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Journal articles on the topic 'Protein microarray'

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Author: Grafiati

Published: 4 June 2021

Last updated: 14 March 2023

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1

Shao, Weiping, Zhimin Zhou, Isabelle Laroche, Hong Lu, Qiuling Zong, Dhavalkumar D. Patel, Stephen Kingsmore, and Steven P. Piccoli. "Optimization of Rolling-Circle Amplified Protein Microarrays for Multiplexed Protein Profiling." Journal of Biomedicine and Biotechnology 2003, no. 5 (2003): 299–307. http://dx.doi.org/10.1155/s1110724303209268.

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Protein microarray-based approaches are increasingly being used in research and clinical applications to either profile the expression of proteins or screen molecular interactions. The development of high-throughput, sensitive, convenient, and cost-effective formats for detecting proteins is a necessity for the effective advancement of understanding disease processes. In this paper, we describe the generation of highly multiplexed, antibody-based, specific, and sensitive protein microarrays coupled with rolling-circle signal amplification (RCA) technology. A total of 150 cytokines were simultaneously detected in an RCA sandwich immunoassay format. Greater than half of these proteins have detection sensitivities in the pg/ml range. The validation of antibody microarray with human serum indicated that RCA-based protein microarrays are a powerful tool for high-throughput analysis of protein expression and molecular diagnostics.

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2

ZHANG, YONG. "INTEGRATION OF NANOPARTICLES WITH PROTEIN MICROARRAYS." International Journal of Nanoscience 05, no. 02n03 (April 2006): 189–94. http://dx.doi.org/10.1142/s0219581x0600422x.

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A variety of DNA, protein or cell microarray devices and systems have been developed and commercialized. In addition to the biomolecule related analysis, they are also being used for pharmacogenomic research, infectious and genetic disease and cancer diagnostics, and proteomic and cellular analysis.1 Currently, microarray is fabricated on a planar surface; this limits the amount of biomolecules that can be bounded on the surface. In this work, a planar protein microarray chip with nonplanar spot surface was fabricated to enhance the chip performance. A nonplanar spot surface was created by first coating the silica nanoparticles with albumin and depositing them into the patterned microwells. The curve surfaces of the nanoparticles increase the surface area for immobilization of proteins, which helps to enhance the detection sensitivity of the chip. Using this technique, proteins are immobilized onto the nanoparticles before they are deposited onto the chip, and therefore the method of protein immobilization can be customized at each spot. Furthermore, a nonplanar surface promotes the retention of native protein structure better than planar surface.2 The technique developed can be used to produce different types of microarrays, such as DNA, protein and antibody microarrays.

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3

Chatterjee, Deb K., Kalavathy Sitaraman, Cassio Baptista, James Hartley, Thomas M. Hill, and David J. Munroe. "Protein Microarray On-Demand: A Novel Protein Microarray System." PLoS ONE 3, no. 9 (September 24, 2008): e3265. http://dx.doi.org/10.1371/journal.pone.0003265.

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4

Joos, Thomas. "Protein microarray technology." Expert Review of Proteomics 1, no. 1 (June 2004): 1–3. http://dx.doi.org/10.1586/14789450.1.1.1.

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5

Stoll, Dieter. "Protein microarray technology." Frontiers in Bioscience 7, no. 1-3 (2002): c13. http://dx.doi.org/10.2741/stoll.

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6

Joos, T. O. "PROTEIN MICROARRAY TECHNOLOGY." Shock 21, Supplement (March 2004): 1. http://dx.doi.org/10.1097/00024382-200403001-00002.

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7

Doerr, Allison. "Protein microarray velcro." Nature Methods 2, no. 9 (September 2005): 642. http://dx.doi.org/10.1038/nmeth0905-642a.

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8

Hall, David A., Jason Ptacek, and Michael Snyder. "Protein microarray technology." Mechanisms of Ageing and Development 128, no. 1 (January 2007): 161–67. http://dx.doi.org/10.1016/j.mad.2006.11.021.

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9

Templin, Markus F., Dieter Stoll, Monika Schrenk, Petra C. Traub, Christian F. Vöhringer, and Thomas O. Joos. "Protein microarray technology." Trends in Biotechnology 20, no. 4 (April 2002): 160–66. http://dx.doi.org/10.1016/s0167-7799(01)01910-2.

