Fiona (Fumiko) Yamamoto

All Publications

• Next-generation HLA typing of 382 International Histocompatibility Working Group reference B-lymphoblastoid cell lines: Report from the 17th International HLA and Immunogenetics Workshop Creary, L. E., Guerra, S. G., Chong, W., Brown, C. J., Turner, T. R., Robinson, J., Bultitude, W. P., Mayor, N. P., Marsh, S. E., Saito, K., Lam, K., Duke, J. L., Mosbruger, T. L., Ferriola, D., Monos, D., Willis, A., Askar, M., Fischer, G., Saw, C., Ragoussis, J., Petrek, M., Serra-Pages, C., Juan, M., Stavropoulos-Giokas, C., Dinou, A., Ameen, R., Al Shemmari, S., Spierings, E., Gendzekhadze, K., Morris, G. P., Zhang, Q., Kashi, Z., Hsu, S., Gangavarapu, S., Mallempati, K. C., Yamamoto, F., Osoegawa, K., Vayntrub, T., Chang, C., Hansen, J. A., Fernandez-Vina, M. A. ELSEVIER SCIENCE INC. 2019: 449–60

  View details for DOI 10.1016/j.humimm.2019.03.001

  View details for Web of Science ID 000474324200013

• Mapping and definition of HLA class I and II serologic epitopes using an unbiased reverse engineering strategy. Human immunology Yamamoto, F., Wang, L., Chang, C., Tyan, D. B. 2019

  Abstract

  Current models describing HLA epitopes are both theoretical and empirical. Each has limitations yielding discordant results and increasingly complex modeling. The models make a priori assumptions that epitopes must be present only on the mature protein, solvent accessible, on the 'top' (peptide binding surface) of the molecule, restricted to the same class as the antibody, and in the same position on the target allele if reactive to more than one locus. Results obtained counter to these assumptions are routinely discounted. For the 17th International Histocompatibility and Immunogenetics Workshop, we developed a reverse engineering algorithm to define epitopes without these assumptions on a cohort of 332 primary transplant pairs. Complete NGS typing of the transcribed (including leader) genomic DNA for 11 HLA loci of donor and recipient and DSA assignment by single antigen beads was performed. Our results show that, when grouped by 16 class I and II allele specific DSA, uniform clusters and 172 specific amino acid target epitopes are recognized by recipients despite originating from disparate HLA pairs. Data also show that these targets can be in the leader, alpha 3, transmembrane and cytoplasmic domains, thus calling into question current assumptions regarding immunogenic epitopes. Comparisons of amino acid epitopes defined by the Terasaki and Duquesnoy groups (TerEp and EpRegistry) are given.

  View details for DOI 10.1016/j.humimm.2019.04.004

  View details for PubMedID 31122739

• A reverse-engineering strategy utilizing the integration of single antigen beads and NGS HLA genotypes to detect potential antibody inducing epitopes. Human immunology Chang, C., Yamamoto, F., Tyan, D. B. 2019

  Abstract

  Central to the idea of antibody recognition is some degree of foreignness of the target antigen compared to the antibody producer. Epitopes are distinct regions on an antigen to which antibody can be elicited and bound. However, for HLA antigens, there is no consensus definition of what represents the minimal functional immunogenic unit of dissimilarity. To assess this in an unbiased way, we developed a reverse engineering software strategy based on donor specific antibodies defined by single antigen beads and full length genomic high resolution HLA typing by NGS of recipients and donors (332 transplant pairs). Starting with the ATG of Exon 1 and moving stepwise one amino acid at a time for each of the following triplets, the algorithm compared every possible amino acid triplet of the recipient and donor for 11 loci (A, B, C, DRB1, DRB3, DRB4, DRB5, DQA1, DQB1, DPA1, DPB1). Results were agnostic with respect to HLA class, not restricted to just the mature protein, and not influenced by existing maps (e.g., IMGT, or epitope models). We also developed web-based functions in the 17th IHIWS database to collect the unbiased triplets so that we could group the transplant pairs with the same donor specific antibodies and find shared triplets within the groups as potential core or essential epitopes that trigger the antibody formation. Profiling the pairs where the same DSA was identified led to identification of discrete amino acid triplets shared among the pairs irrespective of HLA match. The potential epitopes were mapped onto the 3D protein structure for reference.

  View details for PubMedID 30978444

• Quality control project of NGS HLA genotyping for the 17th International HLA and Immunogenetics Workshop Osoegawa, K., Vayntrub, T. A., Wenda, S., De Santis, D., Barsakis, K., Ivanova, M., Hsu, S., Barone, J., Holdsworth, R., Diviney, M., Askar, M., Willis, A., Railton, D., Laflin, S., Gendzekhadze, K., Oki, A., Sacchi, N., Mazzocco, M., Andreani, M., Ameen, R., Stavropoulos-Giokas, C., Dinou, A., Torres, M., Francisco, R., Serra-Pages, C., Goodridge, D., Balladares, S., Bettinotti, M. P., Iglehart, B., Kashi, Z., Martin, R., Saw, C., Ragoussis, J., Downing, J., Navarrete, C., Chong, W., Saito, K., Petrek, M., Tokic, S., Padros, K., Rodriguez, M., Zakharovaa, V., Shragina, O., Marino, S. R., Brown, N. K., Shiina, T., Suzuki, S., Spierings, E., Zhang, Q., Yin, Y., Morris, G. P., Hernandez, A., Ruiz, P., Khor, S., Tokunaga, K., Geretz, A., Thomas, R., Yamamoto, F., Mallempati, K. C., Gangavarapu, S., Kanga, U., Tyagi, S., Marsh, S. E., Bultitude, W. P., Liu, X., Cao, D., Penning, M., Hurley, C. K., Cesbron, A., Mueller, C., Mytilineos, J., Weimer, E. T., Bengtsson, M., Fischer, G., Hansen, J. A., Chang, C., Mack, S. J., Creary, L. E., Fernandez-Vina, M. A. ELSEVIER SCIENCE INC. 2019: 228–36

