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Systemic immunization with soluble flagellin (sFliC) from Typhimurium induces mucosal responses, offering potential as an adjuvant platform for vaccines. Moreover, this engagement of mucosal immunity is necessary for optimal systemic immunity, demonstrating an interaction between these two semi-autonomous immune systems. Although TLR5 and CD103 CD11b cDC2 contribute to this process, the relationship between these is unclear in the early activation of CD4 T cells and the development of antigen-specific B cell responses. In this work, we use TLR5-deficient mice and mice (which have reduced numbers of cDC2, particularly intestinal CD103 CD11b cDCs), to address these points by studying the responses concurrently in the spleen and the mesenteric lymph nodes (MLN). We show that CD103 CD11b cDC2 respond rapidly and accumulate in the MLN after immunization with sFliC in a TLR5-dependent manner. Furthermore, we identify that whilst CD103 CD11b cDC2 are essential for the induction of primary T and B cell responses in the mucosa, they do not play such a central role for the induction of these responses in the spleen. Additionally, we show the involvement of CD103 CD11b cDC2 in the induction of Th2-associated responses. mice showed a reduced primary FliC-specific Th2-associated IgG1 responses, but enhanced Th1-associated IgG2c responses. These data expand our current understanding of the mucosal immune responses promoted by sFliC and highlights the potential of this adjuvant for vaccine usage by taking advantage of the functionality of mucosal CD103 CD11b cDC2.

There is growing evidence for the key role of microglial functional state in brain pathophysiology. Consequently, there is a need for efficient automated methods to measure the morphological changes distinctive of microglia functional states in research settings. Currently, many commonly used automated methods can be subject to sample representation bias, time consuming imaging, specific hardware requirements and difficulty in maintaining an accurate comparison across research environments. To overcome these issues, we use commercially available deep learning tools Aiforia® Cloud (Aifoira Inc., Cambridge, United States) to quantify microglial morphology and cell counts from histopathological slides of Iba1 stained tissue sections. We provide evidence for the effective application of this method across a range of independently collected datasets in mouse models of viral infection and Parkinson’s disease. Additionally, we provide a comprehensive workflow with training details and annotation strategies by feature layer that can be used as a guide to generate new models. In addition, all models described in this work are available within the Aiforia® platform for study-specific adaptation and validation.

The identification of intestinal macrophages (mφs) and dendritic cells (DCs) is a matter of intense debate. Although CD103+ mononuclear phagocytes (MPs) appear to be genuine DCs, the nature and origins of CD103− MPs remain controversial. We show here that intestinal CD103−CD11b+ MPs can be separated clearly into DCs and mφs based on phenotype, gene profile, and kinetics. CD64−CD103−CD11b+ MPs are classical DCs, being derived from Flt3 ligand-dependent, DC-committed precursors, not Ly6Chi monocytes. Surprisingly, a significant proportion of these CD103−CD11b+ DCs express CCR2 and there is a selective decrease in CD103−CD11b+ DCs in mice lacking this chemokine receptor. CCR2+CD103− DCs are present in both the murine and human intestine, drive interleukin (IL)-17a production by T cells in vitro, and show constitutive expression of IL-12/IL-23p40. These data highlight the heterogeneity of intestinal DCs and reveal a bona fide population of CCR2+ DCs that is involved in priming mucosal T helper type 17 (Th17) responses.

Initiation of adaptive immunity to particulate antigens in lymph nodes largely depends on their presentation by migratory dendritic cells (DCs). DC subsets differ in their capacity to induce specific types of immunity, allowing subset-specific DC-targeting to influence vaccination and therapy outcomes. Faithful drug design however requires exact understanding of subset-specific versus global activation mechanisms. cDC1, the subset of DCs that excel in supporting immunity towards viruses, intracellular bacteria and tumors, express uniquely high levels of the pattern recognition receptor TLR3. Using various genetic models, we show here that both the cDC1 and cDC2 subsets of cDCs are activated and migrate equally well in response to TLR3 stimulation in a cell extrinsic and TNFα dependent manner, but that cDC1 show a unique requirement for type I interferon signaling. Our findings reveal common and differing pathways regulating DC subset migration, offering important insights for the design of DC-based vaccination and therapy approaches.

