antigen presentation conference 2022

Antibody Biology and Engineering

Connecting b cell biology with antibody structure, function and applications, conference description.

Antibodies are multi-faceted proteins that are capable of an array of important functions. They play a critical role in immune protection against invading pathogens and also play a role in a variety of clinically relevant inflammatory and autoimmune diseases. Many vaccines also induce neutralizing antibodies as a correlate of protection. Due to their high degree of specificity and generally favorable safety profiles, monoclonal antibodies have also emerged as one of the most promising and fastest growing classes of biotherapeutics. There are currently over 70 FDA-approved monoclonal antibodies and several hundred more in clinical development. The 2022 Gordon Research Conference on Antibody Biology and Engineering will present in-depth coverage of recent advances in this exciting field, in an informal setting designed for maximal interaction. The conference will bring together researchers in both academia and industry, providing an ideal environment for the presentation and discussion of cutting-edge findings. The conference will connect basic scientific aspects of B cell and antibody biology with applications to clinical antibody development, with key topics including antibodies targeting infectious disease agents, immunoglobulin effector function, antibody engineering, antibody structure, and pre-clinical antibody development. The conference will be preceded by a Gordon Research Seminar (GRS), as a specific means to foster involvement by scientists at the graduate student and post doctoral level. Planned by and for trainees, it will provide an exciting opportunity for junior researchers to present talks and posters in a supportive, interactive environment.

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This GRC will be held in conjunction with the "Antibody Biology and Engineering" Gordon Research Seminar (GRS). Those interested in attending both meetings must submit an application for the GRS in addition to an application for the GRC. Refer to the associated GRS program page for more information.

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Funding for this conference was made possible [in part] by 1R13AI150021-01 from the National Institute of Allergy and Infectious Diseases. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention of trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

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Insights in Antigen Presenting Cell Biology: 2022

Loading... Editorial 10 May 2023 Editorial: Insights in antigen presenting cell biology: 2022 Peter van Endert 724 views 0 citations

Original Research 04 April 2023 A machine learning approach to discover migration modes and transition dynamics of heterogeneous dendritic cells Taegeun Song ,  2 more  and  Yoon-Kyoung Cho 3,002 views 6 citations

Review 08 March 2023 Metabolic regulation of dendritic cell activation and immune function during inflammation Lili Wu ,  7 more  and  Yi Liu 4,533 views 0 citations

Original Research 12 January 2023 GM-CSF, Flt3-L and IL-4 affect viability and function of conventional dendritic cell types 1 and 2 Seyed Mohammad Lellahi ,  5 more  and  Karl-Henning Kalland 4,788 views 3 citations

Loading... Original Research 20 December 2022 HLA variants have different preferences to present proteins with specific molecular functions which are complemented in frequent haplotypes Vadim Karnaukhov ,  11 more  and  Mikhail Shugay 5,273 views 8 citations

Perspective 27 October 2022 Intracellular monitoring by dendritic cells – a new way to stay informed – from a simple scavenger to an active gatherer Christopher Herbst ,  1 more  and  Botond Z. Igyártó 2,254 views 4 citations

Loading... Review 22 July 2022 Targeting the antigen processing and presentation pathway to overcome resistance to immune checkpoint therapy Silvia D’Amico ,  5 more  and  Doriana Fruci 4,483 views 11 citations

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Antigen Presentation in the Lung

The lungs are constantly exposed to environmental and infectious agents such as dust, viruses, fungi, and bacteria that invade the lungs upon breathing. The lungs are equipped with an immune defense mechanism that involves a wide variety of immunological cells to eliminate these agents. Various types of dendritic cells (DCs) and macrophages (MACs) function as professional antigen-presenting cells (APCs) that engulf pathogens through endocytosis or phagocytosis and degrade proteins derived from them into peptide fragments. During this process, DCs and MACs present the peptides on their major histocompatibility complex class I (MHC-I) or MHC-II protein complex to naïve CD8 + or CD4 + T cells, respectively. In addition to these cells, recent evidence supports that antigen-specific effector and memory T cells are activated by other lung cells such as endothelial cells, epithelial cells, and monocytes through antigen presentation. In this review, we summarize the molecular mechanisms of antigen presentation by APCs in the lungs and their contribution to immune response.

Introduction

The lung is the peripheral tissue that exchanges gas during respiration; therefore, it is exposed to the outer environment, which potentially increases the risk of invasion by viral and bacterial pathogens. Respiratory viruses, including influenza virus and recent coronavirus, induce inflammation and tissue damage, leading to disorders of the lungs. The high infectivity and spreadability of these viruses have caused a worldwide pandemic in recent years and has provoked the argument for recurrent infection and efficacy of vaccination in order to suppress the pandemic. Innate immune cells such as dendritic cells (DCs) and macrophages (MACs) in the lungs form the first line of defense by recognizing the molecular structures common to pathogens, called pathogen-associated molecular patterns, through pattern recognition receptors ( 1 , 2 ). During the past decade, various types of lung DCs and MACs have been identified and classified according to surface markers, expression genes, and corresponding transcription factors with specialized functions. These DCs and MACs function as antigen-presenting cells (APCs) that engulf pathogens through endocytosis or phagocytosis and present their peptides on major histocompatibility complex class I (MHC-I) or MHC-II protein complex to naïve CD8 + or CD4 + T cells, respectively. Although DCs and MACs are known as professional APCs with a higher expression of co-stimulatory molecules, such as CD80 and CD86, other types of cells such as monocytes and epithelial cells in the lungs also have the potential to present antigens to T cells.