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10

Templin, Markus F., Dieter Stoll, Monika Schrenk, Petra C. Traub, Christian F. Vöhringer, and Thomas O. Joos. "Protein microarray technology." Drug Discovery Today 7, no. 15 (August 2002): 815–22. http://dx.doi.org/10.1016/s1359-6446(00)01910-2.

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11

Joos, Thomas O. "Protein microarray technology." Frontiers in Bioscience 7, no. 3 (2002): c13–32. http://dx.doi.org/10.2741/a756.

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12

Oulton, Tate, Joshua Obiero, Isabel Rodriguez, Isaac Ssewanyana, Rebecca A. Dabbs, Christine M. Bachman, Bryan Greenhouse, et al. "Plasmodium falciparum serology: A comparison of two protein production methods for analysis of antibody responses by protein microarray." PLOS ONE 17, no. 8 (August 29, 2022): e0273106. http://dx.doi.org/10.1371/journal.pone.0273106.

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The evaluation of protein antigens as putative serologic biomarkers of infection has increasingly shifted to high-throughput, multiplex approaches such as the protein microarray. In vitro transcription/translation (IVTT) systems–a similarly high-throughput protein expression method–are already widely utilised in the production of protein microarrays, though purified recombinant proteins derived from more traditional whole cell based expression systems also play an important role in biomarker characterisation. Here we have performed a side-by-side comparison of antigen-matched protein targets from an IVTT and purified recombinant system, on the same protein microarray. The magnitude and range of antibody responses to purified recombinants was found to be greater than that of IVTT proteins, and responses between targets from different expression systems did not clearly correlate. However, responses between amino acid sequence-matched targets from each expression system were more closely correlated. Despite the lack of a clear correlation between antigen-matched targets produced in each expression system, our data indicate that protein microarrays produced using either method can be used confidently, in a context dependent manner, though care should be taken when comparing data derived from contrasting approaches.

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13

Cao, Yiwei, Sang-Jun Park, Akul Y. Mehta, Richard D. Cummings, and Wonpil Im. "GlyMDB: Glycan Microarray Database and analysis toolset." Bioinformatics 36, no. 8 (December 16, 2019): 2438–42. http://dx.doi.org/10.1093/bioinformatics/btz934.

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Abstract Motivation Glycan microarrays are capable of illuminating the interactions of glycan-binding proteins (GBPs) against hundreds of defined glycan structures, and have revolutionized the investigations of protein–carbohydrate interactions underlying numerous critical biological activities. However, it is difficult to interpret microarray data and identify structural determinants promoting glycan binding to glycan-binding proteins due to the ambiguity in microarray fluorescence intensity and complexity in branched glycan structures. To facilitate analysis of glycan microarray data alongside protein structure, we have built the Glycan Microarray Database (GlyMDB), a web-based resource including a searchable database of glycan microarray samples and a toolset for data/structure analysis. Results The current GlyMDB provides data visualization and glycan-binding motif discovery for 5203 glycan microarray samples collected from the Consortium for Functional Glycomics. The unique feature of GlyMDB is to link microarray data to PDB structures. The GlyMDB provides different options for database query, and allows users to upload their microarray data for analysis. After search or upload is complete, users can choose the criterion for binder versus non-binder classification. They can view the signal intensity graph including the binder/non-binder threshold followed by a list of glycan-binding motifs. One can also compare the fluorescence intensity data from two different microarray samples. A protein sequence-based search is performed using BLAST to match microarray data with all available PDB structures containing glycans. The glycan ligand information is displayed, and links are provided for structural visualization and redirection to other modules in GlycanStructure.ORG for further investigation of glycan-binding sites and glycan structures. Availability and implementation http://www.glycanstructure.org/glymdb. Supplementary information Supplementary data are available at Bioinformatics online.

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14

ESPEJO, Alexsandra, Jocelyn CÔTÉ, Andrzej BEDNAREK, Stephane RICHARD, and Mark T. BEDFORD. "A protein-domain microarray identifies novel protein–protein interactions." Biochemical Journal 367, no. 3 (November 1, 2002): 697–702. http://dx.doi.org/10.1042/bj20020860.

