Summary of first round cluster analysis: complete antibody panel

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Summary of first round cluster analysis: complete antibody panel M.M. Carr a'*, J.K. Lunney b, S. Arn c, B. Aasted d, R.M. Binns e, W.C. Davis f, C. Choi g, C.J. Howard a, M. Misfeldt h, T. Molitor g, M. Murtaugh g, M. Pescovitz i, A. Saalmfiller j, D. Sachs c, P. Sopp a, K. Walker b aAFR C, Institute for Animal Health, Compton, Newbury, RG16 ONN, UK bUSDA, ARS, Helminthic Diseases Lab., Beltsville, MD 20705, USA CTransplantation Biomedical Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA dDepartment of Veterinary Virology and Immunology, Royal Veterinary University, DK 1870 Frederiksberg C, Denmark eThe Babraham Institute, Babraham, Cambridge, CB2 4AT, UK fDepartment of Veterinary Microbiology and Pathology, Washington State University, Pullman, WA 99164, USA gDepartment of Veterinary Pathobiology, University of Minnesota, St. Paul, MN55108, USA hDepartment of Medicine Microbiology and Immunology, University of Missouri School of Medicine, Columbia, MO 65212, USA ilndiana University, Department of Surgery, Indianapolis, IN 46202, USA JFederal Research Centre for Virus Diseases of Animals, 7400 Tubingen, Germany

Abstract The reactivities o f 141 monoclonal antibodies ( m A b s ) with 60 target cell types or lines were analysed by flow cytometry and the data subjected to statistical clustering, mAbs were assigned to 23 clusters by statistical similarity and information on specificity supplied by the contributor. Clustered mAbs were examined in more detail in the second round of workshop analyses.

1. Introduction The aim of the first round cluster analysis was to identify groups of monoclonal antibodies (mAbs) with statistically similar patterns of reactivities. A restricted * Corresponding author. 0165-2427/94/$07.00 © 1994 Elsevier Science B.V. All rights reserved SSDI 0165-2427 ( 94 ) 06026-V

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number of laboratories collected flow cytometry data for the complete mAb panel on a variety of target cells. These data were analysed using a computer software package. The statistically similar clusters of mAbs generated from these data were to be used as guidelines for the second round of the workshop analyses, alongside information supplied by the contributors on mAb specificity. The final mAb specificities and workshop nomenclature were to be decided after the second round of workshop analyses. For the purposes of this paper, the specificities described at this early stage of analysis are putative. In the text, mAbs are referred to by workshop number, followed by mAb names in parentheses.

2. Materials and methods

2.1. Monoclonal antibodies The complete mAb panel consisted of 136 mAbs submitted to the workshop, four control duplicate mAbs and a medium-only control. The duplicated mAbs were: 001 and 138 (76-7-4, specific for porcine CD1 ); 002 and 137 (74-12-4, specific for porcine CD4a); 003 and 139 (74-22-15, reactive with porcine macrophages and granulocytes); 020 and 141 (MAC320, a rat mAb reactive with porcine Null cells). The identities of these duplicate mAbs were withheld from participants and decoded only after completion of the first round clustering. These paired mAbs were used as control standards to test the reproducibility and, therefore, the quality of the flow cytometry data.

2.2. Target cells Target cells were selected for antigenic diversity and included purified pig cell populations, cloned pig cell lines, human leukaemic cell lines and mouse cell lines transfected with pig genes. The percentage reactivity of each mAb for each target was assessed after subtraction of non-specific background staining with the appropriate second stage reagent. These flow cytometric data and details of targets can be found in the Appendix to this volume.

2.3. Statistical clustering and interpretation of the dendrogram The quality of the flow cytometric data was checked by comparing the percentage reactivities of the duplicate control mAbs on each target cell preparation. In several preliminary clusterings, target data sets were excluded if the difference in percentage reactivity between the duplicate mAbs was greater than, for example, 10 or 15%. Although several of the target data sets had more than 20% variability between duplicate mAbs, exclusion of data adversely affected the cluster results.