APCs load peptides derived from exogenous antigens on MHC-II and present peptide-MHC-II complex to CD4 + T cells whereas APCs load peptides derived from both endogenous and cytosolic antigens on MHC-I and present peptide-MHC-I complex to CD8 + T cells ( Figures 1 , 2 ). In addition, specific APCs take up exogenous antigens, process them, and load peptides onto MHC-I to CD8 + T cells, a process called antigen cross-presentation ( 3 ). Lung DCs are largely divided into three major subsets: cDC1s, cDC2s, and plasmacytoid DCs (pDCs). These DCs have been focused on as key regulators of T cell responses ( 4 ); however, recent evidence indicates that other types of cells in the lung, such as MACs, monocytes, and epithelial cells, also have antigen presentation capacity to both CD4 + and CD8 + T cells. MACs in the lung are mainly classified into alveolar macrophages (AMs) and interstitial macrophages (IMs). Lung epithelial cells (LECs) consist of alveolar type I (ATI) and alveolar type II (ATII) cells in the alveoli, and the predominant cell types constituting the bronchial airway epithelium include endothelial cells, basal progenitor cells, ciliated cells, secretory club cells, and goblet cells ( 5 , 6 ). Lung DCs, MAC and LECs express MHC-I and/or MHC-II on their cell surface and potentially present antigen to CD4 + or CD8 + T cells ( 7 ).

Antigen presentation on MHC-II molecule. Extracellular antigens are endocytosed or phagocytosed, and intracellular antigens are translocated to the late-endosome or the lysosome via autophagosome- or LAMP-2A- mediated autophagy. Then these antigens are degraded by asparaginyl endopeptidase and cathepsin. MHC-II is synthesized in ER and mainly pooled at the plasma membrane as MHC-II-Ii chain complex. When the complex translocates from the ER or the plasma membrane to the acidic compartment, Ii chain is degraded into CLIP and driven out by interaction with H2-M. Afterward, antigen peptides bind to the MHC-II and the peptide-MHC-II complex exports to the cell surface.

Antigen cross-presentation on MHC-I molecule. Extracellular antigens are presented via “vacuolar pathway” or “cytosolic pathway” in the cross-presentation pathway. In the vacuolar pathway, endocytosed antigen peptides are degraded by cathepsin S and bind to MHC-I in the endosomal compartment. In the cytosolic pathway, endocytosed or phagocytosed extracellular antigens are translocated to the cytosol via Sec61 and degraded by proteasome. The degraded peptides are transported into the ER or the endosome via TAP and trimmed by ERAP (in the ER) or IRAP (in the endosomes). TAP form PLC with MHC-I, ERp57 and calreticulin. Afterward, the trimmed peptides bind to the MHC-I and transported to the cell surface. The MHC-I in the endosomes is recruited from the plasma membrane through Rab11a + recycle endosome, the ER, or the ERGIC. Antigen degradation regulated by the acidification in the endosome, the phagosome, and the lysosome by V-ATPase. On the other hand, NADPH oxidase NOX2 regulates phagosomal alkalization and is recruited to the phagosomes by Rab27a-dependent pathway.

During pathogen infection in the lung, pathogen-specific CD4 + and CD8 + cells are primed in the lung-draining lymph nodes by antigen-presenting DCs that migrate from the infected area in the lung ( 8 , 9 ). Antigen-presenting DCs encounter naïve CD4 + and CD8 + T cells in the lymph nodes, where antigen-specific T cells are selected, and the proliferation and differentiation by antigen presentation on MHC molecules are induced along with the assistance of co-stimulatory molecules and the local cytokine environment ( 10 , 11 ). Antigen-specific CD4 + and CD8 + T cells in the lymph nodes migrate to the lungs to directly eliminate infected cells or induce the accumulation of other immunological cells for pathogen clearance. In addition, antigen-specific T cells encounter local APCs in the lungs, including DCs, MACs, monocytes, and LECs, and further differentiate and expand in the lung ( 12 ). Parts of antigen-specific cells differentiate into long-lived memory cells, which are divided into three types of population: central memory T (T CM ) cells, which are largely found in secondary lymphoid organs; effector memory T (T EF ) cells, which systematically circulate, transiently entering peripheral tissue, and resident memory T (T RM ) cells, a non-circulating, self-renewing population located in peripheral tissues including the lungs ( 13 , 14 ). There has been increasing evidence that antigen-specific memory T cell formation through antigen presentation or cytokines is facilitated by various types of lung cells. In this review, we summarize the molecular mechanisms of antigen presentation to MHC-I and MHC-II on APCs and memory T cell formation by APCs during pathogen infection in the lung.

Molecular Basis of Antigen Presentation to CD4 + T Cells

In general, extracellular antigens are endocytosed or phagocytosed by APCs and degraded by proteases such as asparaginyl endopeptidase ( 15 ) and cathepsins S, B, H, and L ( 16 – 18 ). Degraded peptides are ultimately presented on MHC-II molecules to prime CD4 + T cells ( 19 ) ( Figure 1 ). However, less than 30% of antigens on MHC-II are derived from endogenous antigens, such as cytoplasmic or nuclear antigens ( 20 , 21 ). Regardless of peptides derived from self or non-self-antigens, these peptides can be presented by APCs, non-professional APCs, or tumor cells mainly via autophagosome- or chaperone-mediated autophagy ( 22 ). Antigen degradation is mediated by the fusion of autophagosomes with endosomes and lysosomes in autophagosome-mediated autophagy ( 23 ). Antigens degraded by the proteasome in the cytosol are translocated to the late endosome or lysosome, which is enhanced by lysosome-associated membrane protein 2A (LAMP-2A) ( 24 ).

Newly synthesized MHC-II forms a complex with the invariant (Ii) chain in the endoplasmic reticulum (ER), and is pooled in the ER or plasma membrane and then respectively, translocated to the endosomes and lysosomes either directly ( 25 ) or indirectly though endocytosis ( 26 , 27 ); however, the complex cannot bind to antigen peptides ( 28 , 29 ). The Ii chain is degraded into a small fragment called class II-associated Ii chain peptide (CLIP) and binds to MHC-II in the late-endosome or the lysosome ( 30 ). The CLIP on MHC-II is driven out by interaction with another nonconventional MHC-II, called HLA-DM in humans and H2-M in mice ( 30 ). Then, MHC-II complexes can bind to antigen peptides and be presented on the cell surface ( 30 ). The expression of the peptide-MHC-II complex on the cell surface and its turnover by ubiquitination in DCs is essential for their ability to efficiently prime CD4 + T cells ( 31 , 32 ).

