virion display human GPCR array.
      ), a membrane/secreted protein array for profiling autoantibodies (
      • Zingaretti C.
      • Arigo M.
      • Cardaci A.
      • Moro M.
      • Crosti M.
      • Sinisi A.
      • Sugliano E.
      • Cheroni C.
      • Marabita F.
      • Nogarotto R.
      • Bonnal R.J.
      • Marcatili P.
      • Marconi M.
      • Zignego A.
      • Muratori P.
      • Invernizzi P.
      • Colombatto P.
      • Brunetto M.
      • Bonino F.
      • De Francesco R.
      • Geginat J.
      • Pagani M.
      • Muratori L.
      • Abrignani S.
      • Bombaci M.
      Identification of new autoantigens by protein array indicates a role for IL4 neutralization in autoimmune hepatitis.
      ), a hemagglutinin antigen array for investigating influenza vaccines (
      • Nakajima R.
      • Supnet M.
      • Jasinskas A.
      • Jain A.
      • Taghavian O.
      • Obiero J.
      • Milton D.K.
      • Chen W.H.
      • Grantham M.
      • Webby R.
      • Krammer F.
      • Carter D.
      • Felgner P.L.
      • Davies D.H.
      Protein microarray analysis of the specificity and cross-reactivity of influenza virus hemagglutinin-specific antibodies.
      ,
      • Desbien A.L.
      • Van Hoeven N.
      • Reed S.J.
      • Casey A.C.
      • Laurance J.D.
      • Baldwin S.L.
      • Duthie M.S.
      • Reed S.G.
      • Carter D.
      Development of a high density hemagglutinin protein microarray to determine the breadth of influenza antibody responses.
      ), and a gp120/140 array from HIV for analyzing immune responses (
      • Dotsey E.Y.
      • Gorlani A.
      • Ingale S.
      • Achenbach C.J.
      • Forthal D.N.
      • Felgner P.L.
      • Gach J.S.
      A high throughput protein microarray approach to classify HIV monoclonal antibodies and variant antigens.
      ). Because most protein family microarrays have a relatively small number of proteins, the expression system can be tailored for desired qualities and quantities. For example, the GPCR array is developed using Virion Display (VirD) technology (
      • Hu S.
      • Feng Y.
      • Henson B.
      • Wang B.
      • Huang X.
      • Li M.
      • Desai P.
      • Zhu H.
      VirD: a virion display array for profiling functional membrane proteins.
      ) to maintain the seven transmembrane structure and to obtain the best GPCR expression in several mammalian cell lines, including Vero, HEL, HeLa, and 293T cells (
      • Syu G.D.
      • Wang S.C.
      • Ma G.
      • Liu S.
      • Pearce D.
      • Prakash A.
      • Henson B.
      • Weng L.C.
      • Ghosh D.
      • Ramos P.
      • Eichinger D.
      • Pino I.
      • Dong X.
      • Xiao J.
      • Wang S.
      • Tao N.
      • Kim K.S.
      • Desai P.J.
      • Zhu H.
      Development and application of a high-content virion display human GPCR array.
      ).
      Alternatively, protein domain microarrays can be designed to analyze certain regions, domains, or epitopes within the proteins. These arrays often involve the careful design of desired gene sequences before entering the protein production pipeline. Protein domain arrays, Protein Epitope Signature Tag (PrEST) arrays, and consensus sequence protein arrays are the three best examples of this sort. The protein domain arrays reported by Jones et al. contain all the human Src homology 2 and phosphotyrosine binding domains to profile the interaction networks for tyrosine phosphorylation on ErbB receptors (
      • Jones R.B.
      • Gordus A.
      • Krall J.A.
      • MacBeath G.
      A quantitative protein interaction network for the ErbB receptors using protein microarrays.
      ). PrEST arrays contain the unique signature in the human proteome developed by the Human Protein Atlas Consortium for identifying multiple sclerosis autoantibodies (
      • Ayoglu B.
      • Haggmark A.
      • Khademi M.
      • Olsson T.
      • Uhlen M.
      • Schwenk J.M.
      • Nilsson P.
      Autoantibody profiling in multiple sclerosis using arrays of human protein fragments.
      ) or for validating antibody specificity (
      • Sjoberg R.
      • Mattsson C.
      • Andersson E.
      • Hellstrom C.
      • Uhlen M.
      • Schwenk J.M.
      • Ayoglu B.
      • Nilsson P.
      Exploration of high-density protein microarrays for antibody validation and autoimmunity profiling.
      ). In a consensus sequence protein array, Qi et al. summarize 44 consensus serotype sequences out of 3604 different dengue strains and construct a protein array accordingly for dengue serotyping (
      • Qi H.
      • Zhou H.
      • Czajkowsky D.M.
      • Guo S.
      • Li Y.
      • Wang N.
      • Shi Y.
      • Lin L.
      • Wang J.
      • Wu Tao S.C.
      Rapid production of virus protein microarray using protein microarray fabrication through gene synthesis (PAGES).
      ). Overall, both purified proteome, protein family, and protein domain arrays have a wide variety of applications in basic and translational research, as well as pharmaceutical industry.
      The cell-free protein/peptide microarray is designed to display a short peptide or full-length protein using a cell-free system. Cell-free expression is designed to bypass the expensive and often tedious work of cell-based protein production. To construct protein assays with an in vitro expression, many expression systems, including expression lysate from E. coli, insect cells, wheat germs, and human cells, are commercially available. For instance, the Felgner Lab established various pathogen arrays ranging from viruses to bacteria and yeasts by using an in vitro transcription and translation (IVTT) system adopted from E. coli (Table I and footnote) (
      • Liang L.
      • Felgner P.L.
      A systems biology approach for diagnostic and vaccine antigen discovery in tropical infectious diseases.
      ,
      • Vigil A.
      • Davies D.H.
      • Felgner P.L.
      Defining the humoral immune response to infectious agents using high-density protein microarrays.
      ). On the other hand, the LaBaer group utilized a DNA array, dubbed as the Nucleic Acid Programmable Protein Array (NAPPA), to construct human proteome arrays using in vitro transcription/translation system (
      • Miersch S.
      • Bian X.
      • Wallstrom G.
      • Sibani S.
      • Logvinenko T.
      • Wasserfall C.H.
      • Schatz D.
      • Atkinson M.
      • Qiu J.
      • LaBaer J.
      Serological autoantibody profiling of type 1 diabetes by protein arrays.
      ,
      • Ramachandran N.
      • Raphael J.V.
      • Hainsworth E.
      • Demirkan G.
      • Fuentes M.G.
      • Rolfs A.
      • Hu Y.
      • LaBaer J.
      Next-generation high-density self-assembling functional protein arrays.
      ,
      • Ramachandran N.
      • Hainsworth E.
      • Bhullar B.
      • Eisenstein S.
      • Rosen B.
      • Lau A.Y.
      • Walter J.C.
      • LaBaer J.
      Self-assembling protein microarrays.
      ). Because cell-free expression lacks regulated protein folding, segregated cellular compartments, and coordinated post-translational modifications (PTMs), the protein functions are not guaranteed (
      • Ramachandran N.
      • Raphael J.V.
      • Hainsworth E.
      • Demirkan G.
      • Fuentes M.G.
      • Rolfs A.
      • Hu Y.
      • LaBaer J.
      Next-generation high-density self-assembling functional protein arrays.
      ). The IVTT system also suffers from a lower yield of larger proteins (e.g. >50 kDa), potential contamination by other proteins presented in the lysates, and low array density (e.g. ∼2,000 features per array) (
      • Ramachandran N.
      • Raphael J.V.
      • Hainsworth E.
      • Demirkan G.
      • Fuentes M.G.
      • Rolfs A.
      • Hu Y.
      • LaBaer J.
      Next-generation high-density self-assembling functional protein arrays.
      ). Nevertheless, protein arrays produced by cell-free expression are quite useful to analyze immune responses (
      • Liang L.
      • Felgner P.L.
      A systems biology approach for diagnostic and vaccine antigen discovery in tropical infectious diseases.
      ,
      • Vigil A.
      • Davies D.H.
      • Felgner P.L.
      Defining the humoral immune response to infectious agents using high-density protein microarrays.
      ,
      • Miersch S.
      • Bian X.
      • Wallstrom G.
      • Sibani S.
      • Logvinenko T.
      • Wasserfall C.H.
      • Schatz D.
      • Atkinson M.
      • Qiu J.
      • LaBaer J.
      Serological autoantibody profiling of type 1 diabetes by protein arrays.
      ).

      Application of Yeast Proteome Microarrays in Basic Research

      Functional protein microarrays, especially purified proteome microarrays, are useful for profiling proteome-wide molecular interactions and allow for a comprehensive, unbiased screening. In basic research, researchers have been using functional protein microarrays to study protein-protein interactions, protein-lipid interactions, protein-cell/lysates, protein-DNA interactions, protein-RNA interactions, small molecule binding, and PTMs, such as glycosylation, ubiquitylation, SUMOylation, acetylation, phosphorylation, and methylation (Fig. 1A1G). In Table II, we summarize representative studies based on the research applications illustrated in Fig. 1. Here, we review research studies based on the proteomes immobilized on microarrays.
      Figure thumbnail gr1
      Fig. 1Application of Functional Protein Microarray. Applications of functional protein microarray for interrogating protein-binding property include A, Protein-protein interactions; B, Protein-lipid interactions; C, Protein-cell/lysate interactions; D, Small molecule binding; E, Enzyme-substrate relationships; F, Protein-DNA interactions; G, Protein-RNA interactions; H, Antibody specificity/Serum profiling. PTM = post-translational modification.
      Table IIRepresentative studies using functional protein microarrays
      Classification/ResearchToolsMajor findingsRefs.
      Protein-Protein
       CalmodulinYeast proteome arrayIdentified 30 new targets(
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      )
       4 antimicrobial peptidesE. coli proteome arrayIdentified many intracellular targets(
      • Ho Y.H.
      • Shah P.
      • Chen Y.W.
      • Chen C.S.
      Systematic analysis of intracellular-targeting antimicrobial peptides, bactenecin 7, hybrid of pleurocidin and dermaseptin, proline-arginine-rich peptide, and lactoferricin B, by using Escherichia coli proteome microarrays.
      )
       2-oxohistidine peptideE. coli proteome arrayIdentified 9 redox targets(
      • Lin J.M.
      • Tsai Y.T.
      • Liu Y.H.
      • Lin Y.
      • Tai H.C.
      • Chen C.S.
      Identification of 2-oxohistidine interacting proteins using E. coli proteome chips.
      )
       NS5AHuProtIdentified 90 targets and validated Pim1(
      • Park C.
      • Min S.
      • Park E.M.
      • Lim Y.S.
      • Kang S.
      • Suzuki T.
      • Shin E.C.
      • Hwang S.B.
      Pim kinase interacts with nonstructural 5A protein and regulates hepatitis C virus entry.
      )
       PknGHuProtIdentified 125 targets and validated CypA(
      • Wu F.L.
      • Liu Y.
      • Zhang H.N.
      • Jiang H.W.
      • Cheng L.
      • Guo S.J.
      • Deng J.Y.
      • Bi L.J.
      • Zhang X.E.
      • Gao H.F.
      • Tao S.C.
      Global profiling of PknG interactions using a human proteome microarray reveals novel connections with CypA.
      )
      MTB proteome arrayIdentified 59 targets(
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      )
       ROP18HuProtIdentified 68 targets and validated 4 bindings(
      • Yang Z.
      • Hou Y.
      • Hao T.
      • Rho H.S.
      • Wan J.
      • Luan Y.
      • Gao X.
      • Yao J.
      • Pan A.
      • Xie Z.
      • Qian J.
      • Liao W.
      • Zhu H.
      • Zhou X.
      A human proteome array approach to identifying key host proteins targeted by toxoplasma kinase ROP18.
      )
       SidM, LidA, and AnkXHuman NAPPAIdentified 18, 20, and 8 host targets(
      • Yu X.
      • Decker K.B.
      • Barker K.
      • Neunuebel M.R.
      • Saul J.
      • Graves M.
      • Westcott N.
      • Hang H.
      • LaBaer J.
      • Qiu J.
      • Machner M.P.
      Host-pathogen interaction profiling using self-assembling human protein arrays.
      ,
      • Yu X.
      • Noll R.R.
      • Romero Duenas B.P.
      • Allgood S.C.
      • Barker K.
      • Caplan J.L.
      • Machner M.P.
      • LaBaer J.
      • Qiu J.
      • Neunuebel M.R.
      Legionella effector AnkX interacts with host nuclear protein PLEKHN1.
      )
       61 ErbB peptidesSH2 PBD arrayProfiled interaction networks(
      • Jones R.B.
      • Gordus A.
      • Krall J.A.
      • MacBeath G.
      A quantitative protein interaction network for the ErbB receptors using protein microarrays.
