Antigen Priming Induces Functional Reprogramming in iNKT Cells via Metabolic and Epigenetic Regulation: An Insight into iNKT Cell-Based Antitumor Immunotherapy

Dysfunction of intratumoral invariant natural killer T (iNKT) cells hinders their antitumor efficacy, but the underlying mechanisms and the relationship with endogenous antigen priming remain to be explored. Here, we report that antigen priming leads to metabolic reprogramming and epigenetic remodeling, which causes functional reprogramming in iNKT cells, characterized by limited cytokine responses upon restimulation but constitutive high cytotoxicity. Mechanistically, impaired oxidative phosphorylation (OXPHOS) in antigen-primed iNKT cells inhibited T-cell receptor signaling, as well as elevation of glycolysis, upon restimulation via reducing mTORC1 activation, and thus led to impaired cytokine production. However, the metabolic reprogramming in antigen-primed iNKT cells was uncoupled with their enhanced cytotoxicity; instead, epigenetic remodeling explained their high expression of granzymes. Notably, intratumoral iNKT cells shared similar metabolic reprogramming and functional reprogramming with antigen-primed iNKT cells due to endogenous antigen priming in tumors, and thus recovery of OXPHOS in intratumoral iNKT cells by ZLN005 successfully enhanced their antitumor responses. Our study deciphers the influences of antigen priming-induced metabolic reprogramming and epigenetic remodeling on functionality of intratumoral iNKT cells, and proposes a way to enhance efficacy of iNKT cell-based antitumor immunotherapy by targeting cellular metabolism.

HIVEP3 inhibits fate decision of CD8+ invariant NKT cells after positive selection

CD8+ invariant natural killer T (iNKT) cells are functionally different from other iNKT cells and are enriched in human but not in mouse. To date, their developmental pathway and molecular basis for fate decision remain unclear. Here, we report enrichment of CD8+ iNKT cells in neonatal mice due to their more rapid maturation kinetics than CD8- iNKT cells. Along developmental trajectories, CD8+ and CD8- iNKT cells separate at stage 0, following stage 0 double-positive iNKT cells, and differ in HIVEP3 expression. HIVEP3 is lowly expressed in stage 0 CD8+ iNKT cells and negatively controls their development, whereas it is highly expressed in stage 0 CD8- iNKT cells and positively controls their development. Despite no effect on IFN-γ, HIVEP3 inhibits granzyme B but promotes interleukin-4 production in CD8+ iNKT cells. Together, we reveal that, as a negative regulator for CD8+ iNKT fate decision, low expression of HIVEP3 in stage 0 CD8+ iNKT cells favors their development and T helper 1-biased cytokine responses as well as high cytotoxicity.

Achieving High Performance Stretchable Conjugated Polymers via Donor Structure Engineering

A backbone engineering strategy is developed to tune the mechanical and electrical properties of conjugated polymer semiconductors. Four Donor-Acceptor (D-A) polymers, named PTDPPSe, PTDPPTT, PTDPPBT, and PTDPPTVT, are synthesized using selenophene (Se), thienothiophene (TT), bithiophene (BT), and thienylenevinylenethiophene (TVT) as the donors and siloxane side chain modified diketopyrrolopyrrole (DPP) as acceptor. The influences of the donor structure on the polymer energy level, film morphology, molecular stacking, carrier transport properties, and tensile properties are all examined. The films of PTDPPSe show the best stretchability with crack-onset-strain greater than 100%, but the worst electrical properties with a mobility of only 0.54 cm2  V-1  s-1 . The replacement of the Se donor with larger conjugated donors, that is, TT, BT, and TVT, significantly improves the mobility of conjugated polymers but also leads to reduced stretchability. Remarkably, PTDPPBT exhibits moderate stretchability with crack-onset-strain ≈50% and excellent electrical properties. At 50% strain, it has a mobility of 2.37 cm2 V-1  s-1 parallel to the stretched direction, which is higher than the mobility of most stretchable conjugated polymers in this stretching state.

Gene regulatory network inference based on a nonhomogeneous dynamic Bayesian network model with an improved Markov Monte Carlo sampling

A nonhomogeneous dynamic Bayesian network model, which combines the dynamic Bayesian network and the multi-change point process, solves the limitations of the dynamic Bayesian network in modeling non-stationary gene expression data to a certain extent. However, certain problems persist, such as the low network reconstruction accuracy and poor model convergence. Therefore, we propose an MD-birth move based on the Manhattan distance of the data points to increase the rationality of the multi-change point process. The underlying concept of the MD-birth move is that the direction of movement of the change point is assumed to have a larger Manhattan distance between the variance and the mean of its left and right data points. Considering the data instability characteristics, we propose a Markov chain Monte Carlo sampling method based on node-dependent particle filtering in addition to the multi-change point process. The candidate parent nodes to be sampled, which are close to the real state, are pushed to the high probability area through the particle filter, and the candidate parent node set to be sampled that is far from the real state is pushed to the low probability area and then sampled. In terms of reconstructing the gene regulatory network, the model proposed in this paper (FC-DBN) has better network reconstruction accuracy and model convergence speed than other corresponding models on the Saccharomyces cerevisiae data and RAF data.