Molecular Basis of Antigen Cross-Presentation Pathway

Specific APCs are thought to take up extracellular antigens through endocytosis or phagocytosis and load peptides onto MHC-I for presentation to CD8 + T cells, a process called antigen cross-presentation ( 3 ). The extracellular antigen degradation pathway is mainly divided into the “vacuolar pathway”, through which the peptide is degraded in the endosome, and the “cytosolic pathway” which is responsible for the transport of degraded protein through SEC61 from the endosome to the cytosol ( 33 ) ( Figure 2 ).

Vacuolar Pathway of Antigen Cross-Presentation

In the vacuolar pathway, extracellular antigens are endocytosed by APCs and degraded into peptide fragments by proteases in the compartment. Cathepsin S plays a crucial role in antigen degradation in the endosomes of bone marrow-derived DCs (BMDCs) ( 34 ). It has been shown that cathepsin S plays a key role in priming CD8 + T cells to Influenza A virus (IAV) peptides loaded on MHC-I in the vacuolar pathway ( 34 ). In DCs, cathepsin S is also a crucial protease for MHC-II-dependent presentation to CD4 + T cells ( 18 , 35 ) whereas cathepsin L in the thymic cortical epithelium ( 35 ) and cathepsin F in macrophages likely correspond to proteases in the vacuolar pathway ( 36 ). The degraded peptide by cathepsins forms a complex with MHC-I in the endosome, and the peptide-MHC-I complex is transported to the cell surface. However, it is not clear whether cathepsins are required for antigen degradation in all lung APCs during pathogen infection.

Cytosolic Pathway of Antigen Cross-Presentation

In the cytosolic pathway, phagocytosed or endocytosed antigens are translocated from the endosomal compartments to the cytosol via Sec61 ( 33 ) and degraded to peptide fragments by the proteasome in the cytosol ( 37 , 38 ). Phagosomes and endosomes are mainly acidified via V-ATPase for degradation ( 39 ), which is regulated by Toll-like receptor (TLR) signals and other maturation signals ( 40 ), and restriction of antigen in these compartments by acidification is important for peptide degradation in the cytosolic pathway. DCs lacking the NADPH oxidase NOX2 show enhanced phagosomal acidification and increased antigen degradation, resulting in impaired antigen presentation ( 41 , 42 ). The recruitment of NOX2 to these compartments is prevented by deficiency of Rab27a, which causes acidification of phagosomes, limiting antigen degradation ( 43 ).

The cytosolic pathway is further categorized to two pathways; “ER-dependent pathway” and “Endosomal pathway”. The ER-dependent pathway is the most common route to ER for antigen peptide. Antigen peptides in the cytosol are transported into the ER mainly through transporter associated with antigen processing (TAP) and form peptide-MHC-I complexes in the ER. On the other hand, peptides degraded by the proteasome in the cytosol are transported back to the endosomes through TAP in the endosomal pathway. MHC-I molecules are recycled in the cells. MHC-I molecules in the endosome are transported from the plasma membrane through the Rab11 + recycling endosomes ( 44 ) and are also recruited from the ER or the ER-Golgi intermediate compartment (ERGIC) ( 3 , 45 ). Transported peptides are loaded on MHC-I by the peptide loading complex (PLC) the in the ER or the endosomes ( 46 ). PLC consists of TAP, oxidoreductase ERp57, MHC-I heterodimer, and calreticulin ( 46 ). PLC is recruited to phagosomes or endosomes via the Sec22b-ERGIC pathway ( 47 ). PLC is also recruited from the recycle endosomes after TLR activation ( 44 ). In contrast, the N terminal anchor residues of the peptides are trimmed by ER-resident N-aminopeptidases (ERAP1 and ERAP2 in humans, and ERAAP in mice). Insulin regulated aminopeptidase (IRAP), an aminopeptidase similar to ERAP, trims the peptide in the endosomes ( 48 , 49 ). These peptide trimming proteins are crucial for efficient antigen peptide binding to MHC-I and contribute to cross-presentation ( 50 – 52 ). Although cytosolic peptides shuttle into the ER through TAP1 in the cytosolic pathway, TAP1 blockade in DCs leads to antigen presentation by MHC-I translocation from ERGIC in a Sec22b-dependent manner rather than the Rab11 + recycle-endosome pathway ( 53 ).

DCs and MACs in the Lung

DCs in the lung consist of heterogeneous subsets that exert different functions ( 54 , 55 ). Lung DCs are largely divided into three major subsets and are broadly subdivided into plasmacytoid DCs (pDCs) and conventional DCs (cDCs). Murine cDCs express high levels of integrin CD11c and are further divided into CD103 + DC and CD11b + DCs. CD103 + DCs and CD11b + DCs are also referred to as cDC1s and cDC2s, respectively ( 55 – 58 ). Although CD11b and CD11c have been utilized for the separation of DC population, cDCs separation was proposed as two main subsets cDC1s and cDC2s based on the transcription factor expression ( 59 , 60 ). Interferon regulatory factor 8 (IRF8) and Batf3 drive the development of cDC1s which are separated as XCR1 + Cadm1 + CD172a − cDC1s ( 61 – 69 ). On the other hand, IRF4 drives the development of cDC2 which are separated as XCR1 − Cadm1 − CD172a + cDC1s ( 67 , 69 – 76 ). pDCs develop in the presence of transcription factor 4 (E2-2) and the Ets family transcription factor Spi-B ( 77 – 79 ). In the steady-state, cDC1s associate with airway rather than alveoli in the lung ( 80 , 81 ). cDC2s are located in the airway and lung parenchyma ( 82 – 84 ). Monocyte-derived DCs (moDCs) have been described as another DC population that accumulates in the lungs during inflammation and viral infection ( 85 – 87 ). MoDCs are also known as inflammatory DCs and monocyte derived cells ( 88 – 91 ). These DCs are subdivided based on the presence of surface markers and recent progress in the technology for single-cell RNA sequencing revealed that the cDC2s population in the lung is subdivided based on expression markers with functional differences, whereas pDCs and cDC1s are a unique population ( 92 – 94 ).

