Aging impairs the integrated immunometabolic responses, which have evolved to maintain core body temperature in homeotherms to survive cold stress, infections, and dietary restriction. Adipose tissue inflammation regulates the thermogenic stress response, but how adipose tissue-resident cells instigate thermogenic failure in the aged are unknown. Here, we define alterations in the adipose-resident immune system and identify that type 2 innate lymphoid cells (ILC2s) are lost in aging. Restoration of ILC2 numbers in aged mice to levels seen in adults through IL-33 supplementation failed to rescue old mice from metabolic impairment and increased cold-induced lethality. Transcriptomic analyses revealed intrinsic defects in aged ILC2, and adoptive transfer of adult ILC2s are sufficient to protect old mice against cold. Thus, the functional defects in adipose ILC2s during aging drive thermogenic failure.

The cytokine IL-10 antagonizes pathways that control Mycobacterium tuberculosis (Mtb) infection. Nevertheless, the impact of IL-10 during Mtb infection has been difficult to decipher because loss-of-function studies in animal models have yielded only mild phenotypes. We have discovered that the transcription factor basic helix-loop-helix family member e40 (Bhlhe40) is required to repress Il10 expression during Mtb infection. Loss of Bhlhe40 in mice results in higher Il10 expression, higher bacterial burden, and early susceptibility similar to that observed in mice lacking IFN-γ. Deletion of Il10 in Bhlhe40-/- mice reverses these phenotypes. Bhlhe40 deletion in T cells or CD11c+ cells is sufficient to cause susceptibility to Mtb Bhlhe40 represents the first transcription factor found to be essential during Mtb infection to specifically regulate Il10 expression, revealing the importance of strict control of IL-10 production by innate and adaptive immune cells during infection. Our findings uncover a previously elusive but significant role for IL-10 in Mtb pathogenesis.

Progress toward understanding Zika virus (ZIKV) pathogenesis is hindered by lack of immunocompetent small animal models, in part because ZIKV fails to effectively antagonize Stat2-dependent interferon (IFN) responses in mice. To address this limitation, we first passaged an African ZIKV strain (ZIKV-Dak-41525) through Rag1-/- mice to obtain a mouse-adapted virus (ZIKV-Dak-MA) that was more virulent than ZIKV-Dak-41525 in mice treated with an anti-Ifnar1 antibody. A G18R substitution in NS4B was the genetic basis for the increased replication, and resulted in decreased IFN-β production, diminished IFN-stimulated gene expression, and the greater brain infection observed with ZIKV-Dak-MA. To generate a fully immunocompetent mouse model of ZIKV infection, human STAT2 was introduced into the mouse Stat2 locus (hSTAT2 KI). Subcutaneous inoculation of pregnant hSTAT2 KI mice with ZIKV-Dak-MA resulted in spread to the placenta and fetal brain. An immunocompetent mouse model of ZIKV infection may prove valuable for evaluating countermeasures to limit disease.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.