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Protein domains mediate protein—protein interactions through binding to short peptide motifs in their corresponding ligands. These peptide recognition modules are critical for the assembly of multiprotein complexes. We have arrayed glutathione S-transferase (GST) fusion proteins, with a focus on protein interaction domains, on to nitrocellulose-coated glass slides to generate a protein-domain chip. Arrayed protein-interacting modules included WW (a domain with two conserved tryptophans), SH3 (Src homology 3), SH2, 14.3.3, FHA (forkhead-associated), PDZ (a domain originally identified in PSD-95, DLG and ZO-1 proteins), PH (pleckstrin homology) and FF (a domain with two conserved phenylalanines) domains. Here we demonstrate, using peptides, that the arrayed domains retain their binding integrity. Furthermore, we show that the protein-domain chip can ‘fish’ proteins out of a total cell lysate; these domain-bound proteins can then be detected on the chip with a specific antibody, thus producing an interaction map for a cellular protein of interest. Using this approach we have confirmed the domain-binding profile of the signalling molecule Sam68 (Src-associated during mitosis 68), and have identified a new binding profile for the core small nuclear ribonucleoprotein SmB′. This protein-domain chip not only identifies potential binding partners for proteins, but also promises to recognize qualitative differences in protein ligands (caused by post-translational modification), thus getting at the heart of signal transduction pathways.

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15

Roberts, Josh P. "Protein Microarray Use Multiplies." Genetic Engineering & Biotechnology News 31, no. 9 (May 2011): 1–36. http://dx.doi.org/10.1089/gen.31.9.14.

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16

Hu, Shaohui, Zhi Xie, Jiang Qian, Seth Blackshaw, and Heng Zhu. "Functional protein microarray technology." Wiley Interdisciplinary Reviews: Systems Biology and Medicine 3, no. 3 (September 24, 2010): 255–68. http://dx.doi.org/10.1002/wsbm.118.

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17

Chiodi, Elisa, Allison M. Marn, Matthew T. Geib, and M. Selim Ünlü. "The Role of Surface Chemistry in the Efficacy of Protein and DNA Microarrays for Label-Free Detection: An Overview." Polymers 13, no. 7 (March 26, 2021): 1026. http://dx.doi.org/10.3390/polym13071026.

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The importance of microarrays in diagnostics and medicine has drastically increased in the last few years. Nevertheless, the efficiency of a microarray-based assay intrinsically depends on the density and functionality of the biorecognition elements immobilized onto each sensor spot. Recently, researchers have put effort into developing new functionalization strategies and technologies which provide efficient immobilization and stability of any sort of molecule. Here, we present an overview of the most widely used methods of surface functionalization of microarray substrates, as well as the most recent advances in the field, and compare their performance in terms of optimal immobilization of the bioreceptor molecules. We focus on label-free microarrays and, in particular, we aim to describe the impact of surface chemistry on two types of microarray-based sensors: microarrays for single particle imaging and for label-free measurements of binding kinetics. Both protein and DNA microarrays are taken into consideration, and the effect of different polymeric coatings on the molecules’ functionalities is critically analyzed.

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18

Eckel, Jeanette E., Antje Hoering, and Irene Ghobrial. "Experimental Design & Analysis of Protein Array Data: Applying Methods from cDNA Arrays." Blood 104, no. 11 (November 16, 2004): 4280. http://dx.doi.org/10.1182/blood.v104.11.4280.4280.

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Abstract It appears that a number of recent manuscripts using protein microarray technology are using equivalent analysis procedures that the gene-expression microarray community implemented in their infancy. That is, utilizing a classic reference design such that the ratio of the sample of interest to a reference sample is the response of interest and assessing fold change to determine differential expression. For example, recent publications have concluded that proteins with a fold change less than 0.7 or greater than 1.3 demonstrate significant down- or up-regulated differential expression, respectively. However, fold change is an unreliable measure of differential expression and statistical models that distinguish true signal from random noise should be utilized instead of fold changes. Over the last half decade a tremendous amount of research has been devoted to gene-expression microarrays to vastly improve on the areas of experimental design, normalization and statistical analyses to assess differential expression and classification and these methods are directly applicable to protein microarray technology. Thus, the objective is to review the statistical methodology that has been developed for two-color cDNA arrays that is directly applicable to protein arrays. Examples are provided from a mantle-cell lymphoma protein-array experiment.