      )
      Protein-Lipid
       5 PhospholipidsYeast proteome arrayIdentified 150 targets(
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      )
      Protein-Cell/Lysate
       HBMECE. coli proteome arrayIdentified 23 targets and validated YojI(
      • Feng Y.
      • Chen C.S.
      • Ho J.
      • Pearce D.
      • Hu S.
      • Wang B.
      • Desai P.
      • Kim K.S.
      • Zhu H.
      High-throughput chip assay for investigating Escherichia coli interaction with the blood-brain barrier using microbial and human proteome microarrays (Dual-Microarray Technology).
      )
       Macrophage lysateMTB proteome arrayIdentified 26 targets(
      • He X.
      • Jiang H.W.
      • Chen H.
      • Zhang H.N.
      • Liu Y.
      • Xu Z.W.
      • Wu F.L.
      • Guo S.J.
      • Hou J.L.
      • Yang M.K.
      • Yan W.
      • Deng J.Y.
      • Bi L.J.
      • Zhang X.E.
      • Tao S.C.
      Systematic identification of Mycobacterium tuberculosis effectors reveals that BfrB suppresses innate immunity.
      )
      Small Molecule Binding
       2 inhibitors of rapamycinE. coli proteome arrayIdentified 39 targets and validated Tep1p and Nir1p(
      • Huang J.
      • Zhu H.
      • Haggarty S.J.
      • Spring D.R.
      • Hwang H.
      • Jin F.
      • Snyder M.
      • Schreiber S.L.
      Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips.
      )
       ArsenicHuProtIdentified 360 targets and validated hexokinase(
      • Zhang H.N.
      • Yang L.
      • Ling J.Y.
      • Czajkowsky D.M.
      • Wang J.F.
      • Zhang X.W.
      • Zhou Y.M.
      • Ge F.
      • Yang M.K.
      • Xiong Q.
      • Guo S.J.
      • Le H.Y.
      • Wu S.F.
      • Yan W.
      • Liu B.
      • Zhu H.
      • Chen Z.
      • Tao S.C.
      Systematic identification of arsenic-binding proteins reveals that hexokinase-2 is inhibited by arsenic.
      )
       6-O-angeloylplenolinHuProtIdentified 99 targets and validated STAT3(
      • Cheng X.
      • Liu Y.Q.
      • Wang G.Z.
      • Yang L.N.
      • Lu Y.Z.
      • Li X.C.
      • Zhou B.
      • Qu L.W.
      • Wang X.L.
      • Cheng Y.X.
      • Liu J.
      • Tao S.C.
      • Zhou G.B.
      Proteomic identification of the oncoprotein STAT3 as a target of a novel Skp1 inhibitor.
      )
       Cyclic di-GMPMTB proteome arrayIdentified 30 targets(
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      )
      E. coli proteome arrayIdentified 8 targets and validated CobB(
      • Xu Z.
      • Zhang H.
      • Zhang X.
      • Jiang H.
      • Liu C.
      • Wu F.
      • Qian L.
      • Hao B.
      • Czajkowsky D.M.
      • Guo S.
      • Xu Z.
      • Bi L.
      • Wang S.
      • Li H.
      • Tan M.
      • Yan W.
      • Feng L.
      • Hou J.
      • Tao S.C.
      Interplay between the bacterial protein deacetylase CobB and the second messenger c-di-GMP.
      )
      Substrate Identification
       Six SUMO E3 ligasesHuProtIdentified 250 substrates and validated PYK2(
      • Uzoma I.
      • Hu J.
      • Cox E.
      • Xia S.
      • Zhou J.
      • Rho H.S.
      • Guzzo C.
      • Paul C.
      • Ajala O.
      • Goodwin C.R.
      • Jeong J.
      • Moore C.
      • Zhang H.
      • Meluh P.
      • Blackshaw S.
      • Matunis M.
      • Qian J.
      • Zhu H.
      Global identification of small ubiquitin-related modifier (SUMO) substrates reveals crosstalk between SUMOylation and phosphorylation promotes cell migration.
      )
       289 kinasesHuProt ver. IConstructed a high resolution kinase-substrate network(
      • Newman R.H.
      • Hu J.
      • Rho H.S.
      • Xie Z.
      • Woodard C.
      • Neiswinger J.
      • Cooper C.
      • Shirley M.
      • Clark H.M.
      • Hu S.
      • Hwang W.
      • Jeong J.S.
      • Wu G.
      • Lin J.
      • Gao X.
      • Ni Q.
      • Goel R.
      • Xia S.
      • Ji H.
      • Dalby K.N.
      • Birnbaum M.J.
      • Cole P.A.
      • Knapp S.
      • Ryazanov A.G.
      • Zack D.J.
      • Blackshaw S.
      • Pawson T.
      • Gingras A.C.
      • Desiderio S.
      • Pandey A.
      • Turk B.E.
      • Zhang J.
      • Zhu H.
      • Qian J.
      Construction of human activity-based phosphorylation networks.
      )
       Four herpesvirus kinasesHuProtIdentified a conserved host pathway for viral replication(
      • Li R.
      • Zhu J.
      • Xie Z.
      • Liao G.
      • Liu J.
      • Chen M.R.
      • Hu S.
      • Woodard C.
      • Lin J.
      • Taverna S.D.
      • Desai P.
      • Ambinder R.F.
      • Hayward G.S.
      • Qian J.
      • Zhu H.
      • Hayward S.D.
      Conserved herpesvirus kinases target the DNA damage response pathway and TIP60 histone acetyltransferase to promote virus replication.
      )
       ppGalNAc-TsHuProtIdentified 128 common substrates for glycosylation(
      • Xu Z.
      • Li X.
      • Zhou S.
      • Xie W.
      • Wang J.
      • Cheng L.
      • Wang S.
      • Guo S.
      • Xu Z.
      • Cao X.
      • Zhang M.
      • Yu B.
      • Narimatsu H.
      • Tao S.C.
      • Zhang Y.
      Systematic identification of the protein substrates of UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase-T1/T2/T3 using a human proteome microarray.
      )
       VopS and IbpAFic2Human NAPPAIdentified 21 AMPylation substrates(
      • Yu X.
      • Woolery A.R.
      • Luong P.
      • Hao Y.H.
      • Grammel M.
      • Westcott N.
      • Park J.
      • Wang J.
      • Bian X.
      • Demirkan G.
      • Hang H.C.
      • Orth K.
      • LaBaer J.
      Copper-catalyzed azide-alkyne cycloaddition (click chemistry)-based detection of global pathogen-host AMPylation on self-assembled human protein microarrays.
      )
       87 yeast kinasesYeast proteome arrayConstructed a kinase-substrate network(
      • Ptacek J.
      • Devgan G.
      • Michaud G.
      • Zhu H.
      • Zhu X.
      • Fasolo J.
      • Guo H.
      • Jona G.
      • Breitkreutz A.
      • Sopko R.
      • McCartney R.R.
      • Schmidt M.C.
      • Rachidi N.
      • Lee S.J.
      • Mah A.S.
      • Meng L.
      • Stark M.J.
      • Stern D.F.
      • De Virgilio C.
      • Tyers M.
      • Andrews B.
      • Gerstein M.
      • Schweitzer B.
      • Predki P.F.
      • Snyder M.
      Global analysis of protein phosphorylation in yeast.
      )
       Ubiquitin E3 Rsp5Yeast proteome arrayIdentified 84 substrates and validated Rnr2(
      • Lu J.Y.
      • Lin Y.Y.
      • Qian J.
      • Tao S.C.
      • Zhu J.
      • Pickart C.
      • Zhu H.
      Functional dissection of a HECT ubiquitin E3 ligase.
      )
       NuA4Yeast proteome arrayDiscovered two yeast ageing pathways involving Pck1p and Sip2(
      • Lin Y.Y.
      • Lu J.Y.
      • Zhang J.
      • Walter W.
      • Dang W.
      • Wan J.
      • Tao S.C.
      • Qian J.
      • Zhao Y.
      • Boeke J.D.
      • Berger S.L.
      • Zhu H.
      Protein acetylation microarray reveals that NuA4 controls key metabolic target regulating gluconeogenesis.
      ,
      • Lu J.Y.
      • Lin Y.Y.
      • Sheu J.C.
      • Wu J.T.
      • Lee F.J.
      • Chen Y.
      • Lin M.I.
      • Chiang F.T.
      • Tai T.Y.
      • Berger S.L.
      • Zhao Y.
      • Tsai K.S.
      • Zhu H.
      • Chuang L.M.
      • Boeke J.D.
      Acetylation of yeast AMPK controls intrinsic aging independently of caloric restriction.
      )
       Tyrosine sulfationE. coli proteome arrayIdentified 875 substrates(
      • Huang B.Y.
      • Chen P.C.
      • Chen B.H.
      • Wang C.C.
      • Liu H.F.
      • Chen Y.Z.
      • Chen C.S.
      • Yang Y.S.
      High-throughput screening of sulfated proteins by using a genome-wide proteome microarray and protein tyrosine sulfation system.
      )
       11 MTB kinasesMTB proteome arrayIdentified 1,027 interaction network(
      • Wu F.L.
      • Liu Y.
      • Jiang H.W.
      • Luan Y.Z.
      • Zhang H.N.
      • He X.
      • Xu Z.W.
      • Hou J.L.
      • Ji L.Y.
      • Xie Z.
      • Czajkowsky D.M.
      • Yan W.
      • Deng J.Y.
      • Bi L.J.
      • Zhang X.E.
      • Tao S.C.
      The Ser/Thr protein kinase protein-protein interaction map of M. tuberculosis.
      )
      Protein-DNA
       Yeast genomic DNAYeast proteome arrayIdentified 200 targets and validated Arg5,6(
      • Hall D.A.
      • Zhu H.
      • Zhu X.
      • Royce T.
      • Gerstein M.
      • Snyder M.
      Regulation of gene expression by a metabolic enzyme.
      )
       Mismatch and abasic siteE. coli proteome arrayValidated YbaZ and YbcN(
      • Chen C.S.
      • Korobkova E.
      • Chen H.
      • Zhu J.
      • Jian X.
      • Tao S.C.
      • He C.
      • Zhu H.
      A proteome chip approach reveals new DNA damage recognition activities in Escherichia coli.
      )
       Promoter DNA of fimSE. coli proteome arrayIdentified 19 targets and validated Spr(
      • Chen Y.W.
      • Teng C.H.
      • Ho Y.H.
      • Jessica Ho T.Y.
      • Huang W.C.
      • Hashimoto M.
      • Chiang I.Y.
      • Chen C.S.
      Identification of bacterial factors involved in type 1 fimbria expression using an Escherichia coli K12 proteome chip.
      )
       460 DNA motifs4,191 human arrayDiscovered many unconventional DNA-binding proteins and showed Erk2 as a transcriptional repressor(
      • Hu S.
      • Xie Z.
      • Onishi A.
      • Yu X.
      • Jiang L.
      • Lin J.
      • Rho H.S.
      • Woodard C.
      • Wang H.
      • Jeong J.S.
      • Long S.
      • He X.
      • Wade H.
      • Blackshaw S.
      • Qian J.
      • Zhu H.
      Profiling the human protein-DNA interactome reveals ERK2 as a transcriptional repressor of interferon signaling.
      )
      Protein-RNA
       BMV viral RNAYeast proteome arrayIdentified and validated Pus4 and App1's role in preventing viral spreading in tobacco(
      • Zhu J.
      • Gopinath K.
      • Murali A.
      • Yi G.
      • Hayward S.D.
      • Zhu H.
      • Kao C.
      RNA-binding proteins that inhibit RNA virus infection.
      )
       13 IncRNAsHuProtFound many unconventional RNA-binding proteins and validated IDH1(
      • Liu L.
      • Li T.
      • Song G.
      • He Q.
      • Yin Y.
      • Lu J.Y.
      • Bi X.
      • Wang K.
      • Luo S.
      • Chen Y.S.
      • Yang Y.
      • Sun B.F.
      • Yang Y.G.
      • Wu J.
      • Zhu H.
      • Shen X.
      Insight into novel RNA-binding activities via large-scale analysis of lncRNA-bound proteome and IDH1-bound transcriptome.
      )
       miR-122HuProtIdentified 40 targets and validated hnRNP K(
      • Fan B.
      • Lu K.Y.
      • Reymond Sutandy F.X.
      • Chen Y.W.
      • Konan K.
      • Zhu H.
      • Kao C.C.
      • Chen C.S.
      A human proteome microarray identifies that the heterogeneous nuclear ribonucleoprotein K (hnRNP K) recognizes the 5′ terminal sequence of the hepatitis C virus RNA.
      )
      Antibody specificity
       mAbs against TFsHuProtDemonstrated the use of HuProt for specificity test of mAbs(
      • Venkataraman A.
      • Yang K.
      • Irizarry J.
      • Mackiewicz M.
      • Mita P.
      • Kuang Z.
      • Xue L.
      • Ghosh D.
      • Liu S.
      • Ramos P.
      • Hu S.
      • Bayron Kain D.
