Tomas Kalina,1* Karel Fišer,1* Martin Pérez-Andrés,2 Daniela Kužílková,1 Marta Cuenca,3 Sophinus J.W. Bartol,4 Elena Blanco,2 Pablo Engel,3 Menno C. van Zelm,4,5 on behalf of the Human Cell Differentiation Molecules (HCDM) organization

1 CLIP - Childhood Leukaemia Investigation Prague, Department of Paediatric Haematology and Oncology, Charles University, Prague, Czech Republic and University Hospital Motol, Prague, Czech Republic
2 Department of Medicine, Cancer Research Centre (IBMCC, USAL-CSIC), Cytometry Service (NUCLEUS), University of Salamanca (USAL), Institute of Biomedical Research of Salamanca (IBSAL), Salamanca, Spain and Biomedical Research Networking Centre Consortium of Oncology (CIBERONC) Instituto de salud Carlos III, Madrid, Spain
3 Department of Biomedical Sciences, University of Barcelona, Barcelona, Spain
4 Department of Immunology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
5 Department of Immunology and Pathology, Monash University and The Alfred Hospital, Melbourne, VIC, Australia

* equal contribution

Correspondence:
A/Prof Menno C. van Zelm
Department of Immunology and Pathology
Monash University and Alfred Hospital
89 Commercial road
Melbourne VIC 3004
E: 




Abstract

CD molecules are surface molecules expressed on cells of the immune system that play key roles in immune cell-cell communication and sensing the microenvironment. These molecules are essential markers for the identification and isolation of leukocytes and lymphocyte subsets.

Here, we present the results of the first phase of the CD Maps study, mapping the expression of CD1-100 (n=110) on 47 immune cell subsets from blood, thymus and tonsil using an 8-color standardized EuroFlow approach and quantification of expression.

The resulting dataset included median antibody binding capacities (ABC) and percentage of positivity for all markers on all subsets and was developed into an interactive CD Maps web resource. Using the resource, we examined differentially expressed proteins between granulocyte, monocyte and dendritic cell subsets, and profiled dynamic expression of markers during thymocyte differentiation, T-cell maturation, and between functionally distinct B-cell subset clusters.

The CD Maps resource will serve as a benchmark of antibody reactivities ensuring improved reproducibility of flow cytometry-based research. Moreover, it will provide a full picture of the surfaceome of human immune cells and serves as a useful platform to increase our understanding of leukocyte biology, as well as, to facilitate the identification of new biomarkers and therapeutic targets.




List of Figures and Tables

Methods




Introduction

Leukocytes display on their surface molecules that are crucial for sensing hazardous environmental changes and mediating cell adhesion and communication between cells both within the immune system and with stroma. These include receptors, transporters, channels, cell-adhesion proteins and enzymes. The complexity of surface-expressed proteins, also called the surfaceome, is emphasized by the fact that an estimated 26% of human genes encode transmembrane proteins (~5500).1 However, recent in silico evaluations predict that 2886 proteins are actually expressed at the outer cell membrane, i.e. the cell surface.2 Experimental evidence exists for ~1492 proteins across multiple tissues,3 and 1015 proteins that are expressed in one or more immune cell type and lymphoid tissue.4

Over the past four decades, a vast array of cell surface molecules has been discovered through the production of monoclonal antibodies (mAbs).5 These mAbs, together with the development of multicolor flow cytometric analysis,6 have been instrumental to determine their expression and function. Human Leukocyte Differentiation Antigen (HLDA) Workshops have led to the characterization and formal designation of more than 400 surface molecules,7, 8 known as CD molecules. CD nomenclature provides a unified designation system for mAbs, as well as for the cell surface molecules that they recognize. These molecules include receptors, adhesion molecules, membrane-bound enzymes and glycans that play multiple roles in leukocyte development, activation and differentiation. CD molecules are routinely used as cell markers, allowing the identification of the presence and proportions of specific leukocyte cell populations and lymphocyte subsets, and their isolation, using combinations of fluorochrome labeled antibodies and flow cytometry. Importantly, analysis of CD molecules, known as immunophenotyping, is a fundamental component for the diagnosis, classification and follow-up of hematological malignancies and immune deficiencies, and the monitoring of immune system disorders such as autoimmune diseases. More recently, mAbs recognizing CD molecules have been established as invaluable tools for the treatment of cancer, such as checkpoint inhibitors,9 and autoimmune diseases.10 Development and testing of such therapeutics does rely on accurate knowledge expression and function of the target molecule as has been negatively illustrated by the disaster in the Phase I TGN1412 study with an anti-CD28 superagonist.11

Currently, there are extensive gaps in our knowledge of CD molecule expression patterns, mainly because of the discordancy in the setup of the expression studies and the major changes in flow cytometry technology over the last 30 years.12 As a result, there has been overinterpretation in summarizing tables, which can be misleading. Thus, there is an urgent need to construct a higher resolution and accurate map of the expression profiles of the CD molecules to visualize the surface of leukocyte landscape. Moreover, an important part of the bibliography is incorrect and often misleading.

To correct current misinterpretation and to overcome gaps in knowledge, the HCDM has initiated the CD Maps project, a multi-institute research program to generate a high-resolution map of the cell surface of human immune cells using standardized multicolor flowcytometry protocols. Here, we present the results of the first phase of the CD Maps study which includes the expression signature of CD1-CD100 on 47 cell populations and subsets, 41 of which were non-overlapping. The data have been acquired across 4 expert flowcytometry laboratories to ensure reproducibility, and have been built into an online web resource with free user access. Expression profiling of CD markers across immune cell subsets revealed dynamic changes in expression levels, and hints at further immune cell diversity for markers that were expressed on a fraction of defined populations.





Results


I. Generation of a web resource for expression profiling of CD1-CD100 on major immune cell lineages and their subsets

To investigate the expression levels on major leukocytes subsets of the first surface molecules that had been defined in the 1980s and early 1990s with CD markers 1-100,8, 13, 14 we developed a multi-color immune phenotyping panel consisting of 4 tubes. Seven detection channels were utilized for backbone markers to define cell subsets (Suppl Table 3), and one channel was reserved for a PE-labeled drop-in monoclonal antibody directed against one of the CD1-CD100 antigens (Suppl Table 4). The backbone markers in tubes A and B were directed against innate and adaptive immune cell subsets from blood, respectively, in tube C against B-cell subsets from tonsil tissue and in tube D against T-cell progenitors in thymus. Through stepwise gating strategies for all 4 tubes (Suppl Figures 1-4), a total of 47 cell types and subsets therein were defined (Suppl Table 5).

Following protocol optimization and standardization, 12 biological repeats for blood, tonsil and thymus tissue were subjected to expression analysis of 110 unique targets of CD1-CD100 across four laboratories. Post curation (details in Methods), expression analysis was performed on 9 biological repeats for tube A, 11 for tube B, 7 for tube C and 5 for tube D. Multiple descriptors of CD marker expression were defined for each gated cell subsets and exported (Supplementary Figure 5A). Most notable are the median fluorescence intensity, which was converted to antibody binding capacity (ABC) using the QuantiBRITE bead measurements, and the percentage of positive cells using the FMO control value as cut-off.

The resulting dataset consisted of over a million datapoints of derived statistics and annotation information that together form a quantitative insight into the cell surfaceome of the human immune system. To make the data accessible as a major resource for detailed studies by us and the scientific community, we constructed an interactive web-based application (Figure 1). The resource contains multiple features to visualize the complete dataset (e.g. Principal Component Analysis; PCA), and to examine specific cell lineages and/or subsets (e.g. significantly differentially expressed markers or patterns of expression during cell maturation).