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19

Pawlak, Michael, Eginhard Schick, Martin A. Bopp, Michael J. Schneider, Peter Oroszlan, and Markus Ehrat. "Zeptosens' protein microarrays: A novel high performance microarray platform for low abundance protein analysis." PROTEOMICS 2, no. 4 (April 2002): 383. http://dx.doi.org/10.1002/1615-9861(200204)2:4<383::aid-prot383>3.0.co;2-e.

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20

GUO, ATHENA, and XIAOYANG ZHU. "SURFACE CHEMISTRY FOR PROTEIN MICROARRAYS." International Journal of Nanoscience 06, no. 02 (April 2007): 109–16. http://dx.doi.org/10.1142/s0219581x07004341.

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Protein microarray or protein chip is an important tool in proteomics. However, duplicating the success of the DNA chip for the protein chip has been difficult. This account discusses a key issue in protein microarray development, i.e., surface chemistry. Ideally, the surface chemistry for protein microarray fabrication should satisfy the following criteria: the surface resists nonspecific adsorption; functional groups for the facile immobilization of protein molecules of interest are readily available; bonding between a protein molecule and a solid surface is balanced to provide sufficient stability but minimal disturbance on the delicate three-dimensional structure of the protein; linking chemistry allows the control of protein orientation; the local chemical environment favors the immobilized protein molecules to retain their native conformation; and finally, the specificity of linking chemistry is so high that no pre-purification of proteins is required. Strategies to achieve such an ideal situation are discussed, with successful examples from our laboratories illustrated. Finally, the need of surface technology for membrane protein microarray fabrication is addressed.

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21

Syu, Guan-Da, Jessica Dunn, and Heng Zhu. "Developments and Applications of Functional Protein Microarrays." Molecular & Cellular Proteomics 19, no. 6 (April 17, 2020): 916–27. http://dx.doi.org/10.1074/mcp.r120.001936.

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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.

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22

Wellhausen, Robert, and Harald Seitz. "Facing Current Quantification Challenges in Protein Microarrays." Journal of Biomedicine and Biotechnology 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/831347.

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The proteome is highly variable and differs from cell to cell. The reasons are posttranslational modifications, splice variants, and polymorphisms. Techniques like next-generation sequencing can only give an inadequate picture of the protein status of a cell. Protein microarrays are able to track these changes on the level they occur: the proteomic level. Therefore, protein microarrays are powerful tools for relative protein quantification, to unveil new interaction partners and to track posttranslational modifications. This papers gives an overview on current protein microarray techniques and discusses recent advances in relative protein quantification.

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23

Philippakis, Anthony A., Aaron M. Qureshi, Michael F. Berger, and Martha L. Bulyk. "Design of Compact, Universal DNA Microarrays for Protein Binding Microarray Experiments." Journal of Computational Biology 15, no. 7 (September 2008): 655–65. http://dx.doi.org/10.1089/cmb.2007.0114.

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24

de Lange, Victoria, Andreas Binkert, Janos Vörös, and Marta Bally. "Microarrays Made Easy: Biofunctionalized Hydrogel Channels for Rapid Protein Microarray Production." ACS Applied Materials & Interfaces 3, no. 1 (December 9, 2010): 50–57. http://dx.doi.org/10.1021/am100849f.

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25

Huang, Joe Xi, Dorothy Mehrens, Rick Wiese, Sandy Lee, Sun W. Tam, Steve Daniel, James Gilmore, Michael Shi, and Deval Lashkari. "High-Throughput Genomic and Proteomic Analysis Using Microarray Technology." Clinical Chemistry 47, no. 10 (October 1, 2001): 1912–16. http://dx.doi.org/10.1093/clinchem/47.10.1912.