      • Keegan S.
      • Saul R.
      • Colantonio S.
      • Zhang H.
      • Behn F.P.
      • Song G.
      • Albino E.
      • Asencio L.
      • Ramos L.
      • Lugo L.
      • Morell G.
      • Rivera J.
      • Ruiz K.
      • Almodovar R.
      • Nazario L.
      • Murphy K.
      • Vargas I.
      • Rivera-Pacheco Z.A.
      • Rosa C.
      • Vargas M.
      • McDade J.
      • Clark B.S.
      • Yoo S.
      • Khambadkone S.G.
      • de Melo J.
      • Stevanovic M.
      • Jiang L.
      • Li Y.
      • Yap W.Y.
      • Jones B.
      • Tandon A.
      • Campbell E.
      • Montelione G.T.
      • Anderson S.
      • Myers R.M.
      • Boeke J.D.
      • Fenyo D.
      • Whiteley G.
      • Bader J.S.
      • Pino I.
      • Eichinger D.J.
      • Zhu H.
      • Blackshaw S.
      A toolbox of immunoprecipitation-grade monoclonal antibodies to human transcription factors.
      )
       400 Abs against SH2SH2 PrESTs arrayVerified Abs specificity(
      • Sjoberg R.
      • Sundberg M.
      • Gundberg A.
      • Sivertsson A.
      • Schwenk J.M.
      • Uhlen M.
      • Nilsson P.
      Validation of affinity reagents using antigen microarrays.
      )
      mAbs = monoclonal antibodies.
      Zhu et al. constructed the very first proteome microarray, the yeast proteome microarray, and utilized it to investigate protein-protein interactions and protein-lipid interactions. The array was probed with biotinylated calmodulin and 33 new calmodulin binding proteins with new common motifs were identified (
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      ). In the same study, the yeast proteome array was probed with fluorescently labeled liposomes carrying various phosphatidyl-inositides and more than 150 phospholipid binding proteins were identified (
      • Zhu H.
      • Bilgin M.
      • Bangham R.
      • Hall D.
      • Casamayor A.
      • Bertone P.
      • Lan N.
      • Jansen R.
      • Bidlingmaier S.
      • Houfek T.
      • Mitchell T.
      • Miller P.
      • Dean R.A.
      • Gerstein M.
      • Snyder M.
      Global analysis of protein activities using proteome chips.
      ). Huang et al. used the same microarray to identify binding proteins for two small molecule inhibitors of rapamycin, SMIR3 and SMIR4, and identified 8 and 30 protein targets, respectively. Most target proteins were involved in PI3,4P2 signaling (
      • Huang J.
      • Zhu H.
      • Haggarty S.J.
      • Spring D.R.
      • Hwang H.
      • Jin F.
      • Snyder M.
      • Schreiber S.L.
      Finding new components of the target of rapamycin (TOR) signaling network through chemical genetics and proteome chips.
      ). Hall et al. used the yeast proteome microarray to profile DNA binding proteins and revealed a mitochondrial enzyme, Arg5,6, can regulate both nuclear and mitochondrial gene expression (
      • Hall D.A.
      • Zhu H.
      • Zhu X.
      • Royce T.
      • Gerstein M.
      • Snyder M.
      Regulation of gene expression by a metabolic enzyme.
      ). Similarly, Zhu et al. used the yeast proteome microarray to profile RNA hairpin binding proteins and identified two proteins: Pus4 and App1. Their antiviral activity against the spread of brome mosaic virus was demonstrated in tobacco (
      • Zhu J.
      • Gopinath K.
      • Murali A.
      • Yi G.
      • Hayward S.D.
      • Zhu H.
      • Kao C.
      RNA-binding proteins that inhibit RNA virus infection.
      ). The Zhu lab further demonstrated the utility of proteome arrays by performing covalent enzymatic reactions on the arrays. They were the first to establish the protein acetylation reactions using the yeast NuA4 complex, and two parallel signaling pathways in yeast aging were discovered (
      • Lin Y.Y.
      • Lu J.Y.
      • Zhang J.
      • Walter W.
      • Dang W.
      • Wan J.
      • Tao S.C.
      • Qian J.
      • Zhao Y.
      • Boeke J.D.
      • Berger S.L.
      • Zhu H.
      Protein acetylation microarray reveals that NuA4 controls key metabolic target regulating gluconeogenesis.
      ). It has also been applied to determine the substrates of a HECT domain ubiquitin E3 ligase Rsp5 (
      • Lu J.Y.
      • Lin Y.Y.
      • Qian J.
      • Tao S.C.
      • Zhu J.
      • Pickart C.
      • Zhu H.
      Functional dissection of a HECT ubiquitin E3 ligase.
      ). These studies demonstrate the usefulness of the yeast proteome microarray in basic research.

      Application of E. coli Proteome Microarrays in Basic Research

      Chen et al. established a purified E. coli proteome microarray in 2008, comprising of 4256 unique proteins and applied it to identify potential new players in the DNA damage response. The E. coli proteome microarray was probed with several short DNA probes containing mismatched base pairs or abasic sites, and two DNA repair proteins were identified: YbaZ and YbcN (
      • Chen C.S.
      • Korobkova E.
      • Chen H.
      • Zhu J.
      • Jian X.
      • Tao S.C.
      • He C.
      • Zhu H.
      A proteome chip approach reveals new DNA damage recognition activities in Escherichia coli.
      ). In another study the same array was used to detect DNA binding proteins to the promoter of type 1 fimbriae and identified Spr as a phase switch for type 1 fimbria expression (
      • Chen Y.W.
      • Teng C.H.
      • Ho Y.H.
      • Jessica Ho T.Y.
      • Huang W.C.
      • Hashimoto M.
      • Chiang I.Y.
      • Chen C.S.
      Identification of bacterial factors involved in type 1 fimbria expression using an Escherichia coli K12 proteome chip.
      ). Ho et al. probed several antimicrobial peptides using the E. coli proteome array and identified many intracellular targets. Among the four antimicrobial peptides, they identified some shared and unique targets and suggested a synergistic effect on LfcinB and Bac7, as well as LfcinB and PR-39 (
      • Ho Y.H.
      • Shah P.
      • Chen Y.W.
      • Chen C.S.
      Systematic analysis of intracellular-targeting antimicrobial peptides, bactenecin 7, hybrid of pleurocidin and dermaseptin, proline-arginine-rich peptide, and lactoferricin B, by using Escherichia coli proteome microarrays.
      ). Hsiao et al. probed the E. coli proteome array with four glycosaminoglycans that are common on host cells and identified a hundred protein targets. They further validated ycbS as a bacterial factor for cell entry (
      • Hsiao F.S.
      • Sutandy F.R.
      • Syu G.D.
      • Chen Y.W.
      • Lin J.M.
      • Chen C.S.
      Systematic protein interactome analysis of glycosaminoglycans revealed YcbS as a novel bacterial virulence factor.
      ). Xu et al. probed the E. coli proteome array with an important bacterial second messenger, cyclic di-GMP, and identified CobB as a strong binder. Because CobB is a deacetylation enzyme, they subsequently found that cyclic di-GMP inhibits the enzymatic activity and forms a novel feedback loop to the cyclic di-GMP production (
      • Xu Z.
      • Zhang H.
      • Zhang X.
      • Jiang H.
      • Liu C.
      • Wu F.
      • Qian L.
      • Hao B.
      • Czajkowsky D.M.
      • Guo S.
      • Xu Z.
      • Bi L.
      • Wang S.
      • Li H.
      • Tan M.
      • Yan W.
      • Feng L.
      • Hou J.
      • Tao S.C.
      Interplay between the bacterial protein deacetylase CobB and the second messenger c-di-GMP.
      ). Feng et al. used E. coli proteome microarray to investigate protein-cell interactions by probing the human brain microvascular endothelial cells (HBMEC) on the array. They identified 23 target proteins and validated YojI as a protein for E. coli invasion. Moreover, they purified Yojl, probed using HuProt, and further identified interferon-alpha receptor as a host receptor for Yojl (
      • Feng Y.
      • Chen C.S.
      • Ho J.
      • Pearce D.
      • Hu S.
      • Wang B.
      • Desai P.
      • Kim K.S.
      • Zhu H.
      High-throughput chip assay for investigating Escherichia coli interaction with the blood-brain barrier using microbial and human proteome microarrays (Dual-Microarray Technology).
      ). Besides various binding assays, the E. coli proteome microarray has also been applied to identify substrates, including substrates of glycoproteins (
      • Wang Z.X.
      • Deng R.P.
      • Jiang H.W.
      • Guo S.J.
      • Le H.Y.
      • Zhao X.D.
      • Chen C.S.
      • Zhang J.B.
      • Tao S.C.
      Global identification of prokaryotic glycoproteins based on an Escherichia coli proteome microarray.
      ), tyrosine sulfation (
      • Huang B.Y.
      • Chen P.C.
      • Chen B.H.
      • Wang C.C.
      • Liu H.F.
      • Chen Y.Z.
      • Chen C.S.
      • Yang Y.S.
      High-throughput screening of sulfated proteins by using a genome-wide proteome microarray and protein tyrosine sulfation system.
      ), and ClpYQ protease (
      • Tsai C.H.
      • Ho Y.H.
      • Sung T.C.
      • Wu W.F.
      • Chen C.S.
      Escherichia coli proteome microarrays identified the substrates of ClpYQ protease.
      ). As demonstrated by these representative works, the E. coli proteome microarray is widely used to study bacterial physiology as well as host-microbial interactions.

      Application of Human Proteome Microarrays in Basic Research

      The human proteome microarray is the most widely used array in basic research, translational research, and in the pharmaceutical industry. There are three popular human proteome microarrays: HuProt, ProtoArray, and NAPPA. HuProt contains ∼21,000 individual purified human proteins in full-length, which is by far the most comprehensive human proteome collection. ProtoArray contained ∼9000 human proteins purified from insect cells, but was discontinued commercially in 2018. NAPPA is an in vitro expression system that has been applied to express 10,000 human proteins.
      The HuProt array was not made overnight. In its early stages, it contained 4191 unique human proteins, mostly transcription factors and co-factors. Hu et al. performed a large scale DNA-binding assay with 460 DNA motifs on this array and found 17,718 protein-DNA interactions. Not only were numerous known protein-DNA interactions recovered, but they also found many unconventional DNA-binding proteins, including a mitogen-activated protein kinase (MAPK), Erk2. In-depth mutagenesis studies and cell-based assays demonstrated that Erk2 acts as a transcriptional repressor in the regulation of interferon-gamma signaling (
      • Hu S.
      • Xie Z.
      • Onishi A.
      • Yu X.
      • Jiang L.
      • Lin J.
      • Rho H.S.
      • Woodard C.
      • Wang H.
      • Jeong J.S.
      • Long S.
      • He X.
      • Wade H.
      • Blackshaw S.
      • Qian J.
      • Zhu H.
      Profiling the human protein-DNA interactome reveals ERK2 as a transcriptional repressor of interferon signaling.
      ). In 2012, the Zhu lab published the construction of HuProt version I, which contained 16,368 individual purified human proteins in full-length and demonstrated that it could serve as a useful tool to identify highly specific monoclonal antibodies (
      • Jeong J.S.
      • Jiang L.
      • Albino E.
      • Marrero J.
      • Rho H.S.
      • Hu J.
      • Hu S.
      • Vera C.
      • Bayron-Poueymiroy D.
      • Rivera-Pacheco Z.A.
      • Ramos L.
      • Torres-Castro C.
      • Qian J.
      • Bonaventura J.
      • Boeke J.D.
      • Yap W.Y.
      • Pino I.
      • Eichinger D.J.
      • Zhu H.
      • Blackshaw S.
      Rapid identification of monospecific monoclonal antibodies using a human proteome microarray.
      ). The work laid the foundation for the NIH-funded Protein Capture Reagents Program (PCRP; https://commonfund.nih.gov/proteincapture).
      The birth of HuProt arrays expanded researchers' arsenal for interrogation of a great fraction of the entire human proteome for specific biochemical properties. For example, Liu et al. profiled the binding specificities of 13 long noncoding RNAs (lncRNAs) on HuProt to determine potential players in lncRNA-mediated biological processes. Ultimately, 671 lncRNA-binding proteins were found, 525 of which lacked any known RNA-binding domains. A novel RNA binding protein, IDH1, was further validated in cells and shown to bind thousands of RNA transcripts (
      • Liu L.
      • Li T.
      • Song G.
      • He Q.
      • Yin Y.
      • Lu J.Y.
      • Bi X.
      • Wang K.
      • Luo S.
      • Chen Y.S.
      • Yang Y.
      • Sun B.F.
      • Yang Y.G.
      • Wu J.
      • Zhu H.
      • Shen X.
      Insight into novel RNA-binding activities via large-scale analysis of lncRNA-bound proteome and IDH1-bound transcriptome.