MACs in the lungs consist of two major populations: alveolar MACs (AMs) and interstitial MACs (IMs). AMs are located in the alveolar space of the lungs and are in close contact with the type I and II epithelial cells of the alveoli. AMs are the first line of defense against pathogens for host defense in the lung, with a higher engulfment capacity against antigens and pathogens ( 95 ). AMs produce cytokines such as TGFβ, IL6, and type I interferon during pathogen infection and inflammation ( 95 , 96 ). In addition, AMs play a central role in homeostasis and tissue remodeling. Pulmonary surfactant is a mixture of lipids and proteins secreted into the alveolar space by AT II cells. The surfactant is covered with an interface of alveolar epithelial cells in the lungs to reduce the physical tension during breathing. In addition, the engulfment of surfactant and cell debris by AMs is important for the clearance and maintenance of lung homeostasis. Accumulation of pulmonary surfactant in the absence of AMs causes the development of pulmonary alveolar proteinosis (PAP) ( 97 – 99 ). GM-CSF and TGF-β induce PPAR-γ, a crucial transcription factor for AM development ( 100 ). Interstitial macrophages (IMs) reside in the parenchyma between the microvascular endothelium and alveolar epithelium. However, compared with AMs, the role of IMs in lung homeostasis remains poorly understood. Like AMs, IMs engulf bacteria and foreign particles and secrete IL-1, IL-6, IL-10, and TNFα ( 101 – 104 ). IMs form a heterogeneous population that is further subdivided based on surface markers with distinct functions ( 103 , 105 ).

The lung is composed of a complex tissue structure that exchanges gas and is exposed to outer space. The combination of crosstalk between DCs and MACs effectively protects against inhaled pathogens by inducing acquired immunity ( Figure 3 ). cDC1s, cCD2s and IMs express high levels of MHC I/II with co-stimulatory molecules CD80 and CD86 ( 106 ). However, AMs express lower levels of MHC-II. Based on the expression of molecules for antigen presentation, it is revealed that each cells display antigen presentation capacity against specific infectious pathogens and allergic materials in the lungs.

Antigen presenting cells in the lung. The lungs are constantly exposed to environmental and infectious agents such as dust, viruses, fungi, and bacteria that invade the lungs upon breathing. The lungs are protected by various types of immune cells and epithelial cells. Lung DCs are largely divided into three major subsets and are broadly subdivided into pDCs, cDC1s and cDC2s. MACs in the lungs consist of two major populations: AMs and IMs. LECs consist of ATI and ATII cells in the alveoli, and the endothelial cells and other types of cells constituting the bronchial airway epithelium. Monocytes migrate to the lungs in response to inflammatory stimuli in a CCR2-dependent manner and these cells differentiate to moDCs or AMs. Small blood vessels allow oxygen to be extracted from the air into the blood, and carbon dioxide to be released from the blood into the air. The cells lining the inner surface of blood vessels are the pulmonary endothelial cells. These cells function as APCs that engulf pathogens through endocytosis or phagocytosis and present their peptides on major MHC-I or MHC-II protein complex to CD8 + or CD4 + T cells.

Antigen Presentation by pDCs

pDCs are professional cells that secrete type I IFN through the stimulation of innate immune receptors. It is widely accepted that the production of type I IFN by pDCs in the lungs is important for host defense against pathogens. An Aspergillus fumigatus infection model in the lung demonstrated that pDCs are essential for host defense and neutrophil effector activity ( 107 ). Antigen presentation by pDCs in the lungs is controversial during pathogen infection. Resting pDCs are weak antigen-presenting cells, but appear to be functionally specialized for their ability to capture and present viral antigens to CD4 + T cells in the presence of CpG DNA or virus stimulation ( 108 , 109 ). Transplantation of pDCs in an IAV infection model showed that pDCs infected with IAV promote antigen presentation to CD8 + T cells ( 110 ). In contrast, ablation of pDCs does not have a significant impact on the production of IAV-specific CD8 + T cells and viral clearance, indicating that pDCs have weak or no antigen cross-presentation capacity in vivo ( 111 ). Other groups have shown that pDCs in other peripheral tissues cooperate with cDC2s to promote their maturation and cross-presentation activity and induce antiviral CD8 + T cells, suggesting that pDCs indirectly induce antigen-specific CD8 + T cells ( 112 , 113 ).

Antigen Presentation by cDC2s

cDC2s are localized in the lungs under a steady-state condition, and a large number of cDC2s are accumulated in the lungs in response to inflammation induced by viral infection ( 114 ) or antigen immunization ( 115 ). IAV infection induces accumulation of cDC2s, and the depletion of these cells reduces the number of virus-specific CD8 + cells and mortality ( 85 – 87 ). These results indicate that accumulated cDC2s migrate to the lymph nodes and present antigens to CD8 + T cells. However, cDC1 analysis using Batf3 -deficient mice indicated that cDC2s have a weak cross-presentation capacity in vivo and support the proliferation of CD8 + T cells in the lung during IAV infection ( 116 ). Initial antigen-specific T cell differentiation is induced in the tissue-draining lymph nodes, and lung cDC2s are less migratory than cDC1s ( 117 ). During the inflammation, cDC2s in the lungs have shown to prime CD4 + Th2 cells but not CD8 + T cells responses ( 69 , 75 , 76 ). cDC2s also have shown to prime CD4 + Th17 cells response during Aspergillus fumigatus infection ( 74 ). T follicular helper (Tfh) cells are a subset of CD4 + T cells that promote antibody production during vaccination. cDC2s carry antigen into the lymph node where cDC2-dependent Tfh cells prime antibody-mediated protection from IAV challenge ( 67 ). cDC2s also locate in lymphoid organ, skin intestine and others organs as same with lung cDC2s, and cDC2s in the other organs efficiently promote the differentiation of CD4 + T cells into effector helper T cells during infection with Nippostrongylus brasiliensis , Aspergillus fumigatus or Citrobacterior rodentium ( 70 – 73 ). These results suggest that cDC2s are more specialized in polarizing CD4 + T helper cell responses and providing help to B cells, rather than in inducing CD8 + T cells activation.