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Abstract Background: High-density microarrays are ideally suited for analyzing thousands of genes against a small number of samples. The next step in the discovery process is to take the resulting genes of interest and rapidly screen them against thousands of patient samples, tissues, or cell lines to further investigate their involvement in disease risk or the response to medication. Methods: We used a microarray technology platform for both single-nucleotide polymorphisms (SNPs) and protein expression. Each microarray contains up to 250 elements that can be customized for each application. Slides contained either a 16- or 96-microarray format (4000–24 000 elements per slide), allowing the corresponding number of samples to be rapidly processed in parallel. Results: Results for SNP genotyping and protein profiling agreed with results of restriction fragment length polymorphism (RFLP) analysis or ELISA, respectively. Genotyping analyses, using the microarray technology, on large sample sets over multiple polymorphisms in the NAT2 gene were in full agreement with traditional methodologies, such as sequencing and RFLP analysis. The multiplexed protein microarray had correlation coefficients of 0.82–0.99 (depending on analyte) compared with ELISAs. Conclusions: The integrated microarray technology platform is adaptable and versatile, while offering the high-throughput capabilities needed for drug development and discovery applications.

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Yu, Xiaobo, Nicole Schneiderhan-Marra, and Thomas O. Joos. "Protein Microarrays for Personalized Medicine." Clinical Chemistry 56, no. 3 (March 1, 2010): 376–87. http://dx.doi.org/10.1373/clinchem.2009.137158.

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Abstract Background: Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material. Content: Protein microarrays have become well-established tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine. Summary: Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

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27

A Abdo, M., and P. J Hudson. "Protein microarrays in clinical microbiology." Microbiology Australia 27, no. 2 (2006): 78. http://dx.doi.org/10.1071/ma06078.

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Clinical microbiology laboratories have, in the past, broadly adopted new molecular biology techniques and automation. In the near future, the adoption of protein microarray technology has the potential to revolutionise the field in a manner similar to that of polymerase chain reaction (PCR). With the advantages of far greater sensitivity, parallel experimentation, reduced sample consumption and cost-per-test, the development of protein microarrays has come about through the realisation that mRNA levels do not necessarily correlate with protein expression.

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28

Negm, Ola H., Mohamed R. Hamed, Elizabeth M. Dilnot, Clifford C. Shone, Izabela Marszalowska, Mark Lynch, Christine E. Loscher, et al. "Profiling Humoral Immune Responses to Clostridium difficile-Specific Antigens by Protein Microarray Analysis." Clinical and Vaccine Immunology 22, no. 9 (July 15, 2015): 1033–39. http://dx.doi.org/10.1128/cvi.00190-15.

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ABSTRACTClostridium difficileis an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course ofC. difficileinfection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purifiedC. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid andCandida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated <10% coefficient of variation (CV). Significant correlation was observed between microarray and ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses toC. difficileprotein antigens and may have potential advantages in throughput, convenience, and cost.

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29

Tao, Sheng-Ce, Chien-Sheng Chen, and Heng Zhu. "Applications of Protein Microarray Technology." Combinatorial Chemistry & High Throughput Screening 10, no. 8 (September 1, 2007): 706–18. http://dx.doi.org/10.2174/138620707782507386.

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30

Glökler, Jörn, and Philipp Angenendt. "Protein and antibody microarray technology." Journal of Chromatography B 797, no. 1-2 (November 2003): 229–40. http://dx.doi.org/10.1016/j.jchromb.2003.08.034.

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31

White, A. M., D. S. Daly, S. M. Varnum, K. K. Anderson, N. Bollinger, and R. C. Zangar. "ProMAT: protein microarray analysis tool." Bioinformatics 22, no. 10 (April 4, 2006): 1278–79. http://dx.doi.org/10.1093/bioinformatics/btl093.

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32

Xu, Qingchai, and Kit S. Lam. "Protein and Chemical Microarrays—Powerful Tools for Proteomics." Journal of Biomedicine and Biotechnology 2003, no. 5 (2003): 257–66. http://dx.doi.org/10.1155/s1110724303209220.

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In the last few years, protein and chemical microarrays have emerged as two important tools in the field of proteomics. Specific proteins, antibodies, small molecule compounds, peptides, and carbohydrates can now be immobilized on solid surfaces to form high-density microarrays. Depending on their chemical nature, immobilization of these molecules on solid support is accomplished by in situ synthesis, nonspecific adsorption, specific binding, nonspecific chemical ligation, or chemoselective ligation. These arrays of molecules can then be probed with complex analytes such as serum, total cell extracts, and whole blood. Interactions between the analytes and the immobilized array of molecules are evaluated with a number of different detection systems. In this paper, various components, methods, and applications of the protein and chemical microarray systems are reviewed.