      ). Similarly, Fan et al. probed HuProt with miR-122 and identified 40 target proteins. Because miR-122 is required for hepatitis C virus (HCV) replication, they further validated the target hnRNP K as a repressor for HCV replication (
      • Fan B.
      • Lu K.Y.
      • Reymond Sutandy F.X.
      • Chen Y.W.
      • Konan K.
      • Zhu H.
      • Kao C.C.
      • Chen C.S.
      A human proteome microarray identifies that the heterogeneous nuclear ribonucleoprotein K (hnRNP K) recognizes the 5′ terminal sequence of the hepatitis C virus RNA.
      ). Therefore, the human proteome microarray is a valuable tool to study the complex regulatory networks of protein-DNA and -RNA interactions (Fig. 1F and 1G).
      The human proteome microarray is also useful for the analysis of protein-protein interactions, especially for determining players involved in pathogen-host interactions (Fig. 1A). Park et al. probed the nonstructural 5A protein from HCV on ProtoArray and identified 90 proteins. They further validated one of these proteins, Pim1, as a factor involved in HCV cell entry (
      • Park C.
      • Min S.
      • Park E.M.
      • Lim Y.S.
      • Kang S.
      • Suzuki T.
      • Shin E.C.
      • Hwang S.B.
      Pim kinase interacts with nonstructural 5A protein and regulates hepatitis C virus entry.
      ). Yoon et al. constructed a Zika virus-host protein-protein interaction network using a similar approach and compared its dengue virus counterparts to determine Zika virus-specific interactions (
      • Yoon K.J.
      • Song G.
      • Qian X.
      • Pan J.
      • Xu D.
      • Rho H.S.
      • Kim N.S.
      • Habela C.
      • Zheng L.
      • Jacob F.
      • Zhang F.
      • Lee E.M.
      • Huang W.K.
      • Ringeling F.R.
      • Vissers C.
      • Li C.
      • Yuan L.
      • Kang K.
      • Kim S.
      • Yeo J.
      • Cheng Y.
      • Liu S.
      • Wen Z.
      • Qin C.F.
      • Wu Q.
      • Christian K.M.
      • Tang H.
      • Jin P.
      • Xu Z.
      • Qian J.
      • Zhu H.
      • Song H.
      • Ming G.L.
      Zika-virus-encoded NS2A disrupts mammalian cortical neurogenesis by degrading adherens junction proteins.
      ). Further orthogonal large-scale screenings allowed them to pinpoint drug targets in the host involved in Zika virus replication. Yang et al. investigated the binding events of T. gondii virulence factor ROP18 using HuProt and identified 68 targets. They subsequently validated the crucial role of ROP18 on p53, p38, UBE2N, and SMAD1 through phosphorylation-dependent degradation (
      • Yang Z.
      • Hou Y.
      • Hao T.
      • Rho H.S.
      • Wan J.
      • Luan Y.
      • Gao X.
      • Yao J.
      • Pan A.
      • Xie Z.
      • Qian J.
      • Liao W.
      • Zhu H.
      • Zhou X.
      A human proteome array approach to identifying key host proteins targeted by toxoplasma kinase ROP18.
      ). Wu et al. investigated the binding events of PknG, an important kinase in M. tuberculosis (MTB), using HuProt and identified 128 binding proteins. They further validated that one of these binding proteins, CypA, is degraded upon phosphorylation and subsequently inhibits inflammatory responses (
      • Wu F.L.
      • Liu Y.
      • Zhang H.N.
      • Jiang H.W.
      • Cheng L.
      • Guo S.J.
      • Deng J.Y.
      • Bi L.J.
      • Zhang X.E.
      • Gao H.F.
      • Tao S.C.
      Global profiling of PknG interactions using a human proteome microarray reveals novel connections with CypA.
      ). Using human NAPPA, Yu et al. identified 18, 20, and 8 host proteins that interact with L. pneumophila effectors SidM, LidA, and AnkX, respectively (
      • Yu X.
      • Decker K.B.
      • Barker K.
      • Neunuebel M.R.
      • Saul J.
      • Graves M.
      • Westcott N.
      • Hang H.
      • LaBaer J.
      • Qiu J.
      • Machner M.P.
      Host-pathogen interaction profiling using self-assembling human protein arrays.
      ,
      • Yu X.
      • Noll R.R.
      • Romero Duenas B.P.
      • Allgood S.C.
      • Barker K.
      • Caplan J.L.
      • Machner M.P.
      • LaBaer J.
      • Qiu J.
      • Neunuebel M.R.
      Legionella effector AnkX interacts with host nuclear protein PLEKHN1.
      ).
      Human proteome microarrays have also been widely used to study PTMs (Fig. 1E). Song et al. established methods to detect global tyrosine phosphorylation, lysine acetylation, ubiquitylation, and SUMOylation on HuProt. The HuProt arrays were incubated with cell lysates diluted in different PTM reaction buffers to perform covalent protein modifications, and the modified proteins on the array were visualized using the corresponding PTM antibodies. Among the complex regulation of PTMs in cancers, they validated the hyperactivities of PTK2 and PTK2B kinases in ovarian cancer (
      • Song G.
      • Chen L.
      • Zhang B.
      • Song Q.
      • Yu Y.
      • Moore C.
      • Wang T.L.
      • Shih I.M.
      • Zhang H.
      • Chan D.W.
      • Zhang Z.
      • Zhu H.
      Proteome-wide tyrosine phosphorylation analysis reveals dysregulated signaling pathways in ovarian tumors.
      ). Xu et al. surveyed the substrate for ppGalNAc-Ts using HuProt and identified 128 common substrates for O-GalNAc glycosylation (
      • Xu Z.
      • Li X.
      • Zhou S.
      • Xie W.
      • Wang J.
      • Cheng L.
      • Wang S.
      • Guo S.
      • Xu Z.
      • Cao X.
      • Zhang M.
      • Yu B.
      • Narimatsu H.
      • Tao S.C.
      • Zhang Y.
      Systematic identification of the protein substrates of UDP-GalNAc:polypeptide N-acetylgalactosaminyltransferase-T1/T2/T3 using a human proteome microarray.
      ). Yu et al. used human NAPPA to identify the 20 and 21 AMPylation substrates for VopS and IbpAFic2, respectively (
      • Yu X.
      • Woolery A.R.
      • Luong P.
      • Hao Y.H.
      • Grammel M.
      • Westcott N.
      • Park J.
      • Wang J.
      • Bian X.
      • Demirkan G.
      • Hang H.C.
      • Orth K.
      • LaBaer J.
      Copper-catalyzed azide-alkyne cycloaddition (click chemistry)-based detection of global pathogen-host AMPylation on self-assembled human protein microarrays.
      ). Overall, the human proteome microarray serves as an unbiased platform for studying many kinds of binding events and enzyme-substrate relationships.
      The two major pharmaceutical applications of the human proteome microarray are drug target identification (Fig. 1D) and specificity tests for monoclonal antibodies (mAbs) (Fig. 1H). HuProt was used to identify the targets of arsenic, a cancer drug, and 360 potential binders were identified. Hexokinase was validated to bind arsenic, and this binding event was further shown to result in the inhibition of glycolysis (
      • Zhang H.N.
      • Yang L.
      • Ling J.Y.
      • Czajkowsky D.M.
      • Wang J.F.
      • Zhang X.W.
      • Zhou Y.M.
      • Ge F.
      • Yang M.K.
      • Xiong Q.
      • Guo S.J.
      • Le H.Y.
      • Wu S.F.
      • Yan W.
      • Liu B.
      • Zhu H.
      • Chen Z.
      • Tao S.C.
      Systematic identification of arsenic-binding proteins reveals that hexokinase-2 is inhibited by arsenic.
      ). With a similar strategy, Cheng et al. screened the targets of 6-O-angeloylplenolin, a drug that induces cell cycle arrest, and identified 99 proteins. The proteins Skp1 and STAT3 were further validated to show involvement in cell cycle arrest (
      • Cheng X.
      • Liu Y.Q.
      • Wang G.Z.
      • Yang L.N.
      • Lu Y.Z.
      • Li X.C.
      • Zhou B.
      • Qu L.W.
      • Wang X.L.
      • Cheng Y.X.
      • Liu J.
      • Tao S.C.
      • Zhou G.B.
      Proteomic identification of the oncoprotein STAT3 as a target of a novel Skp1 inhibitor.
      ). Because the mAb-based biologicals are one of the fastest growing therapeutic modalities, quality control is extremely important. Many commercial mAbs, however, exhibit poor quality and have wasted $350 million annually in the United States alone (
      • Bradbury A.
      • Pluckthun A.
      Reproducibility: Standardize antibodies used in research.
      ). HuProt arrays are an ideal platform to screen mAbs for mono-specificity (
      • Michaud G.A.
      • Salcius M.
      • Zhou F.
      • Bangham R.
      • Bonin J.
      • Guo H.
      • Snyder M.
      • Predki P.F.
      • Schweitzer B.I.
      Analyzing antibody specificity with whole proteome microarrays.
      ). As such, Venkataraman et al. established a production pipeline for the mAbs against transcription factors and adapted HuProt as a primary validation tool for specificity tests (
      • Venkataraman A.
      • Yang K.
      • Irizarry J.
      • Mackiewicz M.
      • Mita P.
      • Kuang Z.
      • Xue L.
      • Ghosh D.
      • Liu S.
      • Ramos P.
      • Hu S.
      • Bayron Kain D.
      • Keegan S.
      • Saul R.
      • Colantonio S.
      • Zhang H.
      • Behn F.P.
      • Song G.
      • Albino E.
      • Asencio L.
      • Ramos L.
      • Lugo L.
      • Morell G.
      • Rivera J.
      • Ruiz K.
      • Almodovar R.
      • Nazario L.
      • Murphy K.
      • Vargas I.
      • Rivera-Pacheco Z.A.
      • Rosa C.
      • Vargas M.
      • McDade J.
      • Clark B.S.
      • Yoo S.
      • Khambadkone S.G.
      • de Melo J.
      • Stevanovic M.
      • Jiang L.
      • Li Y.
      • Yap W.Y.
      • Jones B.
      • Tandon A.
      • Campbell E.
      • Montelione G.T.
      • Anderson S.
      • Myers R.M.
      • Boeke J.D.
      • Fenyo D.
      • Whiteley G.
      • Bader J.S.
      • Pino I.
      • Eichinger D.J.
      • Zhu H.
      • Blackshaw S.
      A toolbox of immunoprecipitation-grade monoclonal antibodies to human transcription factors.
      ). Of the 5882 mAbs tested on HuProt arrays, 2000 passed the specificity tests, 1462 of which eventually passed the secondary cell-based validation for their ability to perform Western blot analysis and/or immunoprecipitation.
      Proteome microarrays other than those already mentioned can also be quite useful in basic research, such as the Arabidopsis proteome array (
      • Popescu S.C.
      • Popescu G.V.
      • Bachan S.
      • Zhang Z.
      • Seay M.
      • Gerstein M.
      • Snyder M.
      • Dinesh-Kumar S.P.
      Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays.
      ) and the MTB proteome array (
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      ) to name a few. Popescu et al. established the Arabidopsis proteome microarray and profiled the binding of calmodulin and calmodulin-like proteins (
      • Popescu S.C.
      • Popescu G.V.
      • Bachan S.
      • Zhang Z.
      • Seay M.
      • Gerstein M.
      • Snyder M.
      • Dinesh-Kumar S.P.
      Differential binding of calmodulin-related proteins to their targets revealed through high-density Arabidopsis protein microarrays.
      ). Deng et al. developed the MTB proteome microarray and used it to identify the binding partners of PknG and the protein interactions of second messenger cyclic di-GMP (
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      ). Wu et al. probed 11 serine/threonine protein kinases on the MTB proteome array and identified 492 binding proteins with 1027 network interactions (
      • Wu F.L.
      • Liu Y.
      • Jiang H.W.
      • Luan Y.Z.
      • Zhang H.N.
      • He X.
      • Xu Z.W.
      • Hou J.L.
      • Ji L.Y.
      • Xie Z.
      • Czajkowsky D.M.
      • Yan W.
      • Deng J.Y.
      • Bi L.J.
      • Zhang X.E.
      • Tao S.C.
      The Ser/Thr protein kinase protein-protein interaction map of M. tuberculosis.
      ).

      Application of Functional Protein Microarrays in Translational Research

      Serological biomarkers are valuable tools for diagnosis, prognosis and companion diagnosis in various autoimmune diseases, cancers, and infectious diseases (
      • Huang Y.
      • Zhu H.
      Protein array-based approaches for biomarker discovery in cancer.
      ,
      • Yu X.
      • Petritis B.
      • LaBaer J.
      Advancing translational research with next-generation protein microarrays.
