Computer-assisted analysis of in vivo cytotoxic T cell responses

Computational models in immunological methods: an historical review

The utilization of computational models in immunology dates from the birth of the science. From the description of antibody-antigen binding to the structural models of receptors, models are utilized to bring fundamental understandings of the processes together with laboratory measurements to uncover implications of these data. In this review, an historical view of the role of computational models in the immunology laboratory is presented, and short mathematical descriptions are given of fundamental assays. In addition, the range of current uses of models is explored -- especially as seen through papers which have appeared in the Journal of Immunological Methods from volume 1 (1971/1972) to volume 208 (1997). Each paper which introduced a new mathematical, statistical, or computer simulation model, or introduced an enhancement to an instrument through a model in those volumes is cited and the type of computational model noted.

Suppression induction in vivo by a T helper clone?

We have previously described a helper T cell clone which augments in vivo cytotoxic T cell responses when injected at 10(4) cells per mouse, but not at 10(5) per mouse (Crispe, I. N. et al., Immunology 1984. 52:55). To test whether this dose-response relationship was due to the induction of suppression, naive syngeneic mice were injected with 10(5) cloned T helper cells, and their spleen cells were subsequently assayed for suppressive activity in adoptive transfer experiments. Lymphocytes from such mice indeed suppressed an antigen-specific cytotoxic response, but only in the presence of the same T helper cell clone freshly added at the time of adoptive transfer. On this basis we argue that the distinction between T helper cell activity and T suppressor-inducer activity corresponds to differences in cell numbers, rather than to two separate cell lineages.

Suppression of the cytotoxic T cell response to minor alloantigens in vivo. II. Fine specificity of suppressor T cells and lack of restriction by immunoglobulin heavy chain-linked gene products

While it has been widely reported that some subsets of suppressor T cells are restricted by products of immunoglobulin heavy chain genes (particularly the variable region gene), we have been unable to find evidence for such interactions in the suppression of the primary in vivo cytotoxic T cell response to minor alloantigen. We have also examined the repertoire of the suppressor T cells active in this system and find that they recognize a different set of antigens from cytotoxic T cells, out of the same available pool of minor antigens.

Suppression of the cytotoxic T cell response to minor alloantigens in vivo. Linked recognition by suppressor T cells

This report describes the activity of transferable suppressor T cells (Ts) generated in vivo in response to minor alloantigens. These Ts cells are antigen specific in both primary and secondary in vivo cytotoxic T lymphocyte responses to minor alloantigens and are the result of a host response rather than of a graft-vs.-host reaction. The Ts cells are produced soon after immunization and their activity is transient. They act via "linked recognition", since they can suppress the cytotoxic T lymphocyte response to noncross-reactive minor antigens, but only if these are presented on the same antigenic cell. A model for dominant low responsiveness in (high X low responder)F1 animals is proposed, whereby Ts cells, activated via the low responder allele, work by linked recognition to suppress helper cells activated via the high responder allele.

Computer-assisted analysis of in vivo cytotoxic T cell responses

An approach has been devised for analysing data generated in the study of in vivo cytotoxic T cell responses. The method calculates the total number of lytic units generated in the peritoneal cavity, or in cultures of the lymph nodes draining the rear footpad, following antigenic stimulation. The assessment of group differences is facilitated, and the method lends itself to computerised and hence objective data analysis.