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33

Qi, Huan, Huiqiong Zhou, Daniel Mark Czajkowsky, Shujuan Guo, Yang Li, Nan Wang, Yi Shi, et al. "Rapid Production of Virus Protein Microarray Using Protein Microarray Fabrication through Gene Synthesis (PAGES)." Molecular & Cellular Proteomics 16, no. 2 (December 13, 2016): 288–99. http://dx.doi.org/10.1074/mcp.m116.064873.

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34

Selvarajah, Senthooran, Ola H. Negm, Mohamed R. Hamed, Carolyn Tubby, Ian Todd, Patrick J. Tighe, Tim Harrison, and Lucy C. Fairclough. "Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera." Mediators of Inflammation 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/820304.

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Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays.

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Rafique, Saima, Farukh Kiyani, Sumbal Jawaid, Rubina Nasir, Mahmoosh Ahmad, Shazia Bashir, Muhammad Idress, Jan Sher Khan, and Rizwan Akram. "Reusable, Noninvasive, and Sensitive Fluorescence Enhanced ZnO-Nanorod-Based Microarrays for Quantitative Detection of AFP in Human Serum." BioMed Research International 2021 (July 15, 2021): 1–11. http://dx.doi.org/10.1155/2021/9916909.

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The fabrication of sensitive protein microarrays such as PCR used in DNA microarray is challenging due to lack of signal amplification. The development of microarrays is utilized to improve the sensitivity and limitations of detection towards primal cancer detection. The sensitivity is enhanced by the use of ZnO-nanorods and is investigated as a substrate which enhance the florescent signal to diagnose the hepatocellular carcinoma (HCC) at early stages. The substrate for deposition of ZnO-nanorods is prepared by the conventional chemical bath deposition method. The resultant highly dense ZnO-nanorods enhance the fluorescent signal 7.2 times as compared to the substrate without ZnO-nanorods. The microarray showed sensitivity of 1504.7 ng ml-1 and limit of detection of 0.1 pg ml-1 in wide dynamic range of 0.05 pg-10 μg ml-1 for alpha fetoprotein (AFP) detection in 10% human serum. This immunoassay was successfully applied for human serum samples to detect tumor marker with good recoveries. The ZnO-nanorod substrate is a simple protein microarray which showed a great promise for developing a low-cost, sensitive, and high-throughput protein assay platform for several applications in both fundamental research and clinical diagnosis.

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Wang, Zhiyou, Xiaoqing Huang, and Zhiqiang Cheng. "Automatic Spot Identification Method for High Throughput Surface Plasmon Resonance Imaging Analysis." Biosensors 8, no. 3 (September 13, 2018): 85. http://dx.doi.org/10.3390/bios8030085.

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An automatic spot identification method is developed for high throughput surface plasmon resonance imaging (SPRi) analysis. As a combination of video accessing, image enhancement, image processing and parallel processing techniques, the method can identify the spots in SPRi images of the microarray from SPRi video data. In demonstrations of the method, SPRi video data of different protein microarrays were processed by the method. Results show that our method can locate spots in the microarray accurately regardless of the microarray pattern, spot-background contrast, light nonuniformity and spotting defects, but also can provide address information of the spots.

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37

García-Albert, L., F. Martín-Sánchez, A. García-Sáiz, and G. H. López-Campos. "Analysis and Management of HIV Peptide Microarray Experiments." Methods of Information in Medicine 45, no. 02 (2006): 158–62. http://dx.doi.org/10.1055/s-0038-1634060.

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Summary Objectives: To develop a tool for then easy and user-friendly management of peptide microarray experiments and for the use of the results of these experiments for the study the immune response against HIV virus infection in clinical samples. Methods: Applying bioinformatics and statistics for the analysis of data coming from microarray experiments as well as implementing a MIAME (Minimum Information About a Microarray Experiment) compliant database for managing and annotating experiments, results and samples. Results: We present a new tool for managing not only nucleic acid microarray experiments but also protein microarray experiments. From the analysis of experimental data, we can detect different profiles in the reactivity of the sera with different genotypes. Conclusions: We have developed a new tool for managing microarray data including clinical annotations for the samples as well as the capability of annotating other microarray formats different to those based on nucleic acids. The use of peptide microarrays and bioinformatics analysis opens a new scope for the characterization of the immune response, and analyzing and identifying the humoral response of viruses with different genotypes.