      ). One of the early applications of functional protein microarrays was to discover new serological biomarkers for autoimmune diseases because they can serve as antigen surveying platforms to detect subtle changes in antibody composition. In a dysregulated immune system, the antibodies that are generated by humoral immunity and react with self-antigens are referred to as autoantibodies (AAbs). When a functional protein array covers most of the human proteome (e.g. HuProt), a specific AAb signature can be readily detected by probing the array with a diluted patient serum/plasma sample. When this approach is used to profile AAb signatures for a large cohort, subsequent statistical analysis can reveal potential biomarkers associated with a disease of interest (Table III). This approach has three major advantages. First, patient samples are easy to obtain and store because they are mostly in the forms of serum, plasma or body fluid. Second, detection of AAbs on a human proteome array is very sensitive and quantitative, only requiring several microliters of samples. Finally, the presence of AAbs is detectable before symptoms can be identified, making early diagnosis possible.
      Table IIIFunctional protein microarrays for biomarker idenitification
      Diseases/ClassificationsToolsMajor findingsRefs.
      Autoimmune diseases
       Autoimmune hepatitisPurified 5,011 human arrayValidate 3 AAbs(
      • Song Q.
      • Liu G.
      • Hu S.
      • Zhang Y.
      • Tao Y.
      • Han Y.
      • Zeng H.
      • Huang W.
      • Li F.
      • Chen P.
      • Zhu J.
      • Hu C.
      • Zhang S.
      • Li Y.
      • Zhu H.
      • Wu L.
      Novel autoimmune hepatitis-specific autoantigens identified using protein microarray technology.
      )
      Purified 1,626 human arrayValidate 6 AAbs(
      • Zingaretti C.
      • Arigo M.
      • Cardaci A.
      • Moro M.
      • Crosti M.
      • Sinisi A.
      • Sugliano E.
      • Cheroni C.
      • Marabita F.
      • Nogarotto R.
      • Bonnal R.J.
      • Marcatili P.
      • Marconi M.
      • Zignego A.
      • Muratori P.
      • Invernizzi P.
      • Colombatto P.
      • Brunetto M.
      • Bonino F.
      • De Francesco R.
      • Geginat J.
      • Pagani M.
      • Muratori L.
      • Abrignani S.
      • Bombaci M.
      Identification of new autoantigens by protein array indicates a role for IL4 neutralization in autoimmune hepatitis.
      )
       Ankylosing spondylitisNAPPA 3,498 humanIdentify a set of AAbs(
      • Wright C.
      • Sibani S.
      • Trudgian D.
      • Fischer R.
      • Kessler B.
      • LaBaer J.
      • Bowness P.
      Detection of multiple autoantibodies in patients with ankylosing spondylitis using nucleic acid programmable protein arrays.
      )
       Multiple sclerosis11,520 PrESTs arrayValidate 51 AAbs(
      • Ayoglu B.
      • Haggmark A.
      • Khademi M.
      • Olsson T.
      • Uhlen M.
      • Schwenk J.M.
      • Nilsson P.
      Autoantibody profiling in multiple sclerosis using arrays of human protein fragments.
      )
      ProtoArrayValidate CSF AAbs against RBPJ(
      • Querol L.
      • Clark P.L.
      • Bailey M.A.
      • Cotsapas C.
      • Cross A.H.
      • Hafler D.A.
      • Kleinstein S.H.
      • Lee J.Y.
      • Yaari G.
      • Willis S.N.
      • O'Connor K.C.
      Protein array-based profiling of CSF identifies RBPJ as an autoantigen in multiple sclerosis.
      )
       Type 1 diabetesNAPPA 10,000 humanValidate 5 AAbs(
      • Bian X.
      • Wasserfall C.
      • Wallstrom G.
      • Wang J.
      • Wang H.
      • Barker K.
      • Schatz D.
      • Atkinson M.
      • Qiu J.
      • LaBaer J.
      Tracking the antibody immunome in type 1 diabetes using protein arrays.
      )
       Alzheimer's diseaseProtoArrayValidate 10 AAbs(
      • Nagele E.
      • Han M.
      • Demarshall C.
      • Belinka B.
      • Nagele R.
      Diagnosis of Alzheimer's disease based on disease-specific autoantibody profiles in human sera.
      )
       Rheumatoid arthritisProtoArrayValidate 2 AAbs(
      • Auger I.
      • Balandraud N.
      • Rak J.
      • Lambert N.
      • Martin M.
      • Roudier J.
      New autoantigens in rheumatoid arthritis (RA): screening 8268 protein arrays with sera from patients with RA.
      )
       Sjögren's syndromeProtoArrayValidate 4 saliva AAbs(
      • Hu S.
      • Vissink A.
      • Arellano M.
      • Roozendaal C.
      • Zhou H.
      • Kallenberg C.G.
      • Wong D.T.
      Identification of autoantibody biomarkers for primary Sjogren's syndrome using protein microarrays.
      )
       Primary biliary cirrhosisHuProtValidate 6 AAbs(
      • Hu C.J.
      • Song G.
      • Huang W.
      • Liu G.Z.
      • Deng C.W.
      • Zeng H.P.
      • Wang L.
      • Zhang F.C.
      • Zhang X.
      • Jeong J.S.
      • Blackshaw S.
      • Jiang L.Z.
      • Zhu H.
      • Wu L.
      • Li Y.Z.
      Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays.
      )
       Amyotrophic lateral sclerosisProtoArrayValidate 20 AAbs(
      • May C.
      • Nordhoff E.
      • Casjens S.
      • Turewicz M.
      • Eisenacher M.
      • Gold R.
      • Bruning T.
      • Pesch B.
      • Stephan C.
      • Woitalla D.
      • Penke B.
      • Janaky T.
      • Virok D.
      • Siklos L.
      • Engelhardt J.I.
      • Meyer H.E.
      Highly immunoreactive IgG antibodies directed against a set of twenty human proteins in the sera of patients with amyotrophic lateral sclerosis identified by protein array.
      )
       Male subfertilityProtoArrayValidate AAbs against TGM4 in prostate(
      • Landegren N.
      • Sharon D.
      • Shum A.K.
      • Khan I.S.
      • Fasano K.J.
      • Hallgren A.
      • Kampf C.
      • Freyhult E.
      • Ardesjo-Lundgren B.
      • Alimohammadi M.
      • Rathsman S.
      • Ludvigsson J.F.
      • Lundh D.
      • Motrich R.
      • Rivero V.
      • Fong L.
      • Giwercman A.
      • Gustafsson J.
      • Perheentupa J.
      • Husebye E.S.
      • Anderson M.S.
      • Snyder M.
      • Kampe O.
      Transglutaminase 4 as a prostate autoantigen in male subfertility.
      )
       Juvenile idiopathic arthritisNAPPA 768 humanIdentify 18 AAbs(
      • Gibson D.S.
      • Qiu J.
      • Mendoza E.A.
      • Barker K.
      • Rooney M.E.
      • LaBaer J.
      Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays.
      )
       Behcet's diseaseHuProtValidate AAbs against CTDP1(
      • Hu C.J.
      • Pan J.B.
      • Song G.
      • Wen X.T.
      • Wu Z.Y.
      • Chen S.
      • Mo W.X.
      • Zhang F.C.
      • Qian J.
      • Zhu H.
      • Li Y.Z.
      Identification of novel biomarkers for Behcet disease diagnosis using human proteome microarray approach.
      )
       Sarcoidosis3,072 PrESTs arrayValidate 4 AAbs(
      • Haggmark A.
      • Hamsten C.
      • Wiklundh E.
      • Lindskog C.
      • Mattsson C.
      • Andersson E.
      • Lundberg I.E.
      • Gronlund H.
      • Schwenk J.M.
      • Eklund A.
      • Grunewald J.
      • Nilsson P.
      Proteomic profiling reveals autoimmune targets in sarcoidosis.
      )
      Cancers
       Ovarian cancerPurified 5,005 human arrayValidate 4 AAbs(
      • Hudson M.E.
      • Pozdnyakova I.
      • Haines K.
      • Mor G.
      • Snyder M.
      Identification of differentially expressed proteins in ovarian cancer using high-density protein microarrays.
      )
      NAPPA 5,177 tumor antigensValidate 3 AAbs(
      • Anderson K.S.
      • Cramer D.W.
      • Sibani S.
      • Wallstrom G.
      • Wong J.
      • Park J.
      • Qiu J.
      • Vitonis A.
      • LaBaer J.
      Autoantibody signature for the serologic detection of ovarian cancer.
      )
       GliomaHuProtIdentify a set of AAbs(
      • Syed P.
      • Gupta S.
      • Choudhary S.
      • Pandala N.G.
      • Atak A.
      • Richharia A.
      • Zhu K.P.M.H.
      • Epari S.
      • Noronha S.B.
      • Moiyadi A.
      • Srivastava S.
      Autoantibody profiling of glioma serum samples to identify biomarkers using human proteome arrays.
      )
       Lung cancerHuProtValidate 3 AAbs(
      • Pan J.
      • Song G.
      • Chen D.
      • Li Y.
      • Liu S.
      • Hu S.
      • Rosa C.
      • Eichinger D.
      • Pino I.
      • Zhu H.
      • Qian J.
      • Huang Y.
      Identification of serological biomarkers for early diagnosis of lung cancer using a protein array-based approach.
      )
       Gastric cancerHuProtValidate 4 AAbs(
      • Yang L.
      • Wang J.
      • Li J.
      • Zhang H.
      • Guo S.
      • Yan M.
      • Zhu Z.
      • Lan B.
      • Ding Y.
      • Xu M.
      • Li W.
      • Gu X.
      • Qi C.
      • Zhu H.
      • Shao Z.
      • Liu B.
      • Tao S.C.
      Identification of serum biomarkers for gastric cancer diagnosis using a human proteome microarray.
      )
       Bladder cancerProtoArrayValidate 2 AAbs(
      • Orenes-Pinero E.
      • Barderas R.
      • Rico D.
      • Casal J.I.
      • Gonzalez-Pisano D.
      • Navajo J.
      • Algaba F.
      • Piulats J.M.
      • Sanchez-Carbayo M.
      Serum and tissue profiling in bladder cancer combining protein and tissue arrays.
      )
       Prostate cancerPurified 123 antigenValidate 3 AAbs(
      • Adeola H.A.
      • Smith M.
      • Kaestner L.
      • Blackburn J.M.
      • Zerbini L.F.
      Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort.
      )
       Colon cancerProtoArrayValidate 3 AAbs(
      • Babel I.
      • Barderas R.
      • Diaz-Uriarte R.
      • Martinez-Torrecuadrada J.L.
      • Sanchez-Carbayo M.
      • Casal J.I.
      Identification of tumor-associated autoantigens for the diagnosis of colorectal cancer in serum using high density protein microarrays.
      )
       Breast cancerNAPPA 4,988 tumor antigensValidate 28 AAbs(
      • Anderson K.S.
      • Sibani S.
      • Wallstrom G.
      • Qiu J.
      • Mendoza E.A.
      • Raphael J.
      • Hainsworth E.
      • Montor W.R.
      • Wong J.
      • Park J.G.
      • Lokko N.
      • Logvinenko T.
      • Ramachandran N.
      • Godwin A.K.
      • Marks J.
      • Engstrom P.
      • Labaer J.
      Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer.
      )
       Myelodysplastic syndromesHuProtValidate 3 AAbs(
      • Mias G.I.
      • Chen R.
      • Zhang Y.
      • Sridhar K.
      • Sharon D.
      • Xiao L.
      • Im H.
      • Snyder M.P.
      • Greenberg P.L.
      Specific plasma autoantibody reactivity in myelodysplastic syndromes.
      )
       MeningiomasHuProtIdentify a set of AAbs(
      • Gupta S.
      • Mukherjee S.
      • Syed P.
      • Pandala N.G.
      • Choudhary S.
      • Singh V.A.
      • Singh N.
      • Zhu H.
      • Epari S.
      • Noronha S.B.
      • Moiyadi A.
      • Srivastava S.
      Evaluation of autoantibody signatures in meningioma patients using human proteome arrays.
      )
      Infectious diseases
       CoronavirusesCoronaviruses proteome arrayIdentify a set of Abs(
      • Zhu H.
      • Hu S.
      • Jona G.
      • Zhu X.
      • Kreiswirth N.
      • Willey B.M.
      • Mazzulli T.
      • Liu G.
      • Song Q.
      • Chen P.
      • Cameron M.
      • Tyler A.
      • Wang J.
      • Wen J.
      • Chen W.
      • Compton S.
      • Snyder M.
      Severe acute respiratory syndrome diagnostics using a coronavirus protein microarray.
      )
       FlavivirusesZika/Dengue proteome arrayValidate a set of Abs(
      • Song G.
      • Rho H.S.
      • Pan J.
      • Ramos P.
      • Yoon K.J.
      • Medina F.A.
      • Lee E.M.
      • Eichinger D.
      • Ming G.L.
      • Munoz-Jordan J.L.
      • Tang H.
      • Pino I.
      • Song H.
      • Qian J.
      • Zhu H.
      Multiplexed biomarker panels discriminate Zika and Dengue virus infection in humans.