Transcription Factor EB (TFEB) is a critical regulator of lysosomal biogenesis, autophagy and energy homeostasis through controlling expression of genes belonging to the coordinated lysosomal expression and regulation network. AMP-activated protein kinase (AMPK) has been reported to phosphorylate TFEB at three conserved C-terminal serine residues (S466, S467, S469) and these phosphorylation events were essential for transcriptional activation of TFEB. In sharp contrast to this proposition, here we demonstrate that AMPK activation leads to dephosphorylation of the C-terminal sites, and that AMPK is dispensable for mTORC1-mediated/torin1-sensitive TFEB activation. We show that a synthetic peptide encompassing C-terminal serine residues of TFEB is a poor substrate of AMPK. Treatment of cells with AMPK activator (MK-8722) or mTOR inhibitor (torin1) robustly dephosphorylated TFEB not only at mTORC1-targeted N-terminal serine sites, but also at the C-terminal sites. Loss of function of AMPK abrogated MK-8722-but not torin1-induced dephosphorylation and induction of the vast majority of TFEB target genes.

There is growing evidence for the key role of microglial activation in brain pathophysiology. Consequently, there is a need for efficient automated methods to measure the morphological changes distinctive of microglia functional states in research settings. Currently, many commonly used automated methods can be subject to sample representation bias, time consuming imaging, specific hardware requirements, and difficulty in maintaining an accurate comparison across research environments. To overcome these issues, we use commercially available deep learning tools (Aiforia® Cloud (Aifoira Inc., Cambridge, United States ) to quantify microglial morphology and cell counts from histopathological slides of Iba1 stained tissue sections. We provide evidence for the effective application of this method across a range of independently collected datasets in mouse models of viral infection and Parkinson's disease. Additionally, we provide a comprehensive workflow with training details and annotation strategies by feature layer that can be used as a guide to generate new models. In addition, all models described in this work are shared within the Aiforia® platform and are available for study-specific adaptation and validation. Competing Interest Statement B.P. receives commercial support as a consultant from Axial Therapeutics, Calico Life Sciences, CureSen, Enterin Inc, Idorsia Pharmaceuticals, Lundbeck A/S, AbbVie, Fujifilm-Cellular Dynamics International. He has received commercial support for research from Lundbeck A/S and Roche. He has ownership interests in Acousort AB, Enterin Inc and RYNE Biotechnology. S.L. is an employee of Aiforia Technologies. J.R. is an advisor for Agios Pharmaceuticals and Servier Pharmaceuticals. J.R. is a member of the scientific advisory board and has ownership interests in Immunomet Therapeutics. All other authors declare no additional competing financial interests.

Environmental nutrient availability influences T cell metabolism, impacting T cell function and shaping immune outcomes. However, the metabolic pathways critical for optimal T cell responses remain poorly understood. Here, we identify ketone bodies (KBs) – including β-hydroxybutyrate (βOHB) and acetoacetate (AcAc) – as essential fuels supporting CD8+ T cell metabolism and effector function. Ketolysis is an intrinsic feature of highly functional CD8+ T effector (Teff) cells and βOHB directly increases CD8+ Teff cell IFN-γ production and cytolytic activity. Using metabolic tracers, we establish that CD8+ Teff cells preferentially use KBs over glucose to fuel the tricarboxylic acid (TCA) cycle in vitro and in vivo. KBs directly boost the respiratory capacity of CD8+ T cells and TCA cycle-dependent metabolic pathways that fuel T cell growth. Mechanistically, we find that βOHB is a major substrate for acetyl-CoA production in CD8+ T cells and regulates effector responses through effects on histone acetylation. Together, our results identify cell-intrinsic ketolysis as a metabolic and epigenetic driver of optimal CD8+ T cell effector responses. Ketone bodies promote CD8+ T cell metabolism and effector function through regulation of epigenetic programming