Immunotherapy-activated T cells recruit and skew late-stage activated M1-like macrophages that are critical for therapeutic efficacy.

Total tumor clearance through immunotherapy is associated with a fully coordinated innate and adaptive immune response, but knowledge on the exact contribution of each immune cell subset is limited. We show that therapy-induced intratumoral CD8+ T cells recruited and skewed late-stage activated M1-like macrophages, which were critical for effective tumor control in two different murine models of cancer immunotherapy. The activated CD8+ T cells summon these macrophages into the tumor and their close vicinity via CCR5 signaling. Exposure of non-polarized macrophages to activated T cell supernatant and tumor lysate recapitulates the late-stage activated and tumoricidal phenotype in vitro. The transcriptomic signature of these macrophages is also detected in a similar macrophage population present in human tumors and coincides with clinical response to immune checkpoint inhibitors. The requirement of a functional co-operation between CD8+ T cells and effector macrophages for effective immunotherapy gives warning to combinations with broad macrophage-targeting strategies.

Engineered bacterial swarm patterns as spatial records of environmental inputs.

A diverse array of bacteria species naturally self-organize into durable macroscale patterns on solid surfaces via swarming motility-a highly coordinated and rapid movement of bacteria powered by flagella. Engineering swarming is an untapped opportunity to increase the scale and robustness of coordinated synthetic microbial systems. Here we engineer Proteus mirabilis, which natively forms centimeter-scale bullseye swarm patterns, to 'write' external inputs into visible spatial records. Specifically, we engineer tunable expression of swarming-related genes that modify pattern features, and we develop quantitative approaches to decoding. Next, we develop a dual-input system that modulates two swarming-related genes simultaneously, and we separately show that growing colonies can record dynamic environmental changes. We decode the resulting multicondition patterns with deep classification and segmentation models. Finally, we engineer a strain that records the presence of aqueous copper. This work creates an approach for building macroscale bacterial recorders, expanding the framework for engineering emergent microbial behaviors.