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It was decided that the final first round dendrogram should be derived from all 60 target data sets. The Leucocyte Typing Database 4 program which was used for the statistical analysis presents the results as a dendrogram; the more statistically similar the mAbs, the further to the left of the dendrogram they are joined. Thus, mAbs detecting the same antigen should cluster closely together with a joining probability to the left of the dendrogram. 3. Results Fig. 1 is a dendrogram showing the statistical similarities of the complete panel of mAbs submitted to the First International Swine Leucocyte CD Antigen workshop. In this first round analysis, 23 mAb clusters were assigned by statistical £o 67.447 p1.00000

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Fig. 1. A dendrogram representing the results of cluster analysis for all monoclonal antibodies submitted to the workshop. For presentation purposes the dendrogram has been divided into four sections. FC: first round antibody cluster; U: unclustered antibody.

similarity and information on specificity supplied by the contributors of mAbs. Six groups of mAbs, containing one or more clusters, were identified. These groups of mAbs had putative specificities for C D 4 4 / 4 5 , MHC Class II, T activation antigens, myeloid cells, Null/B cells and T cells. Four mAbs were unclustered and were given the designation 'U'.

3.1. Clusters I, 2, 3, 4 and 5 (putative specificity: CD44/45) Clusters 1-5 contained 26 mAbs in total, many of which had a known specificity for CD44 or CD45. An unclustered rat mAb (018, MAC325) has also been included in this group because of its known specificity for CD44. Two rat mAbs (023, MAC83; 024, MAC80), specific for the T cell differentiation antigen, CD2,

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were statistically closely related to the CD45-specific mAbs in Cluster 5 (Zuckermann et al. 1994). 3.2. Clusters 6 and 7 (putative specificity: M H C Class II) Seven mAbs with specificity for MHC Class II formed Clusters 6 and 7. MHC II DR and DQ were both represented. Provisional assignment to mAbs of DR or DQ specificity was based on their reactivity with SLA-DR or SLA-DQ transfected mouse cell lines. These clusters were not studied further in the workshop. 3.3. Clusters 8 and 9 Clusters 8 and 9 contained two and three mAbs, respectively. These clusters showed no clear pattern of reactivity, containing mAbs with putative specificities for T cells (050, PG1A; 075, PG108A; 076, PG132A), Null cells (063, PT14A) and erythrocytes (098, ANAl 8A). 3.4. Cluster 10 (putative specificity: T cell activation antigens) Cluster 10 contained 14 mAbs with putative specificities for swine T cell activation antigens. Also included were three mAbs (037, PNK-I; 077, H2OA; 136, MHM-23 ) considered to be reactive with CD 18a, and one mAb (078, MUC76A) with CD 11 / 18 (Saalmiiller et al. 1994 ). 3.5. Clusters 11, 12, 13 and 14 (putative specificity: myeloid cells) Sixteen mAbs specific for myeloid cells fell into Clusters 11-14 (Blecha et al., this volume). Workshop duplicate control mAbs 003 and 139 (74-22-15) were both in Cluster 14. 3.6. Clusters 15 and 16 These clusters showed no clear pattern of reactivity, mAbs 025 (62.14.7) and 072 (MUCI06A) formed Cluster 15. These mAbs had putative reactivities with T and B cells, respectively. Cluster 16 contained four mAbs with diverse reactivities, including myeloid cells only (040, 1G 1 ), T cells/myeloid cells (026, 62.41.5 ) and Null cells/myeloid cells (038, C4; 039, 2B8 ). 3.7. Clusters 17, 18 and 23 (putative specificity: Null cells and B cells) Twenty-two mAbs grouped together in Cluster 18 and were specific for Null cells only (Binns et al. 1994, this volume), or B cells only (Denham et al. 1994, or both Null and B cells, mAb 032 (PM 18-7) in Cluster 18 had lost specific activity due to acid treatment. The four mAbs in Cluster 23 were reactive only with Null cells and included

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the duplicated standard control mAbs 020 and 141 (MAC320, a rat mAb specific for porcine Null cells). Cluster 17 contained the duplicate control mAbs 001 and 138 (76-7-4, which detects the CD1 antigen), mAb 123 (LIG 4), which detects porcine IgM, was also included in this cluster.