      )
      M. tuberculosisPurified MTB proteome arrayIdentify 14 Abs(
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      )
      NAPPA 4,045 MTBIdentify 8 Abs(
      • Song L.
      • Wallstrom G.
      • Yu X.
      • Hopper M.
      • Van Duine J.
      • Steel J.
      • Park J.
      • Wiktor P.
      • Kahn P.
      • Brunner A.
      • Wilson D.
      • Jenny-Avital E.R.
      • Qiu J.
      • Labaer J.
      • Magee D.M.
      • Achkar J.M.
      Identification of antibody targets for tuberculosis serology using high-density nucleic acid programmable protein arrays.
      )
       Varicella zoster virusNAPPA 69 VZVIdentify 19 Abs(
      • Ceroni A.
      • Sibani S.
      • Baiker A.
      • Pothineni V.R.
      • Bailer S.M.
      • LaBaer J.
      • Haas J.
      • Campbell C.J.
      Systematic analysis of the IgG antibody immune response against varicella zoster virus (VZV) using a self-assembled protein microarray.
      )
      P. aeruginosaNAPPA 262 P. aeruginosaIdentify 12 Abs(
      • Montor W.R.
      • Huang J.
      • Hu Y.
      • Hainsworth E.
      • Lynch S.
      • Kronish J.W.
      • Ordonez C.L.
      • Logvinenko T.
      • Lory S.
      • LaBaer J.
      Genome-wide study of Pseudomonas aeruginosa outer membrane protein immunogenicity using self-assembling protein microarrays.
      )
       Herpes simplex virusHSV-1&2 proteome arrayValidate 2 Abs(
      • Kalantari-Dehaghi M.
      • Chun S.
      • Chentoufi A.A.
      • Pablo J.
      • Liang L.
      • Dasgupta G.
      • Molina D.M.
      • Jasinskas A.
      • Nakajima-Sasaki R.
      • Felgner J.
      • Hermanson G.
      • BenMohamed L.
      • Felgner P.L.
      • Davies D.H.
      Discovery of potential diagnostic and vaccine antigens in herpes simplex virus 1 and 2 by proteome-wide antibody profiling.
      )
      L. interrogansIVTT 3,359 L. interrogans arrayIdentify 191 Abs(
      • Lessa-Aquino C.
      • Wunder Jr, E.A.
      • Lindow J.C.
      • Rodrigues C.B.
      • Pablo J.
      • Nakajima R.
      • Jasinskas A.
      • Liang L.
      • Reis M.G.
      • Ko A.I.
      • Medeiros M.A.
      • Felgner P.L.
      Proteomic features predict seroreactivity against leptospiral antigens in leptospirosis patients.
      )
      S. TyphiIVTT 2,724 S. Typhi arrayIdentify 93 Abs(
      • Liang L.
      • Juarez S.
      • Nga T.V.
      • Dunstan S.
      • Nakajima-Sasaki R.
      • Davies D.H.
      • McSorley S.
      • Baker S.
      • Felgner P.L.
      Immune profiling with a Salmonella Typhi antigen microarray identifies new diagnostic biomarkers of human typhoid.
      )
      B. melitensisIVTT 3,046 B. melitensis arrayIdentify 33 Abs(
      • Liang L.
      • Tan X.
      • Juarez S.
      • Villaverde H.
      • Pablo J.
      • Nakajima-Sasaki R.
      • Gotuzzo E.
      • Saito M.
      • Hermanson G.
      • Molina D.
      • Felgner S.
      • Morrow W.J.
      • Liang X.
      • Gilman R.H.
      • Davies D.H.
      • Tsolis R.M.
      • Vinetz J.M.
      • Felgner P.L.
      Systems biology approach predicts antibody signature associated with Brucella melitensis infection in humans.
      )
       Human papillomavirusIVTT 104 HPV arrayIdentify E7 Ab in cancer(
      • Luevano M.
      • Bernard H.U.
      • Barrera-Saldana H.A.
      • Trevino V.
      • Garcia-Carranca A.
      • Villa L.L.
      • Monk B.J.
      • Tan X.
      • Davies D.H.
      • Felgner P.L.
      • Kalantari M.
      High-throughput profiling of the humoral immune responses against thirteen human papillomavirus types by proteome microarrays.
      )
      C. albicansIVTT 451 C. albicans arrayIdentify 13 Abs(
      • Mochon A.B.
      • Jin Y.
      • Kayala M.A.
      • Wingard J.R.
      • Clancy C.J.
      • Nguyen M.H.
      • Felgner P.
      • Baldi P.
      • Liu H.
      Serological profiling of a Candida albicans protein microarray reveals permanent host-pathogen interplay and stage-specific responses during candidemia.
      )
      F. TularensisIVTT 1,741 F. Tularensis arrayIdentify 15 Abs(
      • Sundaresh S.
      • Randall A.
      • Unal B.
      • Petersen J.M.
      • Belisle J.T.
      • Hartley M.G.
      • Duffield M.
      • Titball R.W.
      • Davies D.H.
      • Felgner P.L.
      • Baldi P.
      From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis.
      )
      Other diseases
       AsthmaProtoArrayValidate 4 AAbs(
      • Liu M.
      • Subramanian V.
      • Christie C.
      • Castro M.
      • Mohanakumar T.
      Immune responses to self-antigens in asthma patients: clinical and immunopathological implications.
      )
       Kawasaki diseaseE. coli proteome arrayValidate a set of AAbs(
      • Kuo H.C.
      • Huang Y.H.
      • Chung F.H.
      • Chen P.C.
      • Sung T.C.
      • Chen Y.W.
      • Hsieh K.S.
      • Chen C.S.
      • Syu G.D.
      Antibody profiling of Kawasaki Disease using Escherichia coli proteome microarrays.
      )
       PreeclampsiaE. coli proteome arrayValidate 5 AAbs(
      • Hsu T.Y.
      • Lin J.M.
      • Nguyen M.T.
      • Chung F.H.
      • Tsai C.C.
      • Cheng H.H.
      • Lai Y.J.
      • Hung H.N.
      • Chen C.S.
      Antigen analysis of pre-eclamptic plasma antibodies using Escherichia coli proteome chips.
      )
       Bipolar disorderE. coli proteome arrayValidate 6 AAbs(
      • Chen P.C.
      • Syu G.D.
      • Chung K.H.
      • Ho Y.H.
      • Chung F.H.
      • Chen P.H.
      • Lin J.M.
      • Chen Y.W.
      • Tsai S.Y.
      • Chen C.S.
      Antibody profiling of bipolar disorder using Escherichia coli proteome microarrays.
      )
       Parkinson's diseaseProtoArrayValidate 10 AAbs(
      • Han M.
      • Nagele E.
      • DeMarshall C.
      • Acharya N.
      • Nagele R.
      Diagnosis of Parkinson's disease based on disease-specific autoantibody profiles in human sera.
      )
       Osteoarthritis3,840 PrESTs arrayValidate a set of AAbs(
      • Henjes F.
      • Lourido L.
      • Ruiz-Romero C.
      • Fernandez-Tajes J.
      • Schwenk J.M.
      • Gonzalez-Gonzalez M.
      • Blanco F.J.
      • Nilsson P.
      • Fuentes M.
      Analysis of autoantibody profiles in osteoarthritis using comprehensive protein array concepts.
      )
       Chronic renal diseaseProtoArrayValidate 4 AAbs(
      • Butte A.J.
      • Sigdel T.K.
      • Wadia P.P.
      • Miklos D.B.
      • Sarwal M.M.
      Protein microarrays discover angiotensinogen and PRKRIP1 as novel targets for autoantibodies in chronic renal disease.
      )
       Inflammatory bowel diseaseProtoArrayValidate AAbs against FAM84A(
      • Vermeulen N.
      • de Beeck K.O.
      • Vermeire S.
      • Van Steen K.
      • Michiels G.
      • Ballet V.
      • Rutgeerts P.
      • Bossuyt X.
      Identification of a novel autoantigen in inflammatory bowel disease by protein microarray.
      )
      E. coli proteome arrayIdentify a set of AAbs(
      • Chen C.S.
      • Sullivan S.
      • Anderson T.
      • Tan A.C.
      • Alex P.J.
      • Brant S.R.
      • Cuffari C.
      • Bayless T.M.
      • Talor M.V.
      • Burek C.L.
      • Wang H.
      • Li R.
      • Datta L.W.
      • Wu Y.
      • Winslow R.L.
      • Zhu H.
      • Li X.
      Identification of novel serological biomarkers for inflammatory bowel disease using Escherichia coli proteome chip.
      )
       Meniere's diseaseProtoArrayIdentify 18 AAbs(
      • Kim S.H.
      • Kim J.Y.
      • Lee H.J.
      • Gi M.
      • Kim B.G.
      • Choi J.Y.
      Autoimmunity as a candidate for the etiopathogenesis of Meniere's disease: detection of autoimmune reactions and diagnostic biomarker candidate.
      )
       Chronic humoral rejectionProtoArrayNo common AAbs(
      • Porcheray F.
      • DeVito J.
      • Yeap B.Y.
      • Xue L.
      • Dargon I.
      • Paine R.
      • Girouard T.C.
      • Saidman S.L.
      • Colvin R.B.
      • Wong W.
      • Zorn E.
      Chronic humoral rejection of human kidney allografts associates with broad autoantibody responses.
      )
      AAbs = autoantibodies. AAbs if not specified, they are from blood. IVTT = in vitro transcription and translation.
      Human proteome microarrays have been used to identify diagnostic AAbs for more than 13 autoimmune diseases, including autoimmune hepatitis (
      • Zingaretti C.
      • Arigo M.
      • Cardaci A.
      • Moro M.
      • Crosti M.
      • Sinisi A.
      • Sugliano E.
      • Cheroni C.
      • Marabita F.
      • Nogarotto R.
      • Bonnal R.J.
      • Marcatili P.
      • Marconi M.
      • Zignego A.
      • Muratori P.
      • Invernizzi P.
      • Colombatto P.
      • Brunetto M.
      • Bonino F.
      • De Francesco R.
      • Geginat J.
      • Pagani M.
      • Muratori L.
      • Abrignani S.
      • Bombaci M.
      Identification of new autoantigens by protein array indicates a role for IL4 neutralization in autoimmune hepatitis.
      ,
      • Song Q.
      • Liu G.
      • Hu S.
      • Zhang Y.
      • Tao Y.
      • Han Y.
      • Zeng H.
      • Huang W.
      • Li F.
      • Chen P.
      • Zhu J.
      • Hu C.
      • Zhang S.
      • Li Y.
      • Zhu H.
      • Wu L.
      Novel autoimmune hepatitis-specific autoantigens identified using protein microarray technology.
      ), ankylosing spondylitis (
      • Wright C.
      • Sibani S.
      • Trudgian D.
      • Fischer R.
      • Kessler B.
      • LaBaer J.
      • Bowness P.
      Detection of multiple autoantibodies in patients with ankylosing spondylitis using nucleic acid programmable protein arrays.
      ), multiple sclerosis (
      • Ayoglu B.
      • Haggmark A.
      • Khademi M.
      • Olsson T.
      • Uhlen M.
      • Schwenk J.M.
      • Nilsson P.
      Autoantibody profiling in multiple sclerosis using arrays of human protein fragments.
      ,
      • Querol L.
      • Clark P.L.
      • Bailey M.A.
      • Cotsapas C.
      • Cross A.H.
      • Hafler D.A.
      • Kleinstein S.H.
      • Lee J.Y.
      • Yaari G.
      • Willis S.N.
      • O'Connor K.C.
      Protein array-based profiling of CSF identifies RBPJ as an autoantigen in multiple sclerosis.
      ), type 1 diabetes (
      • Bian X.
      • Wasserfall C.
      • Wallstrom G.
      • Wang J.
      • Wang H.
      • Barker K.
      • Schatz D.
      • Atkinson M.
      • Qiu J.
      • LaBaer J.
      Tracking the antibody immunome in type 1 diabetes using protein arrays.
      ), Alzheimer's disease (
      • Nagele E.
      • Han M.
      • Demarshall C.
      • Belinka B.
      • Nagele R.
      Diagnosis of Alzheimer's disease based on disease-specific autoantibody profiles in human sera.
      ), rheumatoid arthritis (
      • Auger I.
      • Balandraud N.
      • Rak J.
      • Lambert N.
      • Martin M.
      • Roudier J.
      New autoantigens in rheumatoid arthritis (RA): screening 8268 protein arrays with sera from patients with RA.
      ), Sjögren's syndrome in saliva (
      • Hu S.
      • Vissink A.
      • Arellano M.
      • Roozendaal C.
      • Zhou H.
      • Kallenberg C.G.
      • Wong D.T.
      Identification of autoantibody biomarkers for primary Sjogren's syndrome using protein microarrays.
      ), primary biliary cirrhosis (
      • Hu C.J.
      • Song G.
      • Huang W.
      • Liu G.Z.
      • Deng C.W.
      • Zeng H.P.