cDC2s consist of heterogeneous subpopulations although it is unclear whether the same subpopulation of cDC2s induces both Th2 and Th17 cells ( 71 , 74 , 94 ). Single-cell RNA and cytometry by time-of-flight (CyTOF) analyses revealed that cDC2s consist of five distinct clusters. Ly-6C + CD301b – cDC2s promote Th17 differentiation, and CD200 + cDC2s induce the differentiation of Th2 but not Th17 cells ( 94 ). In addition, there are conflicting reports on how moDCs and CD11b + DCs interact with and regulate T cell responses ( 118 ). A recent report indicated that inflammatory cDC2s (inf-cDC2s) express the Fc receptor CD64 shared with moDCs and IRF8 shared with cDC1s and are infiltrated to present antigen to CD4 + and CD8 + T cells during respiratory virus infection ( 92 ). TNFR2 − cDC2 subpopulation drives moDCs maturation to generate T follicular helper (Tfh) cells in the lung ( 119 ).

Antigen Cross-Presentation by cDC1s

Many studies have shown the importance of cDC1s in the initiation of antiviral T cell response following influenza infection. Particular subsets of cDC1s, such as CD8α + and CD103 + cDC1s, play specific roles in naïve T cell activation and differentiation ( 10 , 120 – 122 ). CD8α + cDC1s in the spleen and lymphoid organs are known as the cross-presenting subset ( 123 – 125 ). CD103 + cDC1s are migratory DCs that cross-present antigens in peripheral tissues, including the lungs ( 126 , 127 ). Both CD103 + cDC1s in the lungs and CD8α + cDC1s in lymph nodes share the expression of various genes, including transcription factors IRF8, BATF3, and ID2, and both of these DC subtypes are developed in the presence of Flt3 ( 128 ).

cDC1s directly present antigen to naive CD4 + T cells ( 129 ) and cDC1s could prime Th2 and Th17 differentiation by producing IL4, IL12, IL13 and IL17 induction during allergic airway inflammation ( 130 , 131 ). A mouse model of invasive pulmonary aspergillosis infection showed cDC1s induces Th17 response by producing IL-2 in the lung ( 132 ). Other reports postulate that cDC1s promote airway tolerance by the induction of FoxP3 + T reg s in antigen induced airway inflammation ( 133 ) or by inducing IL-10 without T reg -induction ( 134 ). Although cDC1s can present antigens and stimulate CD4 + T cells, they are well known for their ability to cross-present antigens to CD8 + T cells ( 127 , 132 ). Lung cDC1s preserve viral antigens in their endocytic compartments and control the induction of virus-specific CD8 + T cells through antigen cross-presentation ( 116 , 135 ). Lung cDC1s migrate to mediastinal LNs after viral infection, where they directly present antigens to naïve CD8 + T cells or transfer captured antigens to CD8α + cDC1s, which present antigens and activate naïve CD8 + T cells ( 86 , 136 , 137 ). In addition to cDC1s, cDC2s have the potential to migrate to mediastinal LNs (MLNs) ( 117 ), however, cDC2s do not present antigens efficiently in the MLNs ( 138 ). The cytotoxic activity of CD8 + T cells plays a critical role in viral clearance in the lungs. Initial virus-specific CD8 + T cells in the LNs are induced by cDC1s migrating from the infected lung, and the virus-specific CD8 + T cells then traffic back to the infected lung to mediate their effector function ( 10 , 11 , 139 ).

Antigen Presentation by moDCs

Chemokine receptor CCR2- and Ly6C-expressing inflammatory monocytes infiltrate into the lung during pathogen infection including Aspergillus fumigatus ( 140 ) and IAV ( 141 ), and differentiate rapidly into moDCs. MoDCs in other organs are also capable of presenting antigen and priming to CD4 + T cells ( 142 , 143 ) and CD8 + T cells ( 88 ). However, the precise function of moDCs to regulate T cells response in lung is controversial. CCR2-deficient mice impair moDCs recruitment and exhibit reduction of effecter CD8 + T cell response in the lung after IAV infection ( 85 ). moDCs depletion by CD11c-cre- Irf4 f/f mice reduces CD8 + memory precursor cells and T RM cells during IAV infection ( 144 ). MoDCs in the lung prime IFN-γ-producing antigen-specific CD4 + T cells in pulmonary aspergillosis ( 140 ). MoDCs also promote Th1 and Th17 cell polarization through antigen presentation during allogeneic responses ( 118 ) and induce Th2 type CD4 + cells during house dust mite allergy ( 145 ). Report using CD26 as a maker for separation of moDCs indicated that moDCs have poor capacity to migrate to lymph node and prime CD4 + T cells and CD8 + T cells ( 92 , 117 , 146 ).

Antigen Presentation by Macrophages

AMs develop during embryogenesis, and then predominantly maintain their populations by self-renewal ( 147 – 149 ) and are specialized in the removal and recycling of surfactant molecules. Although AMs are the most abundant immune cells in the lungs and have been suggested to play a functional role in antigen presentation during tuberculosis and Cryptococcus neoformans infection in humans ( 150 , 151 ), supportive evidence for antigen presentation by AMs has not been reported in mice. Certain IM subsets have been contributed to lung immune homeostasis by spontaneously producing the immunosuppressive cytokine IL-10 and preventing the development of aberrant type 2 allergic responses against inhaled allergens ( 101 , 104 ). IMs are separated by a distinct subpopulation based on the surface expression pattern ( 103 , 152 ) and single-cell RNA sequencing ( 153 , 154 ), some of which express antigen-presenting genes and may mediate antigen presentation to CD4 + T cells in the lungs. Accumulated Ly-6C + monocytes develop to exudative macrophages (exMACs) during Cryptococcus ( 155 ), Streptococcus ( 156 ) and IAV infection ( 157 ). ExMACs produce high levels of TNF-α and NOS2 and stimulate the proliferation of memory CD4 + T cells ( 157 ).

