Understanding the freezing responses of T cells and other subsets of human peripheral blood mononuclear cells using DSMO-free cryoprotectants.

BACKGROUND: This study examined the freezing responses of peripheral blood mononuclear cells (PBMCs) and specific white blood cell subsets contained therein when cryopreserved in three combinations of osmolytes composed of sugars, sugar alcohols and amino acids. METHODS: A differential evolution algorithm with multiple objectives was used to optimize cryoprotectant composition and thus the post-thaw recoveries for both helper and cytotoxicity T cells simultaneously. RESULTS: The screening of various formulations using a differential evolution algorithm showed post-thaw recoveries greater than 80% for the two subsets of T cells. The phenotypes and viabilities of PBMC subsets were characterized using flow cytometry. Significant differences between the post-thaw recovery for helper T cells and cytotoxic T cells were observed. Statistical models were used to analyze the importance of individual osmolytes and interactions between post-thaw recoveries of three subsets of T cell including helper T cells, cytotoxic T cells and natural killer T cells. The statistical model indicated that the preferred concentration levels of osmolytes and interaction modes were distinct between the three subsets studied. PBMCs were cultured for 72 h post-thaw to determine the stability of the cells. Because post-thaw apoptosis is a significant concern for lymphocytes, apoptosis of helper T cell and cytotoxic T cells frozen in a DMSO-free cryoprotectant was analyzed immediately post-thaw and 24 h post-thaw. Both cell types showed a decrease in cell viability 24 h post-thaw compared with immediately post-thaw. Helper T cell viability dropped 17%, and cytotoxic T cells had a 10% drop in viability. Immediately post-thaw, both cell types had >30% of cells in early apoptosis, but after 24 h the number of cells in early apoptosis decreased to below 20%. CONCLUSION: This study helped us identify the freezing responses of different human PBMC subsets using combinations of osmolytes.

Differential Evolution for the Optimization of DMSO-Free Cryoprotectants: Influence of Control Parameters.

This study presents the influence of control parameters including population (NP) size, mutation factor (F), crossover (Cr), and four types of differential evolution (DE) algorithms including random, best, local-to-best, and local-to-best with self-adaptive (SA) modification for the purpose of optimizing the compositions of dimethylsufloxide (DMSO)-free cryoprotectants. Post-thaw recovery of Jurkat cells cryopreserved with two DMSO-free cryoprotectants at a cooling rate of 1 °C/min displayed a nonlinear, four-dimensional structure with multiple saddle nodes, which was a suitable training model to tune the control parameters and select the most appropriate type of differential evolution algorithm. Self-adaptive modification presented better performance in terms of optimization accuracy and sensitivity of mutation factor and crossover among the four different types of algorithms tested. Specifically, the classical type of differential evolution algorithm exhibited a wide acceptance to mutation factor and crossover. The optimization performance is more sensitive to mutation than crossover and the optimization accuracy is proportional to the population size. Increasing population size also reduces the sensitivity of the algorithm to the value of the mutation factor and crossover. The analysis of optimization accuracy and convergence speed suggests larger population size with F > 0.7 and Cr > 0.3 are well suited for use with cryopreservation optimization purposes. The tuned differential evolution algorithm is validated through finding global maximums of other two DMSO-free cryoprotectant formulation datasets. The results of these studies can be used to help more efficiently determine the optimal composition of multicomponent DMSO-free cryoprotectants in the future.

Characterizing modes of action and interaction for multicomponent osmolyte solutions on Jurkat cells.

This study examined the post-thaw recovery of Jurkat cells cryopreserved in three combinations of five osmolytes including trehalose, sucrose, glycerol, mannitol, and creatine. Cellular response was characterized using low-temperature Raman spectroscopy, and variation of post-thaw recovery was analyzed using statistical modeling. Combinations of osmolytes displayed distinct trends of post-thaw recovery, and a nonlinear relationship between compositions and post-thaw recovery was observed, suggesting interactions not only between different solutes but also between solutes and cells. The post-thaw recovery for optimized cryoprotectants in different combinations of osmolytes at a cooling rate of 1°C/min was comparable to that measured with 10% dimethyl sulfoxide. Statistical modeling was used to understand the importance of individual osmolytes as well as interactions between osmolytes on post-thaw recovery. Both higher concentrations of glycerol and certain interactions between sugars and glycerol were found to typically increase the post-thaw recovery. Raman images showed the influence of osmolytes and combinations of osmolytes on ice crystal shape, which reflected the interactions between osmolytes and water. Differences in the composition also influenced the presence or absence of intracellular ice formation, which could also be detected by Raman. These studies help us understand the modes of action for cryoprotective agents in these osmolyte solutions.

Characterizing the "sweet spot" for the preservation of a T-cell line using osmolytes.

This study examined the post-thaw recovery of Jurkat cells cryopreserved in single osmolyte solutions containing sucrose, glycerol or isoleucine, as well as in a combination of the three osmolytes. Cell response was determined using low temperature Raman Spectroscopy and variation in post-thaw recovery with composition was analyzed using statistical modeling. Post-thaw recovery of Jurkat cells in single osmolyte was low. A combination of the osmolytes displayed a non-linear relationship between composition and post-thaw recovery, suggesting that interactions exist between the different solutes. The post-thaw recovery for an optimized multicomponent solution was comparable to that observed using 10% dimethyl sulfoxide and a cooling rate of 1 °C/min. Statistical modeling was used to characterize the importance of each osmolyte in the combination and test for interactions between osmolytes. Higher concentrations of glycerol increase post-thaw recovery and interactions between sucrose and glycerol, as well as sucrose and isoleucine improve post-thaw recovery. Raman images clearly demonstrated that damaging intracellular ice formation was observed more often in the presence of single osmolytes as well as non-optimized multi-component solution compositions.