      • Wang L.
      • Zhang F.C.
      • Zhang X.
      • Jeong J.S.
      • Blackshaw S.
      • Jiang L.Z.
      • Zhu H.
      • Wu L.
      • Li Y.Z.
      Identification of new autoantigens for primary biliary cirrhosis using human proteome microarrays.
      ), amyotrophic lateral sclerosis (
      • May C.
      • Nordhoff E.
      • Casjens S.
      • Turewicz M.
      • Eisenacher M.
      • Gold R.
      • Bruning T.
      • Pesch B.
      • Stephan C.
      • Woitalla D.
      • Penke B.
      • Janaky T.
      • Virok D.
      • Siklos L.
      • Engelhardt J.I.
      • Meyer H.E.
      Highly immunoreactive IgG antibodies directed against a set of twenty human proteins in the sera of patients with amyotrophic lateral sclerosis identified by protein array.
      ), male subfertility (
      • Landegren N.
      • Sharon D.
      • Shum A.K.
      • Khan I.S.
      • Fasano K.J.
      • Hallgren A.
      • Kampf C.
      • Freyhult E.
      • Ardesjo-Lundgren B.
      • Alimohammadi M.
      • Rathsman S.
      • Ludvigsson J.F.
      • Lundh D.
      • Motrich R.
      • Rivero V.
      • Fong L.
      • Giwercman A.
      • Gustafsson J.
      • Perheentupa J.
      • Husebye E.S.
      • Anderson M.S.
      • Snyder M.
      • Kampe O.
      Transglutaminase 4 as a prostate autoantigen in male subfertility.
      ), juvenile idiopathic arthritis (
      • Gibson D.S.
      • Qiu J.
      • Mendoza E.A.
      • Barker K.
      • Rooney M.E.
      • LaBaer J.
      Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays.
      ), Behcet's disease (
      • Hu C.J.
      • Pan J.B.
      • Song G.
      • Wen X.T.
      • Wu Z.Y.
      • Chen S.
      • Mo W.X.
      • Zhang F.C.
      • Qian J.
      • Zhu H.
      • Li Y.Z.
      Identification of novel biomarkers for Behcet disease diagnosis using human proteome microarray approach.
      ), and sarcoidosis (
      • Haggmark A.
      • Hamsten C.
      • Wiklundh E.
      • Lindskog C.
      • Mattsson C.
      • Andersson E.
      • Lundberg I.E.
      • Gronlund H.
      • Schwenk J.M.
      • Eklund A.
      • Grunewald J.
      • Nilsson P.
      Proteomic profiling reveals autoimmune targets in sarcoidosis.
      ). For biomarker identification, it is necessary to include the most comprehensive human proteome collection for unbiased screening, and to validate candidate biomarkers using additional cohort to avoid overfitting. These requirements often result in a high price tag for biomarker research. Song et al. developed a strategy to overcome this issue by dividing the process into two phases. In phase I, also known as the biomarker discovery or screening step, they used the HuProt array to survey AAbs in a smaller cohort of serums from 22 autoimmune hepatitis (AIH) patients and 30 healthy controls. In this phase, they narrowed down thousands of human proteins to 11 candidate autoantigens. In phase II, also known as the biomarker verification or validation step, they fabricated a focused antigen array with the 11 candidate antigens to survey AAbs in a much larger cohort composed of sera from 44 AIH patients, 50 healthy controls, and 184 patients suffering from other autoimmune diseases as a disease comparison group. With this two-phase strategy, they identified and validated three new antigens, RPS20, Alba-like, and dUTPase as highly specific biomarkers for AIH (
      • Song Q.
      • Liu G.
      • Hu S.
      • Zhang Y.
      • Tao Y.
      • Han Y.
      • Zeng H.
      • Huang W.
      • Li F.
      • Chen P.
      • Zhu J.
      • Hu C.
      • Zhang S.
      • Li Y.
      • Zhu H.
      • Wu L.
      Novel autoimmune hepatitis-specific autoantigens identified using protein microarray technology.
      ).
      In translational cancer research, it is important to identify early diagnosis markers to allow for earlier treatment and intervention. Human proteome arrays are widely used to profile the AAbs in 10 cancer types, including ovarian cancer (
      • Hudson M.E.
      • Pozdnyakova I.
      • Haines K.
      • Mor G.
      • Snyder M.
      Identification of differentially expressed proteins in ovarian cancer using high-density protein microarrays.
      ,
      • Anderson K.S.
      • Cramer D.W.
      • Sibani S.
      • Wallstrom G.
      • Wong J.
      • Park J.
      • Qiu J.
      • Vitonis A.
      • LaBaer J.
      Autoantibody signature for the serologic detection of ovarian cancer.
      ), glioma (
      • Syed P.
      • Gupta S.
      • Choudhary S.
      • Pandala N.G.
      • Atak A.
      • Richharia A.
      • Zhu K.P.M.H.
      • Epari S.
      • Noronha S.B.
      • Moiyadi A.
      • Srivastava S.
      Autoantibody profiling of glioma serum samples to identify biomarkers using human proteome arrays.
      ), lung cancer (
      • Pan J.
      • Song G.
      • Chen D.
      • Li Y.
      • Liu S.
      • Hu S.
      • Rosa C.
      • Eichinger D.
      • Pino I.
      • Zhu H.
      • Qian J.
      • Huang Y.
      Identification of serological biomarkers for early diagnosis of lung cancer using a protein array-based approach.
      ), gastric cancer (
      • Yang L.
      • Wang J.
      • Li J.
      • Zhang H.
      • Guo S.
      • Yan M.
      • Zhu Z.
      • Lan B.
      • Ding Y.
      • Xu M.
      • Li W.
      • Gu X.
      • Qi C.
      • Zhu H.
      • Shao Z.
      • Liu B.
      • Tao S.C.
      Identification of serum biomarkers for gastric cancer diagnosis using a human proteome microarray.
      ), bladder cancer (
      • Orenes-Pinero E.
      • Barderas R.
      • Rico D.
      • Casal J.I.
      • Gonzalez-Pisano D.
      • Navajo J.
      • Algaba F.
      • Piulats J.M.
      • Sanchez-Carbayo M.
      Serum and tissue profiling in bladder cancer combining protein and tissue arrays.
      ), prostate cancer (
      • Adeola H.A.
      • Smith M.
      • Kaestner L.
      • Blackburn J.M.
      • Zerbini L.F.
      Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort.
      ), colon cancer (
      • Babel I.
      • Barderas R.
      • Diaz-Uriarte R.
      • Martinez-Torrecuadrada J.L.
      • Sanchez-Carbayo M.
      • Casal J.I.
      Identification of tumor-associated autoantigens for the diagnosis of colorectal cancer in serum using high density protein microarrays.
      ), breast cancer (
      • Anderson K.S.
      • Sibani S.
      • Wallstrom G.
      • Qiu J.
      • Mendoza E.A.
      • Raphael J.
      • Hainsworth E.
      • Montor W.R.
      • Wong J.
      • Park J.G.
      • Lokko N.
      • Logvinenko T.
      • Ramachandran N.
      • Godwin A.K.
      • Marks J.
      • Engstrom P.
      • Labaer J.
      Protein microarray signature of autoantibody biomarkers for the early detection of breast cancer.
      ), myelodysplastic syndromes (
      • Mias G.I.
      • Chen R.
      • Zhang Y.
      • Sridhar K.
      • Sharon D.
      • Xiao L.
      • Im H.
      • Snyder M.P.
      • Greenberg P.L.
      Specific plasma autoantibody reactivity in myelodysplastic syndromes.
      ), and meningiomas (
      • Gupta S.
      • Mukherjee S.
      • Syed P.
      • Pandala N.G.
      • Choudhary S.
      • Singh V.A.
      • Singh N.
      • Zhu H.
      • Epari S.
      • Noronha S.B.
      • Moiyadi A.
      • Srivastava S.
      Evaluation of autoantibody signatures in meningioma patients using human proteome arrays.
      ). Orenes-Pinero et al. performed serum profiling on ProtoArray and identified 171 autoantigens related to bladder cancer. They validated selected candidates by using a cancer tissue array and confirmed that dynamin is not only an autoantigen biomarker, but it is also associated with poor survival (
      • Orenes-Pinero E.
      • Barderas R.
      • Rico D.
      • Casal J.I.
      • Gonzalez-Pisano D.
      • Navajo J.
      • Algaba F.
      • Piulats J.M.
      • Sanchez-Carbayo M.
      Serum and tissue profiling in bladder cancer combining protein and tissue arrays.
      ).
      Regarding infectious disease, the purpose of using protein microarrays is quite different from autoimmune diseases or cancer because the serum antibodies in infectious diseases are a part of the normal immune response. Ways in which the protein microarray can be used to study infectious disease include serotyping, identifying markers for prognosis, and identifying immunogenic proteins for vaccine development. To serve these purposes, the protein array must be tailored according to the pathogens being studied. NAPPA techniques have been applied to vaccine development by profiling serum antibodies against P. aeruginosa in a varicella-zoster virus proteome array (
      • Montor W.R.
      • Huang J.
      • Hu Y.
      • Hainsworth E.
      • Lynch S.
      • Kronish J.W.
      • Ordonez C.L.
      • Logvinenko T.
      • Lory S.
      • LaBaer J.
      Genome-wide study of Pseudomonas aeruginosa outer membrane protein immunogenicity using self-assembling protein microarrays.
      ,
      • Ceroni A.
      • Sibani S.
      • Baiker A.
      • Pothineni V.R.
      • Bailer S.M.
      • LaBaer J.
      • Haas J.
      • Campbell C.J.
      Systematic analysis of the IgG antibody immune response against varicella zoster virus (VZV) using a self-assembled protein microarray.
      ). Because in vitro expression arrays are more flexible, most of the pathogen-protein arrays are built with either IVTT or NAPPA. Such arrays include MTB (
      • Song L.
      • Wallstrom G.
      • Yu X.
      • Hopper M.
      • Van Duine J.
      • Steel J.
      • Park J.
      • Wiktor P.
      • Kahn P.
      • Brunner A.
      • Wilson D.
      • Jenny-Avital E.R.
      • Qiu J.
      • Labaer J.
      • Magee D.M.
      • Achkar J.M.
      Identification of antibody targets for tuberculosis serology using high-density nucleic acid programmable protein arrays.
      ), varicella zoster virus (
      • Ceroni A.
      • Sibani S.
      • Baiker A.
      • Pothineni V.R.
      • Bailer S.M.
      • LaBaer J.
      • Haas J.
      • Campbell C.J.
      Systematic analysis of the IgG antibody immune response against varicella zoster virus (VZV) using a self-assembled protein microarray.
      ), P. aeruginosa (
      • Montor W.R.
      • Huang J.
      • Hu Y.
      • Hainsworth E.
      • Lynch S.
      • Kronish J.W.
      • Ordonez C.L.
      • Logvinenko T.
      • Lory S.
      • LaBaer J.
      Genome-wide study of Pseudomonas aeruginosa outer membrane protein immunogenicity using self-assembling protein microarrays.
      ), L. interrogans (
      • Lessa-Aquino C.
      • Wunder Jr, E.A.
      • Lindow J.C.
      • Rodrigues C.B.
      • Pablo J.
      • Nakajima R.
      • Jasinskas A.
      • Liang L.
      • Reis M.G.
      • Ko A.I.
      • Medeiros M.A.
      • Felgner P.L.
      Proteomic features predict seroreactivity against leptospiral antigens in leptospirosis patients.
      ), S. Typhi (
      • Liang L.
      • Juarez S.
      • Nga T.V.
      • Dunstan S.
      • Nakajima-Sasaki R.
      • Davies D.H.
      • McSorley S.
      • Baker S.
      • Felgner P.L.
      Immune profiling with a Salmonella Typhi antigen microarray identifies new diagnostic biomarkers of human typhoid.
      ), B. melitensis (
      • Liang L.
      • Tan X.
      • Juarez S.
      • Villaverde H.
      • Pablo J.
      • Nakajima-Sasaki R.
      • Gotuzzo E.
      • Saito M.
      • Hermanson G.
      • Molina D.
      • Felgner S.
      • Morrow W.J.
      • Liang X.
      • Gilman R.H.
      • Davies D.H.
      • Tsolis R.M.
      • Vinetz J.M.
      • Felgner P.L.
      Systems biology approach predicts antibody signature associated with Brucella melitensis infection in humans.
      ), human papillomavirus (
      • Luevano M.
      • Bernard H.U.
      • Barrera-Saldana H.A.
      • Trevino V.
      • Garcia-Carranca A.
      • Villa L.L.
      • Monk B.J.
      • Tan X.
      • Davies D.H.
      • Felgner P.L.
      • Kalantari M.
      High-throughput profiling of the humoral immune responses against thirteen human papillomavirus types by proteome microarrays.
      ), C. albicans (
      • Mochon A.B.
      • Jin Y.
      • Kayala M.A.
      • Wingard J.R.