  View details for DOI 10.1016/j.humimm.2019.01.009

  View details for Web of Science ID 000463463900004

• Very high resolution single pass HLA genotyping using amplicon sequencing on the 454 next generation DNA sequencers: Comparison with Sanger sequencing HUMAN IMMUNOLOGY Yamamoto, F., Hoeglund, B., Fernandez-Vina, M., Tyan, D., Rastrou, M., Williams, T., Moonsamy, P., Goodridge, D., Anderson, M., Erlich, H. A., Holcomb, C. L. 2015; 76 (12): 910-916

  View details for DOI 10.1016/j.humimm.2015.05.002

  View details for Web of Science ID 000366437900006

  View details for PubMedID 26037172

• The Functional Characterization of Long Noncoding RNA SPRY4-IT1 in Human Melanoma Cells ONCOTARGET Mazar, J., Zhao, W., Khalil, A. M., Lee, B., Shelley, J., Govindarajan, S. S., Yamamoto, F., Ratnam, M., Aftab, M., Collins, S., Finck, B. N., Han, X., Mattick, J. S., Dinger, M. E., Perera, R. J. 2014; 5 (19): 8959–69

  Abstract

  Expression of the long noncoding RNA (lncRNA) SPRY4-IT1 is low in normal human melanocytes but high in melanoma cells. siRNA knockdown of SPRY4-IT1 blocks melanoma cell invasion and proliferation, and increases apoptosis. To investigate its function further, we affinity purified SPRY4-IT1 from melanoma cells and used mass spectrometry to identify the protein lipin 2, an enzyme that converts phosphatidate to diacylglycerol (DAG), as a major binding partner. SPRY4-IT1 knockdown increases the accumulation of lipin2 protein and upregulate the expression of diacylglycerol O-acyltransferase 2 (DGAT2) an enzyme involved in the conversion of DAG to triacylglycerol (TAG). When SPRY4-IT1 knockdown and control melanoma cells were subjected to shotgun lipidomics, an MS-based assay that permits the quantification of changes in the cellular lipid profile, we found that SPRY4-IT1 knockdown induced significant changes in a number of lipid species, including increased acyl carnitine, fatty acyl chains, and triacylglycerol (TAG). Together, these results suggest the possibility that SPRY4-IT1 knockdown may induce apoptosis via lipin 2-mediated alterations in lipid metabolism leading to cellular lipotoxicity.

  View details for DOI 10.18632/oncotarget.1863

  View details for Web of Science ID 000348033800011

  View details for PubMedID 25344859

  View details for PubMedCentralID PMC4253410

• Detection of cytomegalovirus drug resistance mutations by next-generation sequencing. Journal of clinical microbiology Sahoo, M. K., Lefterova, M. I., Yamamoto, F., Waggoner, J. J., Chou, S., Holmes, S. P., Anderson, M. W., Pinsky, B. A. 2013; 51 (11): 3700-3710

  Abstract

  Antiviral therapy for cytomegalovirus (CMV) plays an important role in the clinical management of solid organ and hematopoietic stem cell transplant recipients. However, CMV antiviral therapy can be complicated by drug resistance associated with mutations in the phosphotransferase UL97 and the DNA polymerase UL54. We have developed an amplicon-based high-throughput sequencing strategy for detecting CMV drug resistance mutations in clinical plasma specimens using a microfluidics PCR platform for multiplexed library preparation and a benchtop next-generation sequencing instrument. Plasmid clones of the UL97 and UL54 genes were used to demonstrate the low overall empirical error rate of the assay (0.189%) and to develop a statistical algorithm for identifying authentic low-abundance variants. The ability of the assay to detect resistance mutations was tested with mixes of wild-type and mutant plasmids, as well as clinical CMV isolates and plasma samples that were known to contain mutations that confer resistance. Finally, 48 clinical plasma specimens with a range of viral loads (394 to 2,191,011 copies/ml plasma) were sequenced using multiplexing of up to 24 specimens per run. This led to the identification of seven resistance mutations, three of which were present in <20% of the sequenced population. Thus, this assay offers more sensitive detection of minor variants and a higher multiplexing capacity than current methods for the genotypic detection of CMV drug resistance mutations.

  View details for DOI 10.1128/JCM.01605-13

  View details for PubMedID 23985916

• Overexpression of sense and antisense ced-9 in tobacco plants confers resistance to Meloidogyne incognita PLANT BIOTECHNOLOGY REPORTS Calderon-Urrea, A., Yamamoto, F., Padukkavidana, T., Bahaji, A., Cheng, D. W., Polack, G. W. 2012; 6 (4): 263-274

  View details for DOI 10.1007/s11816-012-0221-8

  View details for Web of Science ID 000310089600001