3.8. Clusters 19 and 20 (putative specificity: T cells) Clusters 19 and 20 included 20 and nine mAbs, respectively, mAbs which detect the T cell differentiation antigens CD2, CD4, CD5, CD6 and CD8 were present in these clusters (Saalmfiller et al., this volume ). All mAbs in Cluster 19 were identified as being T cell specific. In Cluster 20, all mAbs were specific for T cell differentiation antigens, with the exception of 074 ( P G 104A), 064 (PT79A) and 065 (MUC127A).

3.9. Cluster 22 Cluster 22 contained two mAbs (027 and 028). mAb 027 (K231.3B2) is specific for CD25, the receptor molecule for interleukin-2.

3.10. Unclustered mAbs Four mAbs (018, 043, 115 and 101 ) were unique and did not cluster, mAbs 018 (MAC323) and 043 (2F4) were statistically most similar to the CD44/45 group. mAb 115 (2A5) was most closely related to Cluster 8, which contained two mAbs of different reactivities, mAb 010 (86D), originally raised against the ovine 7/3 T cell receptor (TcR), reacts with the y/d TcR in pigs but was most related to Cluster 21 (099, blank control, no data except background non-specific staining; 006, 74-9-3, specific for CD45). These statistical similarities are spurious since mAbs 010 and 006 had lost specific activity (indicated by an 'X' in Table 1, Lunney et al. 1994) during the processing required for US import regulations.

4. Discussion

The first round cluster analysis provided guidelines for groups of mAbs to be examined in the second round cluster analysis. Statistical clustering was most successful for mAbs specific to M H C Class II antigens, T cell activation antigens, T cells and CD44/45. This reflects the high number of appropriate targets for identifying the T cell antigens relative to B cell or Null cell targets. However, these T cell-specific target cells were limited in their ability to discriminate between mAbs specific for the major T cell antigens CD2, CD4 and CD8. Thus, although a large T cell-specific group of mAbs was identified, clustering was random within this group. Cultured cell lines represent a relatively pure population

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with respect to surface antigen expression compared with tissue isolates and are, therefore, valuable targets for successful clustering. For example, clustering of the MHC Class II antigens was particularly successful because mouse cell lines transfected with SLA-II DQ and DR were available. Conversely, a paucity of appropriate target cell types resulted in weak clustering of mAbs specific to Null cell and B cell antigens. Also, target cell types commonly used in the workshop, e.g. whole pig blood, contained similar proportions of Null and B cells. As a result, mAbs for these cell types clustered together. It is recommended for future workshops that early analyses include more cell lines and pure Null and B cell targets. Weak clustering was also symptomatic of technical problems, such as inappropriate second stage reagent; high auto-fluorescence of some target cell types, e.g. alveolar macrophages, which obscured specific staining with workshop mAbs; the % reactivity of positively stained cells being assessed subjectively and for individual mAbs rather than objectively using a negative control sample; incorrect or unknown titre of mAbs supplied to the workshop. Some mAbs also clustered incorrectly because of specific activity being lost during the acidification procedure required for mAb import into the US. Given these difficulties, the first round cluster analysis provided valuable information for participants in the later stages of the workshop.

References Binns et al. (1994), Vet. Immun. lmmunopathol. (this issue) Blecha et al. (1994), Vet. Immun. Immunopathol. (this issue) Denham et al. (1994), Vet. Immun. Immunopathol. (this issue) Lunney et al. (1994), Vet. Immun. Immunopathol. (this issue) Saalmiiller et al. (1994), Vet. Immun. Immunopathol. (this issue) Zuckermann et al. (1994), Vet. Immun. Immunopathol. (1994) (this issue)