Antigen Presentation by Monocytes

Two types of monocytes have been identified with different phenotypes and functions: Ly6C + classical monocytes and Ly6C − non-classical monocytes. Ly6C + monocytes constitutively enter to lung tissues in the steady state and a large number of these cells migrate to the lungs in response to inflammatory stimuli in a CCR2-dependent manner ( 158 , 159 ). Ly6C + monocytes develop to moDCs, IMs, exMACs or monocyte-derived AMs in the lungs during inflammatory stimulation, but in the steady state, monocytes continuously migrate to non-lymphoid organs including lung without differentiating into other types of cells and may exit lung via the lymphatics or undergo local apoptosis and cleared ( 160 ). Ly6C + monocytes have been shown to produce large amounts of IL-1, IL-6, and TNFα, and have an ability to drive adaptive immune responses through antigen presentation ( 160 ). Ly6C + monocytes in other tissues reported that these cells have an ability to present antigen to both CD4 + and CD8 + cells. Ly6C + monocytes regulate early host response to Aspergillus lung infection by taking up conidia and trafficking them into the draining LN to prime CD4 + T cells ( 140 ). Cross-presentation by Ly6C + inflammatory monocytes in lymphoid organs has been reported in the presence of TLR agonists, especially TLR7 ( 161 ). Once recruited into the lungs, Ly6C + monocytes further differentiate into moDCs and monocyte-derived AMs. Recent evidence have shown that CCR2-deficient mice, which are defective in monocyte trafficking to the lung, exhibit decreased number of virus-specific lung resident memory CD8 + (T RM ) cells by the antigen presentation on monocytes ( 162 ).

Antigen Presentation by Epithelial and Endothelial Cells

As lung epithelial cells directly interact with the external environment, these cells are thought to be critical regulators of barrier immunity ( 163 , 164 ). The alveoli are composed of two distinct lung epithelial cell types: AT I cells, which are thin and cover approximately 95% of the internal surface of the lung, and AT II cells, which are cuboidal secreting cells located between type I cells ( 165 ). AT I cells are specialized in gas exchange and alveolar fluid regulation, whereas type II cells secrete surfactants and constitute the progenitor cells of the epithelium ( 166 ). There is increasing evidence that epithelial cells in the lung contribute to adaptive immune responses in the lungs. AT II cells express MHCII and present antigen. In vitro co-culture experiments AT II cells with antigen specific hybridoma suggested that AT II cells activate CD4 + cells to induce IFNγ in the presence of peptide antigen, and deletion of MHC-II on AT II cells results in a modest worsening of respiratory virus disease following influenza and Sendai virus infections ( 167 ). Surfactant Protein C (SPC) low MHC-II high AT II cells function as APCs to induce CD4 + T RM cells ( 7 ). Antigen presenting AT II cells primes naïve CD4 + T cells in vitro and induce regulatory T (T reg ) cells ( 168 ); however, it is unclear whether AT II cells prime naïve CD4 + T cells in vivo ( 169 ). In addition to CD4 + T cells activation, barrier epithelial cells recruit and maintain CD8 + T RM cells near the sites of antigen encounter and reactivate them in the tissues via local antigen presentation ( 12 , 170 ).

Small blood vessels, known as capillaries, come in close contact with the alveoli, allowing oxygen to be extracted from the air into the blood, and carbon dioxide to be released from the blood into the air. The cells lining the inner surface of these capillaries are known as the pulmonary endothelial cells ( 171 ). Lung endothelial cells cross-present malaria antigen to antigen specific reporter cells in vitro and a mouse model of malaria infection by Plasmodium berghi ANKA (PbA) induces IFNγ positive CD8 + T cell. These results demonstrate that lung endothelial cells cross-present malaria antigen to CD8 + T cells, although it is unclear whether these cells activate naive CD8 + T cell in vivo ( 172 ).

Perspective and Conclusion

Lungs are protected by various types of APCs that stimulate antigen-specific CD4 + and CD8 + T cells against infectious pathogens. cDC1s and cDC2s work as professional APCs in the lung. Sub-population of cDCs has been investigated by deep separation using single RNA sequence and CyTOF technology and have shown to process and present antigen. In addition, there has been increasing evidence for antigen presentation by resident APCs such as epithelial cells, epithelial cells in the lungs. The relation of pathogen and inflammation model to APCs was shown in Table 1 . Although MACs express MHC and costimulatory molecules with higher engulfment capacity, the role of MACs in the lung as APCs is still unclear.

Lung APCs and their roles in T cell responses.

To initially prime antigen-specific T cells, antigen-captured DCs and migratory APCs need to traffic to lung-draining LNs where they encounter naïve T cells to select antigen-specific T cells. Following a program of proliferation and differentiation of T cells in LNs, antigen-specific effector or memory T cells migrate back to the infected lung to mediate their effector function ( 10 , 11 ). At the same time, antigen-specific effector or memory T cells are reactivated by APCs, including monocytes, epithelial cells and endothelial cells in the lungs, with support of cytokine production and the local microenvironment ( 12 ). Among the antigen specific memory type cells, CD4 + and CD8 + T RM cells in the lung provide protection against pathogen infection and retain for long time period in the peripheral tissue. Pulmonary antigen encounter is necessary for the establishment of T RM during IAV infection in the lung ( 173 ), and antigen presentation by DCs with cytokines such as TGF-β and IL15 is shown to be important for T RM development in the lung ( 174 – 176 ). Various types of APCs in the lungs contribute to pathogen clearance against viruses, fungi, and bacteria; therefore, APCs perform their function depending on the pathogen infection, and further studies are needed to clarify the role of individual APCs in the lungs.

