title: Automation of sample preparation for mass cytometry barcoding in support of clinical research: protocol optimization.
abstract: Analysis of multiplexed assays is highly important for clinical diagnostics and other analytical applications. Mass cytometry enables multi-dimensional, single-cell analysis of cell type and state. In mass cytometry, the rare earth metals used as reporters on antibodies allow determination of marker expression in individual cells. Barcode-based bioassays for CyTOF are able to encode and decode for different experimental conditions or samples within the same experiment, facilitating progress in producing straightforward and consistent results. Herein, an integrated protocol for automated sample preparation for barcoding used in conjunction with mass cytometry for clinical bioanalysis samples is described; we offer results of our work with barcoding protocol optimization. In addition, we present some points to be considered in order to minimize the variability of quantitative mass cytometry measurements. For example, we discuss the importance of having multiple populations during titration of the antibodies and effect of storage and shipping of labelled samples on the stability of staining for purposes of CyTOF analysis. Data quality is not affected when labelled samples are stored either frozen or at 4 °C and used within 10 days; we observed that cell loss is greater if cells are washed with deionized water prior to shipment or are shipped in lower concentration. Once the labelled samples for CyTOF are suspended in deionized water, the analysis should be performed expeditiously, preferably within the first hour. Damage can be minimized if the cells are resuspended in phosphate-buffered saline (PBS) rather than deionized water while waiting for data acquisition.
authors.affiliation: School of Medicine, Department of Internal Medicine, Yale University, 300 Cedar St./TAC s416, New Haven, CT, 06510, USA. ala.nassar@yale.edu.|Department of Chemistry, University of Connecticut, 55 North Eagleville Road, Storrs, CT, 06269, USA. ala.nassar@yale.edu.
authors.forename: Ala F
authors.initials: AF
authors.lastname: Nassar
authors.affiliation: School of Medicine, Department of Internal Medicine, Yale University, 300 Cedar St./TAC s416, New Haven, CT, 06510, USA.
authors.forename: Adam V
authors.initials: AV
authors.lastname: Wisnewski
authors.affiliation: Department of Neurology, Yale School of Medicine, New Haven, CT, 06511, USA.
authors.forename: Khadir
authors.initials: K
authors.lastname: Raddassi
mesh_terms: D000906:Antibodies / Q000032:analysis; D001331:Automation; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D059010:Single-Cell Analysis / Q000379:methods*; D013048:Specimen Handling
chemical_list: D000906:Antibodies
keywords: Barcoding; CyTOF; Mass cytometry; Multiplexing