Surface morphology of murine B and T lymphocytes: A comparative study by scanning electron microscopy

A variety of murine lymphocytes of known B or T derivation obtained from different lymphoid organs were prepared for scanning electron microscopy (SEM) by the critical point drying method after collecting the cells by aspiration onto silver membranes. Comparison of SEM appearances of cells prepared by this technique and serological classification according to surface antigens showed that most T cells had smooth surfaces with few microvilli, while many B lymphocytes were moderately to markedly villous. Further evidence for the above correlation was obtained by examining thymic cells and enriched B or T cell populations. Thymic cell suspensions containing less than 5% B cells showed over 80% generally smooth cells by SEM. Enriched T cell populations, obtained by mass cytolysis of lymph node preparations with anti-Ia or anti-Ig sera or by purification through nylon fiber columns, contained over 85% T cells, and more than 75% of them were of the smooth cell type. A similar correlation was noted for enriched B cell populations obtained by cytolysis of lymph node cells with anti-Thy-1 serum, and by lysis of EAC-rosettes. Over 90% of these cells were identified as B cells by immunologic methods and approximately 75% had moderate to markedly villous surfaces. The 15% difference can be accounted for by the existence of a subpopulation of smooth B cells. Direct observation of EAC-rosettes confirmed that most B cells had moderate to large numbers of surface microvilli and that less than 10% were smooth. It is possible that some of the smooth cells seen in enriched B cell populations may represent precursors or B lymphocytes at different stages of differentiation. These results indicate that murine T and B lymphocytes, like their human counterparts, can be recognized in many cases under the SEM on the basis of their surface morphology. Smoother B and more villous T cells are difficult to classify by SEM without parallel immunologic identification.