Author Contributions

TakK and MI wrote the manuscript. TarK edited and supervised the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We thank Chihiro Suzuki for secretarial assistance. This work was supported by JSPS KAKENHI Grant-in-Aid for Scientific Research B (20H03468) and C (19K07608), Grant-in-Aid for Early-Career Scientists (21K14817) and the Takeda Science Foundation. We would like to thank Editage ( www.editage.com ) for English language editing.

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Microparticle Delivery of a STING Agonist Enables Indirect Activation of NK Cells by Antigen-Presenting Cells

Add to collection, downloadable content.

• Affiliation: School of Medicine, Department of Genetics
• Affiliation: Eshelman School of Pharmacy, Division of Pharmacoengineering and Molecular Pharmaceutics
• Affiliation: N.C. Cancer Hospital, UNC Lineberger Comprehensive Cancer Center
• Natural killer (NK) cells are an important member of the innate immune system and can participate in direct tumor cell killing in response to immunotherapies. One class of immunotherapy is stimulator of interferon gene (STING) agonists, which result in a robust type I interferon (IFN-I) response. Most mechanistic studies involving STING have focused on macrophages and T cells. Nevertheless, NK cells are also activated by IFN-I, but the effect of STING activation on NK cells remains to be adequately investigated. We show that both direct treatment with soluble STING agonist cyclic di-guanosine monophosphate-adenosine monophosphate (cGAMP) and indirect treatment with cGAMP encapsulated in microparticles (MPs) result in NK cell activation in vitro, although the former requires 100× more cGAMP than the latter. Additionally, direct activation with cGAMP leads to NK cell death. Indirect activation with cGAMP MPs does not result in NK cell death but rather cell activation and cell killing in vitro. In vivo, treatment with soluble cGAMP and cGAMP MPs both cause short-term activation, whereas only cGAMP MP treatment produces long-term changes in NK cell activation markers. Thus, this work indicates that treatment with an encapsulated STING agonist activates NK cells more efficiently than that with soluble cGAMP. In both the in vitro and in vivo systems, the MP delivery system results in more robust effects at a greatly reduced dosage. These results have potential applications in aiding the improvement of cancer immunotherapies.
• acetalated dextran
• immunotherapy
• microparticle
• https://doi.org/10.17615/bp3w-tc40
• https://doi.org/10.1021/acs.molpharmaceut.2c00207
• In Copyright
• Molecular Pharmaceutics
• National Institute of Allergy and Infectious Diseases, NIAID, (T32AI007273, U19AI067798, U19AI109784)
• National Institutes of Health, NIH
• Big Lottery Fund, BIG
• National Cancer Institute, NCI, (P30CA016086, U54CA198999)
• University of North Carolina, UNC
• North Carolina Biotechnology Center Biotechnology Innovation
• National Science Foundation, NSF, (ECCS-1542015)
• University of North Carolina Cancer Research Fund
• American Chemical Society

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2022 Oral Presentations

Tuesday, march 29, 2022, educational session.

Impacts of the COVID-19 Pandemic on Advancing HIV, STI and Viral Hepatitis Testing Megan Crumpler, PhD Presentation

Overview of HIV Testing Practices and Technology S. Michele Owen, PhD Presentation

STI Testing Technology Barbara Van der Pol, Phd Presentation

Hepatitis C Virus Test Technology Saleem Kamili, PhD Presentation

Debrief of the HCV Diagnostics Conference Carolyn Wester, MD Presentation

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A Shared Service Model for HIV Nucleic Acid Testing and the Impact of COVID-19 Lauren Johnson, MPH Presentation

Multisite Evaluation of an HIV-1 panel on the Alinity m HIV-1 assay and its relevance to critical clinical decision points Whitnie Crown, MS, M(ASCP)MB Presentation

HIV/HCV Screening, Testing, and Diagnostic Reliability during the Acute Encounter with the Cepheid GeneXpert Jason Wilson, MD, MA, FACEP Presentation

Evaluation of the Aptima HCV Quant Dx Assay for qualitative and quantitative RNA detection in Dried Blood Spots Renee Hallack, BS Presentation

Validation of new STI panel for Abbott Alinity m Karen C. Rexroth, M(ASCP) Presentation

The Clinical and Cost Implications of Using HIV RNA Instead of Antibody Testing to Confirm Reactive HIV Screening Tests in the United States Daniel Gromer, MD Presentation

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Discussion panel 2: the utility of multiplex versus singleplex or lower plex testing in sti diagnostics.

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Session 2: Recently Marketed Tests

2A. Evaluation of the DPP HIV-Syphilis test performance characteristics at the point-of-care clinical setting (FDOH-Miami-Dade STD clinical lab). Olga V. Ponomareva, MD Presentation

2B. Performance of the Avioq VioOne HIV Profile Supplemental Assay for Confirmation and Differentiation of HIV-1 and HIV-2 Antibodies at a State Public Health Laboratory. S. Berry Bennett, MPH Presentation

2C. Visby Medical Sexual Health Click test: A patient-centric approach to diagnosing sexually transmitted infections Teresa M. Abraham, PhD Presentation

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3C. Infectious Disease Testing at a Syringe Services Program (SSP) Heather Henderson, MA/CAS Presentation

3D. Promoting HIV and Hepatitis C Virus Testing and Linkage to Harm Reduction Resources Through Navigation Programs Shamia Roberts, BSN, RN Presentation

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Discussion Panel 3 – The Reddit Community asks the experts about STIs. Here’s what we discovered…

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4C. Longitudinal Specificity of the BioPlex 2200 HIV Ag-Ab Combination Assay in Routine Screening in a US Public Health Laboratory Alfredo Villarreal, BS, MBA Presentation

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5B. A laboratory-developed quantitative hepatitis B surface antigen (qHBsAg) test detects 8 major HBV genotypes and sG145R mutants Mary Lape Nixon, BA, MS Presentation

5C. Time to leave Fiebig staging in the dust? Estimated Dates of Detectable Infection (EDDIs) as a new and improved method for HIV infection dating Shelley Facente, PhD, MPH Presentation

5D. Use of the Geenius Index to indicate recent HIV infection in Project DETECT Lauren Violette, MPH Presentation

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Discussion Panel 5 – Detecting and confirming acute or incident HIV infection in persons taking antiretrovirals for PrEP

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Friday, April 1, 2022

Feedback session: regulatory issues related to self-collection and remote testing (led by fda and cdc).