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Gryadunov, D. A., B. L. Shaskolskiy, T. V. Nasedkina, A. Yu Rubina, and A. S. Zasedatelev. "The EIMB Hydrogel Microarray Technology: Thirty Years Later." Acta Naturae 10, no. 4 (December 15, 2018): 4–18. http://dx.doi.org/10.32607/20758251-2018-10-4-4-18.

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Biological microarrays (biochips) are analytical tools that can be used to implement complex integrative genomic and proteomic approaches to the solution of problems of personalized medicine (e.g., patient examination in order to reveal the disease long before the manifestation of clinical symptoms, assess the severity of pathological or infectious processes, and choose a rational treatment). The efficiency of biochips is predicated on their ability to perform multiple parallel specific reactions and to allow one to study the interactions of biopolymer molecules, such as DNA, proteins, glycans, etc. One of the pioneers of microarray technology was the Engelhardt Institute of Molecular Biology of the Russian Academy of Sciences (EIMB), with its suggestion to immobilize molecular probes in the three-dimensional structure of a hydrophilic gel. Since the first experiments on sequencing by hybridization on oligonucleotide microarrays conducted some 30 years ago, the hydrogel microarrays designed at the EIMB have come a long and successful way from basic research to clinical laboratory diagnostics. This review discusses the key aspects of hydrogel microarray technology and a number of state-ofthe-art approaches for a multiplex analysis of DNA and the protein biomarkers of socially significant diseases, including the molecular genetic, immunological, and epidemiological aspects of pathogenesis.

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Forster, T., D. Roy, and P. Ghazal. "Experiments using microarray technology: limitations and standard operating procedures." Journal of Endocrinology 178, no. 2 (August 1, 2003): 195–204. http://dx.doi.org/10.1677/joe.0.1780195.

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Microarrays are a powerful method for the global analysis of gene or protein content and expression, opening up new horizons in molecular and physiological systems. This review focuses on the critical aspects of acquiring meaningful data for analysis following fluorescence-based target hybridisation to arrays. Although microarray technology is adaptable to the analysis of a range of biomolecules (DNA, RNA, protein, carbohydrates and lipids), the scheme presented here is applicable primarily to customised DNA arrays fabricated using long oligomer or cDNA probes. Rather than provide a comprehensive review of microarray technology and analysis techniques, both of which are large and complex areas, the aim of this paper is to provide a restricted overview, highlighting salient features to provide initial guidance in terms of pitfalls in planning and executing array projects. We outline standard operating procedures, which help streamline the analysis of microarray data resulting from a diversity of array formats and biological systems. We hope that this overview will provide practical initial guidance for those embarking on microarray studies.

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Smith, David F., Richard D. Cummings, and Xuezheng Song. "History and future of shotgun glycomics." Biochemical Society Transactions 47, no. 1 (January 9, 2019): 1–11. http://dx.doi.org/10.1042/bst20170487.

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Abstract Glycans in polysaccharides and glycoconjugates of the hydrophilic exterior of all animal cells participate in signal transduction, cellular adhesion, intercellular signaling, and sites for binding of pathogens largely through protein–glycan interactions. Microarrays of defined glycans have been used to study the binding specificities of biologically relevant glycan-binding proteins (GBP), but such arrays are limited by their lack of diversity or relevance to the GBP being investigated. Shotgun glycan microarrays are made up of structurally undefined glycans that were released from natural sources, labeled with bifunctional reagents so that they can be monitored during their purification using multidimensional chromatographic procedures, stored as a tagged glycan library (TGL) and subsequently printed onto microarrays at equal molar concentrations. The shotgun glycan microarray is then interrogated with a biologically relevant GBP and the corresponding glycan ligands can be retrieved from the TGL for detailed structural analysis and further functional analysis. Shotgun glycomics extended the defined glycan microarray to a discovery platform that supports functional glycomic analyses and may provide a useful process for ultimately defining the human glycome.

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Celebi, Iris, Matthew T. Geib, Elisa Chiodi, Nese Lortlar Ünlü, Fulya Ekiz Kanik, and Selim Ünlü. "Instrument-Free Protein Microarray Fabrication for Accurate Affinity Measurements." Biosensors 10, no. 11 (October 29, 2020): 158. http://dx.doi.org/10.3390/bios10110158.

