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Automation of flow cytometric antibody screening and reporting
S74
Abstracts
2.03 #58
ANALYSES OF ENTRIES IN THE HLA LIGAND/MOTIF DATABASE AND THE PREDICTIVE ALGORITHMS EMPOWERED BY THESE DATA Muthuraman Sathiamurthy, Heather D. Hickman, Joshua W. Cavett, William H. Hildebrand. Department of Microbiology/Immunology, Univ of Oklahoma Health Sciences Center, Oklahoma City, OK We maintain an NIH funded HLA Ligand Database that is publicly available on the World Wide Web at http://hlaligand.ouhsc.edu. The main goal of the database is to provide a bridge for researchers and clinicians to logically access (1) the complex and rapidly expanding HLA ligand and motif data set, and (2) predictive algorithms that utilize the database for identification of new peptide epitopes. Here we discuss the parameters of the dataset and address the question “How many ligands are required to support accurate predictions of peptide binding to HLA?” The HLA epitope binding prediction algorithm available on the database predicts epitopes that bind sequences using an un-weighted, dynamic amino acid frequency table. Due to the dynamic nature of this algorithm, the important factor that drives algorithm accuracy is the number of endogenous ligands databased for each allele. In order to analyze the minimum number of endogenous ligands needed for accurate prediction, we input the prediction algorithm with randomly selected A*0201 peptides in additive groups of 10 (for example). We then entered the HIV gag protein and tested the algorithm’s ability to predict A*0201binding of the well-characterized gag epitope SLYNTVATL (SL9). Multiple randomized trials were carried out with random peptide sets of different sizes and a median dataset size was determined for SL9 prediction. These experiments allow us to extrapolate the minimum number of ligands necessary for algorithm accuracy. A complete understanding of the minimum dataset for accurate ligand prediction will allow better algorithms for the study of minor histocompatibility antigens, cancer CTL epitopes, and viral ligands.
3.01 #59
AUTOMATION OF FLOW CYTOMETRIC ANTIBODY SCREENING AND REPORTING Stephanie Tipton,1 Kim Holden,1 John Kreuziger,1 Ellen Klohe,1 Scot Townshend,2 Susan Metz.2 1HLA Laboratory, Inland Northwest Blood Center, Spokane, WA; 2SystemLink, Inc., Chantilly, VA One Lambda Flow PRA™ beads are a highly sensitive and specific means to determine the presence of IgG anti-HLA antibodies in patient sera and is the method we employ for monthly antibody screening of our growing kidney transplant candidate list. We have incorporated software interfaces to accommodate the management of large volume test data generated by the One Lambda FlowPRA™ screening assays. SystemLink’s lab management software, HistoTrac™, facilitates the data management through the use of an interface with the Becton-Dickinson flow cytometer analysis software, CellQuest™, and through the ability to upload PRA results into UNet. The HistoTrac™ batch and labeling modules allow for the accessioning and sample label creation for large numbers of samples. Once a batch is created, a worklist is set up using the interface and imported directly into the Worklist Manager program for acquisition by AutoLoader™ on the FACSCalibur™ flow cytometer. Following acquisition, batch analysis of the data is performed with CellQuest™ and the PRA values generated from the analysis are exported, for import into HistoTrac™. Once reviewed, the PRA data are exported from HistoTrac™ for upload into UNet. This streamlining of data has significantly reduced the time required for data entry and reduced the potential for transcription errors. Additionally, since the interfaces occur at multiple stages, it is possible to make changes or additions throughout the process.
Abstracts
2.03 #58
ANALYSES OF ENTRIES IN THE HLA LIGAND/MOTIF DATABASE AND THE PREDICTIVE ALGORITHMS EMPOWERED BY THESE DATA Muthuraman Sathiamurthy, Heather D. Hickman, Joshua W. Cavett, William H. Hildebrand. Department of Microbiology/Immunology, Univ of Oklahoma Health Sciences Center, Oklahoma City, OK We maintain an NIH funded HLA Ligand Database that is publicly available on the World Wide Web at http://hlaligand.ouhsc.edu. The main goal of the database is to provide a bridge for researchers and clinicians to logically access (1) the complex and rapidly expanding HLA ligand and motif data set, and (2) predictive algorithms that utilize the database for identification of new peptide epitopes. Here we discuss the parameters of the dataset and address the question “How many ligands are required to support accurate predictions of peptide binding to HLA?” The HLA epitope binding prediction algorithm available on the database predicts epitopes that bind sequences using an un-weighted, dynamic amino acid frequency table. Due to the dynamic nature of this algorithm, the important factor that drives algorithm accuracy is the number of endogenous ligands databased for each allele. In order to analyze the minimum number of endogenous ligands needed for accurate prediction, we input the prediction algorithm with randomly selected A*0201 peptides in additive groups of 10 (for example). We then entered the HIV gag protein and tested the algorithm’s ability to predict A*0201binding of the well-characterized gag epitope SLYNTVATL (SL9). Multiple randomized trials were carried out with random peptide sets of different sizes and a median dataset size was determined for SL9 prediction. These experiments allow us to extrapolate the minimum number of ligands necessary for algorithm accuracy. A complete understanding of the minimum dataset for accurate ligand prediction will allow better algorithms for the study of minor histocompatibility antigens, cancer CTL epitopes, and viral ligands.
3.01 #59
AUTOMATION OF FLOW CYTOMETRIC ANTIBODY SCREENING AND REPORTING Stephanie Tipton,1 Kim Holden,1 John Kreuziger,1 Ellen Klohe,1 Scot Townshend,2 Susan Metz.2 1HLA Laboratory, Inland Northwest Blood Center, Spokane, WA; 2SystemLink, Inc., Chantilly, VA One Lambda Flow PRA™ beads are a highly sensitive and specific means to determine the presence of IgG anti-HLA antibodies in patient sera and is the method we employ for monthly antibody screening of our growing kidney transplant candidate list. We have incorporated software interfaces to accommodate the management of large volume test data generated by the One Lambda FlowPRA™ screening assays. SystemLink’s lab management software, HistoTrac™, facilitates the data management through the use of an interface with the Becton-Dickinson flow cytometer analysis software, CellQuest™, and through the ability to upload PRA results into UNet. The HistoTrac™ batch and labeling modules allow for the accessioning and sample label creation for large numbers of samples. Once a batch is created, a worklist is set up using the interface and imported directly into the Worklist Manager program for acquisition by AutoLoader™ on the FACSCalibur™ flow cytometer. Following acquisition, batch analysis of the data is performed with CellQuest™ and the PRA values generated from the analysis are exported, for import into HistoTrac™. Once reviewed, the PRA data are exported from HistoTrac™ for upload into UNet. This streamlining of data has significantly reduced the time required for data entry and reduced the potential for transcription errors. Additionally, since the interfaces occur at multiple stages, it is possible to make changes or additions throughout the process.