Ionic immune suppression within the tumour microenvironment limits T cell effector function.

Tumours progress despite being infiltrated by tumour-specific effector T cells. Tumours contain areas of cellular necrosis, which are associated with poor survival in a variety of cancers. Here, we show that necrosis releases intracellular potassium ions into the extracellular fluid of mouse and human tumours, causing profound suppression of T cell effector function. Elevation of the extracellular potassium concentration ([K+]e) impairs T cell receptor (TCR)-driven Akt-mTOR phosphorylation and effector programmes. Potassium-mediated suppression of Akt-mTOR signalling and T cell function is dependent upon the activity of the serine/threonine phosphatase PP2A. Although the suppressive effect mediated by elevated [K+]e is independent of changes in plasma membrane potential (Vm), it requires an increase in intracellular potassium ([K+]i). Accordingly, augmenting potassium efflux in tumour-specific T cells by overexpressing the potassium channel Kv1.3 lowers [K+]i and improves effector functions in vitro and in vivo and enhances tumour clearance and survival in melanoma-bearing mice. These results uncover an ionic checkpoint that blocks T cell function in tumours and identify potential new strategies for cancer immunotherapy

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models