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Protein microarrays have gained popularity as an attractive tool for various fields, including drug and biomarker development, and diagnostics. Thus, multiplexed binding affinity measurements in microarray format has become crucial. The preparation of microarray-based protein assays relies on precise dispensing of probe solutions to achieve efficient immobilization onto an active surface. The prohibitively high cost of equipment and the need for trained personnel to operate high complexity robotic spotters for microarray fabrication are significant detriments for researchers, especially for small laboratories with limited resources. Here, we present a low-cost, instrument-free dispensing technique by which users who are familiar with micropipetting can manually create multiplexed protein assays that show improved capture efficiency and noise level in comparison to that of the robotically spotted assays. In this study, we compare the efficiency of manually and robotically dispensed α-lactalbumin probe spots by analyzing the binding kinetics obtained from the interaction with anti-α-lactalbumin antibodies, using the interferometric reflectance imaging sensor platform. We show that the protein arrays prepared by micropipette manual spotting meet and exceed the performance of those prepared by state-of-the-art robotic spotters. These instrument-free protein assays have a higher binding signal (~4-fold improvement) and a ~3-fold better signal-to-noise ratio (SNR) in binding curves, when compared to the data acquired by averaging 75 robotic spots corresponding to the same effective sensor surface area. We demonstrate the potential of determining antigen-antibody binding coefficients in a 24-multiplexed chip format with less than 5% measurement error.

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Kersten, Birgit, Erich E. Wanker, Jörg D. Hoheisel, and Philipp Angenendt. "Multiplex approaches in protein microarray technology." Expert Review of Proteomics 2, no. 4 (August 2005): 499–510. http://dx.doi.org/10.1586/14789450.2.4.499.

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Bertone, Paul, and Michael Snyder. "Advances in functional protein microarray technology." FEBS Journal 272, no. 21 (November 2005): 5400–5411. http://dx.doi.org/10.1111/j.1742-4658.2005.04970.x.

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Xu, Yangqing, and Gang Bao. "A Filtration-Based Protein Microarray Technique." Analytical Chemistry 75, no. 20 (October 2003): 5345–51. http://dx.doi.org/10.1021/ac034613g.

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Ramiya Ramesh Babu, Heman Kumar, and Levi A. Gheber. "Rapid assaying of miniaturized protein microarray." Sensors and Actuators B: Chemical 268 (September 2018): 55–60. http://dx.doi.org/10.1016/j.snb.2018.04.074.

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Feng, Feng, Sila Toksoz Ataca, Mingxuan Ran, Yumei Wang, Michael Breen, and Thomas B. Kepler. "Gain-Scanning for Protein Microarray Assays." Journal of Proteome Research 19, no. 7 (January 13, 2020): 2664–75. http://dx.doi.org/10.1021/acs.jproteome.9b00892.

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Lee, Yun-Il, Daniel Giovinazzo, Ho Chul Kang, Yunjong Lee, Jun Seop Jeong, Paschalis-Thomas Doulias, Zhi Xie, et al. "Protein Microarray Characterization of theS-Nitrosoproteome." Molecular & Cellular Proteomics 13, no. 1 (October 8, 2013): 63–72. http://dx.doi.org/10.1074/mcp.m113.032235.

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Lee, Hye Jin, Alastair W. Wark, and Robert M. Corn. "Microarray methods for protein biomarker detection." Analyst 133, no. 8 (2008): 975. http://dx.doi.org/10.1039/b717527b.

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Wilson, David S., and Steffen Nock. "Recent Developments in Protein Microarray Technology." Angewandte Chemie International Edition 42, no. 5 (February 3, 2003): 494–500. http://dx.doi.org/10.1002/anie.200390150.

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Pollard, Harvey B., Meera Srivastava, Ofer Eidelman, Catherine Jozwik, Stephen W. Rothwell, Gregory P. Mueller, David M. Jacobowitz, et al. "Protein microarray platforms for clinical proteomics." PROTEOMICS – CLINICAL APPLICATIONS 1, no. 9 (September 2007): 934–52. http://dx.doi.org/10.1002/prca.200700154.

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