      • Clancy C.J.
      • Nguyen M.H.
      • Felgner P.
      • Baldi P.
      • Liu H.
      Serological profiling of a Candida albicans protein microarray reveals permanent host-pathogen interplay and stage-specific responses during candidemia.
      ), and F. Tularensis (
      • Sundaresh S.
      • Randall A.
      • Unal B.
      • Petersen J.M.
      • Belisle J.T.
      • Hartley M.G.
      • Duffield M.
      • Titball R.W.
      • Davies D.H.
      • Felgner P.L.
      • Baldi P.
      From protein microarrays to diagnostic antigen discovery: a study of the pathogen Francisella tularensis.
      ). A few pathogen-protein arrays are purified from yeast, including MTB (
      • Deng J.
      • Bi L.
      • Zhou L.
      • Guo S.J.
      • Fleming J.
      • Jiang H.W.
      • Zhou Y.
      • Gu J.
      • Zhong Q.
      • Wang Z.X.
      • Liu Z.
      • Deng R.P.
      • Gao J.
      • Chen T.
      • Li W.
      • Wang J.F.
      • Wang X.
      • Li H.
      • Ge F.
      • Zhu G.
      • Zhang H.N.
      • Gu J.
      • Wu F.L.
      • Zhang Z.
      • Wang D.
      • Hang H.
      • Li Y.
      • Cheng L.
      • He X.
      • Tao S.C.
      • Zhang X.E.
      Mycobacterium tuberculosis proteome microarray for global studies of protein function and immunogenicity.
      ), flaviviruses (
      • Song G.
      • Rho H.S.
      • Pan J.
      • Ramos P.
      • Yoon K.J.
      • Medina F.A.
      • Lee E.M.
      • Eichinger D.
      • Ming G.L.
      • Munoz-Jordan J.L.
      • Tang H.
      • Pino I.
      • Song H.
      • Qian J.
      • Zhu H.
      Multiplexed biomarker panels discriminate Zika and Dengue virus infection in humans.
      ), and herpes simplex virus (
      • Kalantari-Dehaghi M.
      • Chun S.
      • Chentoufi A.A.
      • Pablo J.
      • Liang L.
      • Dasgupta G.
      • Molina D.M.
      • Jasinskas A.
      • Nakajima-Sasaki R.
      • Felgner J.
      • Hermanson G.
      • BenMohamed L.
      • Felgner P.L.
      • Davies D.H.
      Discovery of potential diagnostic and vaccine antigens in herpes simplex virus 1 and 2 by proteome-wide antibody profiling.
      ).
      Other diseases with altered immune responses can also be examined using protein microarrays in order to identify AAbs relevant to disease. To date, there are nine inflammatory diseases with biomarkers that have been discovered using protein microarrays, including asthma (
      • Liu M.
      • Subramanian V.
      • Christie C.
      • Castro M.
      • Mohanakumar T.
      Immune responses to self-antigens in asthma patients: clinical and immunopathological implications.
      ), Kawasaki disease (
      • Kuo H.C.
      • Huang Y.H.
      • Chung F.H.
      • Chen P.C.
      • Sung T.C.
      • Chen Y.W.
      • Hsieh K.S.
      • Chen C.S.
      • Syu G.D.
      Antibody profiling of Kawasaki Disease using Escherichia coli proteome microarrays.
      ), preeclampsia (
      • Hsu T.Y.
      • Lin J.M.
      • Nguyen M.T.
      • Chung F.H.
      • Tsai C.C.
      • Cheng H.H.
      • Lai Y.J.
      • Hung H.N.
      • Chen C.S.
      Antigen analysis of pre-eclamptic plasma antibodies using Escherichia coli proteome chips.
      ), bipolar disorder (
      • Chen P.C.
      • Syu G.D.
      • Chung K.H.
      • Ho Y.H.
      • Chung F.H.
      • Chen P.H.
      • Lin J.M.
      • Chen Y.W.
      • Tsai S.Y.
      • Chen C.S.
      Antibody profiling of bipolar disorder using Escherichia coli proteome microarrays.
      ), Parkinson's disease (
      • Han M.
      • Nagele E.
      • DeMarshall C.
      • Acharya N.
      • Nagele R.
      Diagnosis of Parkinson's disease based on disease-specific autoantibody profiles in human sera.
      ), osteoarthritis (
      • Henjes F.
      • Lourido L.
      • Ruiz-Romero C.
      • Fernandez-Tajes J.
      • Schwenk J.M.
      • Gonzalez-Gonzalez M.
      • Blanco F.J.
      • Nilsson P.
      • Fuentes M.
      Analysis of autoantibody profiles in osteoarthritis using comprehensive protein array concepts.
      ), chronic renal disease (
      • Butte A.J.
      • Sigdel T.K.
      • Wadia P.P.
      • Miklos D.B.
      • Sarwal M.M.
      Protein microarrays discover angiotensinogen and PRKRIP1 as novel targets for autoantibodies in chronic renal disease.
      ), inflammatory bowel disease (
      • Vermeulen N.
      • de Beeck K.O.
      • Vermeire S.
      • Van Steen K.
      • Michiels G.
      • Ballet V.
      • Rutgeerts P.
      • Bossuyt X.
      Identification of a novel autoantigen in inflammatory bowel disease by protein microarray.
      ,
      • Chen C.S.
      • Sullivan S.
      • Anderson T.
      • Tan A.C.
      • Alex P.J.
      • Brant S.R.
      • Cuffari C.
      • Bayless T.M.
      • Talor M.V.
      • Burek C.L.
      • Wang H.
      • Li R.
      • Datta L.W.
      • Wu Y.
      • Winslow R.L.
      • Zhu H.
      • Li X.
      Identification of novel serological biomarkers for inflammatory bowel disease using Escherichia coli proteome chip.
      ), and Meniere's disease (
      • Kim S.H.
      • Kim J.Y.
      • Lee H.J.
      • Gi M.
      • Kim B.G.
      • Choi J.Y.
      Autoimmunity as a candidate for the etiopathogenesis of Meniere's disease: detection of autoimmune reactions and diagnostic biomarker candidate.
      ).

      GPCR-VirD Microarray

      GPCRs form the largest transmembrane protein family in humans, consisting of seven transmembrane domains. This complex structure allows GPCRs to bind to a variety of ligands, ranging from protons, ATP, amino acids, peptides, proteins, and to many other unidentified ligands. To date, ∼40% of the FDA-approved drugs target GPCRs. Because the lipid bilayer is required to maintain the conformation of GPCRs, purification attempts often disrupt the GPCR conformation. To overcome this hurdle, Hu et al. developed VirD technology by replacing a viral envelope gene in herpes simplex virus-1 (HSV-1) with an ORF encoding a human transmembrane protein. The production of this recombinant virus from mammalian cells allowed the human receptor to be embedded in the viral envelope with correct conformation and function (
      • Hu S.
      • Feng Y.
      • Henson B.
      • Wang B.
      • Huang X.
      • Li M.
      • Desai P.
      • Zhu H.
      VirD: a virion display array for profiling functional membrane proteins.
      ). More importantly, these recombinant viruses were arrayed on a glass slide to facilitate high-throughput screenings. Syu et al. expended the VirD technology to cover most of the non-odorant GPCRs (e.g. 315) for further biochemical interrogation (
      • Syu G.D.
      • Wang S.C.
      • Ma G.
      • Liu S.
      • Pearce D.
      • Prakash A.
      • Henson B.
      • Weng L.C.
      • Ghosh D.
      • Ramos P.
      • Eichinger D.
      • Pino I.
      • Dong X.
      • Xiao J.
      • Wang S.
      • Tao N.
      • Kim K.S.
      • Desai P.J.
      • Zhu H.
      Development and application of a high-content virion display human GPCR array.
      ). We demonstrated that the GPCR-VirD array is useful to profile specificity of mAbs (Fig. 2A). Among the 20 commercial mAbs tested, only 10 mAbs were determined to be ultra-specific. The rest either failed to show specificity entirely, or at least had several off-targets. Interestingly, all four mAbs with reported neutralization activity were shown to be ultra-specific on the GPCR-VirD array. Next, we performed specificity tests with known ligands (Fig. 2B) and revealed several off-targets for a peptide hormone, somatostatin-14. Two selected off-targets along with the canonical GPCR were validated with virion nano-oscillators for real-time and label-free detection (
      • Ma G.
      • Syu G.D.
      • Shan X.
      • Henson B.
      • Wang S.
      • Desai P.J.
      • Zhu H.
      • Tao N.
      Measuring Ligand Binding Kinetics to Membrane Proteins Using Virion Nano-oscillators.
      ) and showed significant binding affinities. Lastly, we probed the GPCR-VirD array with a clinical strain involved in neonatal meningitis (Group B Streptococcus K79) and identified five potential GPCR targets (Fig. 2C). CysLTR1 was further validated in vitro and in vivo as a host receptor for K79 invasion. We believe that the VirD array is a robust platform to profile many kinds of membrane protein interactions.
      Figure thumbnail gr2
      Fig. 2Application of GPCR-Virion Display (VirD) Microarray. 315 non-odorant GPCRs are displayed on the HSV-1 envelope to maintain the native conformation and form the world's largest functional GPCR-VirD array. The GPCR-VirD array is useful to screen for highly specific biologicals (A), ligands (B), small molecule drugs (B), and pathogen receptors (C).

      Future Directions

      Membrane proteins are one of the most important protein categories, as they play important roles in many biological processes, such as signal transduction, cell recognition, cell-cell communication, transport, and anchorage, to name a few. It is highly desirable to develop a high-content and high-throughput platform for functional membrane proteins to enable meaningful screening for ligands, biologicals and small molecule drugs. To date, many methods have been developed to maintain the native conformation of membrane proteins, including nanodiscs (
      • Nath A.
      • Atkins W.M.
      • Sligar S.G.
      Applications of phospholipid bilayer nanodiscs in the study of membranes and membrane proteins.
      ), macrodiscs (
      • Park S.H.
      • Berkamp S.
      • Cook G.A.
      • Chan M.K.
      • Viadiu H.
      • Opella S.J.
      Nanodiscs versus macrodiscs for NMR of membrane proteins.
      ), Salipro nanoparticales (
      • Frauenfeld J.
      • Loving R.
      • Armache J.P.
      • Sonnen A.F.
      • Guettou F.
      • Moberg P.
      • Zhu L.
      • Jegerschold C.
      • Flayhan A.
      • Briggs J.A.
      • Garoff H.
      • Low C.
      • Cheng Y.
      • Nordlund P.
      A saposin-lipoprotein nanoparticle system for membrane proteins.
      ), virus-like particles (
      • Hirozane Y.
      • Motoyaji T.
      • Maru T.
      • Okada K.
      • Tarui N.
      Generating thermostabilized agonist-bound GPR40/FFAR1 using virus-like particles and a label-free binding assay.
      ), and VirD (
      • Syu G.D.
      • Wang S.C.
      • Ma G.
      • Liu S.
      • Pearce D.
      • Prakash A.
      • Henson B.
      • Weng L.C.
      • Ghosh D.
      • Ramos P.
      • Eichinger D.
      • Pino I.
      • Dong X.
      • Xiao J.
      • Wang S.
      • Tao N.
      • Kim K.S.
      • Desai P.J.
      • Zhu H.
      Development and application of a high-content virion display human GPCR array.
      ,
      • Hu S.
      • Feng Y.
      • Henson B.
      • Wang B.
      • Huang X.
      • Li M.
      • Desai P.
      • Zhu H.
      VirD: a virion display array for profiling functional membrane proteins.
      ). Unlike VirD, the other methods are not easy to scale up for multiplexed, highly parallel screening while maintaining the flexibility of massive production of the reagents from various mammalian cell lines. When the VirD array is coupled with nano-oscillator technology (
      • Ma G.
      • Syu G.D.
      • Shan X.
      • Henson B.
      • Wang S.
      • Desai P.J.
      • Zhu H.
      • Tao N.
      Measuring Ligand Binding Kinetics to Membrane Proteins Using Virion Nano-oscillators.
      ), the entire membrane protein family can be screened simultaneously with candidate drugs or biologicals in a label-free, real time fashion, and binding specificity and kinetics can be obtained in a single experiment. We envision that VirD array technology can expand to all kind of membrane protein families and holds promise for discovering biologicals, drugs, and receptor interactions. Besides VirD tailored for membrane proteins, all other human proteins need a proper expression system for the best folding and PTMs. For this reason, it would be desirable to use a mammalian expression system. In combination with transfection, transformation, and CRISPR knock-in technologies (
      • Koch B.
      • Nijmeijer B.
      • Kueblbeck M.
      • Cai Y.
      • Walther N.
      • Ellenberg J.
      Generation and validation of homozygous fluorescent knock-in cells using CRISPR-Cas9 genome editing.
      ), it is possible to generate a human proteome microarray from human cells and accelerate research, potentially leading to the discovery of novel drugs or biologicals.

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