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Measuring binding properties of binders (e.g., antibodies) is essential for developing useful experimental reagents, diagnostics, and pharmaceuticals. Display technologies can evaluate a large number of binders in a high-throughput manner, but the immobilization effect and the avidity effect prohibit the precise evaluation of binding properties. In this paper, we propose a novel methodology, peptide barcoding, to quantitatively measure the binding properties of multiple binders without immobilization. In the experimental scheme, unique peptide barcodes are fused with each binder, and they represent genotype information. These peptide barcodes are designed to have high detectability for mass spectrometry, leading to low identification bias and a high identification rate. A mixture of different peptide-barcoded nanobodies is reacted with antigen-coated magnetic beads in one pot. Peptide barcodes of functional nanobodies are cleaved on beads by a specific protease, and identified by selected reaction monitoring using triple quadrupole mass spectrometry. To demonstrate proof-of-principle for peptide barcoding, we generated peptide-barcoded anti-CD4 nanobody and anti-GFP nanobody, and determined whether we could simultaneously quantify their binding activities. We showed that peptide barcoding did not affect the properties of the nanobodies, and succeeded in measuring the binding activities of these nanobodies in one shot. The results demonstrate the advantages of peptide barcoding, new types of genotype–phenotype linkages., 多様なモノクロナル抗体分子を迅速に作製するペプチドバーコード手法を確立 --動物を使わずに試験管内で多様な抗体を調製することが可能に--. 京都大学プレスリリース. 2019-04-25.

Pathway analysis of glycolysis. Glycolysis pathway was constructed from KEGG. White box indicates the fold change of each protein relative to glucose at the same time point, and gray box indicates temporal profile of each protein relative to TP1 in each carbon sources. Each line indicates fold change or temporal profile (cellulose, red; xylan, purple; green, galactomannan; pectin, blue) (PDF 563 kb)

Pathway analysis of tricarboxylic acid cycle. Tricarboxylic acid cycle was constructed from KEGG. White box indicates the fold change of each protein relative to glucose at the same time point, and gray box indicates temporal profile of each protein relative to TP1 in each carbon source. Each line indicates fold change or temporal profile (cellulose, red; xylan, purple; galactomannan, green; pectin, blue) (PDF 708 kb)

Pathway analysis of xylan degradation and metabolism. Pathway of xylan degradation and metabolism was constructed from KEGG. White box indicates the fold change of each protein relative to glucose at the same time point, and gray box indicates temporal profile of each protein relative to TP1 in each carbon source. Each line indicates fold change or temporal profile (cellulose, red; xylan, purple; galactomannan, green; pectin, blue) (PDF 344 kb)

Pathway analysis of galactomannan degradation and metabolism. (a) Pathway of mannan degradation and metabolism; (b) galactose degradation and metabolism pathway A. Each pathway was constructed from KEGG. White box indicates the fold change of each protein relative to glucose at the same time point, and gray box indicates temporal profile of each protein relative to TP1 in each carbon source. Each line indicates fold change or temporal profile (cellulose, red; xylan, purple; galactomannan, green; pectin, blue) (PDF 699 kb)

Pathway analysis of pectin degradation and metabolism. Pathway of pectin degradation and metabolism was constructed from KEGG. White box indicates the fold change of each protein relative to glucose at the same time point, and gray box indicates temporal profile of each protein relative to TP1 in each carbon source. Each line indicates fold change or temporal profile (cellulose, red; xylan, purple; galactomannan, green; pectin, blue) (PDF 656 kb)

To elucidate the pathogenesis of rheumatoid arthritis (RA), we used proteomic analysis to determine the protein profile in a synovial cell line, MH7A, established from patients with RA. Proteins were extracted from MH7A cells that were or were not stimulated with tumor necrosis factor-α (TNF-α), and then analyzed on a liquid chromatography/mass spectrometry system equipped with a unique long monolithic silica capillary. On the basis of the results of this proteomic analysis, we identified 2650 proteins from untreated MH7A cells and 2688 proteins from MH7A cells stimulated with TNF-α. Next, we selected 269 differentially produced proteins that were detected only under TNF-α stimulation, and classified these proteins by performing gene ontology analysis by using DAVID as a functional annotation tool. In TNF-α-stimulated MH7A cells, we observed substantial production of plasminogen-activator inhibitor 2 and apoptosis-regulating proteins such as BH3-interacting domain death agonist, autophagy protein 5, apolipoprotein E, and caspase-3. These results indicate that the upregulation of plasminogen-activator inhibitor 2 and apoptosis-regulating proteins in synovial cells in response to TNF-α stimulation might represent a predominant factor that contributes to the pathogenesis of RA.