Reverse-Phase Protein Microarrays for Overexpressed Escherichia coli Lysates Reveal a Novel Tyrosine Kinase.

Tyrosine phosphorylation is one of the most important posttranslational modifications in bacteria, linked to regulating growth, migration, virulence, secondary metabolites, biofilm formation, and capsule production. Only two tyrosine kinases (yccC (etk) and wzc) have been identified in Escherichia coli. The investigation by similarity has not revealed any novel BY-kinases in silico so far, most probably due to their sequence and structural variability. Here we developed a reverse-phase protein array from 4126 overexpressed E. coli clones, lysed, and printed on coated glass slides. These high-density E. coli lysate arrays (ECLAs) were quality controlled by the reproducibility and immobilization of total lysate proteins and specific overexpressed proteins. ECLAs were used to interrogate the relationship between protein overexpression and tyrosine phosphorylation in the total lysate. We identified 6 protein candidates, including etk and wzc, with elevated phosphotyrosine signals in the total lysates. Among them, we identified a novel kinase nrdD with autophosphorylation and transphosphorylation activities in the lysates. Moreover, the overexpression of nrdD induced biofilm formation. Since nrdD is a novel kinase, we used E. coli proteome microarrays (purified 4,126 E. coli proteins) to perform an in vitro kinase assay and identified 33 potential substrates. Together, this study established a new ECLA platform for interrogating posttranslational modifications and identified a novel kinase that is important in biofilm formation, which will shed some light on bacteria biochemistry and new ways to impede drug resistance.

BAPCP: A comprehensive and user-friendly web tool for identifying biomarkers from protein microarray technologies.

BACKGROUND AND OBJECTIVE: Proteome microarrays are one of the popular high-throughput screening methods for large-scale investigation of protein interactions in cells. These interactions can be measured on protein chips when coupled with fluorescence-labeled probes, helping indicate potential biomarkers or discover drugs. Several computational tools were developed to help analyze the protein chip results. However, existing tools fail to provide a user-friendly interface for biologists and present only one or two data analysis methods suitable for limited experimental designs, restricting the use cases. METHODS: In order to facilitate the biomarker examination using protein chips, we implemented a user-friendly and comprehensive web tool called BAPCP (Biomarker Analysis tool for Protein Chip Platforms) in this research to deal with diverse chip data distributions. RESULTS: BAPCP is well integrated with standard chip result files and includes 7 data normalization methods and 7 custom-designed quality control/differential analysis filters for biomarker extraction among experiment groups. Moreover, it can handle cost-efficient chip designs that repeat several blocks/samples within one single slide. Using experiments of the human coronavirus (HCoV) protein microarray and the E. coli proteome chip that helps study the immune response of Kawasaki disease as examples, we demonstrated that BAPCP can accelerate the time-consuming week-long manual biomarker identification process to merely 3 min. CONCLUSIONS: The developed BAPCP tool provides substantial analysis support for protein interaction studies and conforms to the necessity of expanding computer usage and exchanging information in bioscience and medicine. The web service of BAPCP is available at https://cosbi.ee.ncku.edu.tw/BAPCP/.