Panelists Julia Lathrop, PhD Presentation S. Michele Owen, PhD Ellen Kersh, PhD Timothy Stenzel, MD, PhD

Session 6: Mail-in Testing

6A. Addition of Extragenital STI testing in “I Want The Kit” Program Users Tong Yu, ScM Presentation

6B. I Want The Kit (IWTK): Improving an online platform for STI specimen at- home self-collection and laboratory testing Gretchen Armington, MA Presentation

6C. Preparing for a Home-Based Self-Sampling STI/HIV Testing Pilot Program Ashton Morris, MPH Johnnie Green, MBA Presentation

6D. GetCheckedDC: A Mail-in STI Testing Pilot Program Kenya Troutman, MPH Presentation

6E. TakeMeHome: Implementing a novel home HIV/STI testing program Jennifer Hecht, MPH Presentation

Moderator: Liisa Randall, PhD

Session 7: Self-collected Micro-sampling

7A. Actionable multi-targeted STI testing using self-collect DBS for high-risk populations Zoe Goedecke, BS

7B. Validation and prospective evaluation of mailed dried blood spot (DBS) for dual detection of HIV and syphilis using the DPP® HIV-Syphilis test Johan H. Melendez, PhD Presentation

7C. Clinical Utility of Hepatitis C Viral Load Detected via Dried Blood Spot Card At-Home Collection Mariko Nakano, PhD Presentation

7D. The implementation of self-collected MicrotainerTM specimens in a large research project—iSTAMP Amanda J. Smith, MPH Presentation

7E. Self-collected MicrotainerTM specimens for HIV viral load testing: a step towards HIV telemedicine Jeffrey A. Johnson, PhD Presentation

7F. Evaluation of self-collected MicrotainerTM specimens for measuring antiretroviral drugs Richard E. Haaland, PhD Presentation

Moderator: Joanne Mei, PhD

Antigen Presentation Machinery Signature-Derived CALR Mediates Migration, Polarization of Macrophages in Glioma and Predicts Immunotherapy Response

Affiliations.

• 1 Department of Neurosurgery, Affiliated Nanhua Hospital, University of South China, Hengyang, China.
• 2 Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
• 3 National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
• 4 Department of Oncology, Xiangya Hospital, Central South University, Changsha, China.
• 5 Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
• 6 Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
• 7 Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
• 8 Department of Neurology, Hunan Aerospace Hospital, Changsa, China.
• PMID: 35418980
• PMCID: PMC8995475
• DOI: 10.3389/fimmu.2022.833792

Immunogenicity, influenced by tumor antigenicity and antigen presenting efficiency, critically determines the effectiveness of immune checkpoint inhibitors. The role of immunogenicity has not been fully elucidated in gliomas. In this study, a large-scale bioinformatics analysis was performed to analyze the prognostic value and predictive value of antigen presentation machinery (APM) signature in gliomas. ssGSEA algorithm was used for development of APM signature and LASSO regression analysis was used for construction of APM signature-based risk score. APM signature and risk score showed favorable performance in stratifying survival and predicting tumorigenic factors of glioma patients. APM signature and risk score were also associated with different genomic features in both training cohort TCGA and validating cohort CGGA. Furthermore, APM signature-based risk score was independently validated in three external cohorts and managed to predict immunotherapy response. A prognostic nomogram was constructed based on risk score. Risk score-derived CALR was found to mediate the invasion and polarization of macrophages based on the coculture of HMC3 and U251 cells. CALR could significantly predict immunotherapy response. In conclusion, APM signature and APM signature-based risk score could help promote the clinical management of gliomas.

Keywords: antigen presentation machinery; genomic alteration; glioma; immunotherapy; microenvironment; prognosis.

Copyright © 2022 Chen, Zhang, Wu, Li, Wang, Dai, Liu, Zhang, Luo, Xia and Cheng.

Publication types

• Research Support, Non-U.S. Gov't
• Antigen Presentation*
• Glioma* / genetics
• Glioma* / therapy
• Immunotherapy
• Macrophages / pathology

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• Published: 05 December 2022

The circadian clock influences T cell responses to vaccination by regulating dendritic cell antigen processing

• Mariana P. Cervantes-Silva 1   na1 ,
• Richard G. Carroll   ORCID: orcid.org/0000-0001-9917-3443 1   na1 ,
• Mieszko M. Wilk   ORCID: orcid.org/0000-0002-7947-633X 2 , 3 ,
• Diana Moreira 2 ,
• Cloe A. Payet 1 ,
• James R. O’Siorain 1 ,
• Shannon L. Cox 1 ,
• Lauren E. Fagan 1 , 4 ,
• Paula A. Klavina   ORCID: orcid.org/0000-0001-8294-343X 1 , 5 ,
• Yan He 1 , 6 ,
• Tabea Drewinski 1 ,
• Alan McGinley 1 ,
• Sharleen M. Buel 7 ,
• George A. Timmons 1 ,
• James O. Early 1 , 4 ,
• Roger J. S. Preston 5 ,
• Jennifer M. Hurley 7 ,
• David K. Finlay   ORCID: orcid.org/0000-0003-2716-6679 2 ,
• Ingmar Schoen   ORCID: orcid.org/0000-0002-5699-1160 5 ,
• F. Javier Sánchez-García 8 ,
• Kingston H. G. Mills 2 &
• Annie M. Curtis   ORCID: orcid.org/0000-0002-9601-9624 1 , 2 , 4 , 5  

Nature Communications volume  13 , Article number:  7217 ( 2022 ) Cite this article

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• Circadian rhythms
• Dendritic cells

Dendritic cells play a key role in processing and presenting antigens to naïve T cells to prime adaptive immunity. Circadian rhythms are known to regulate many aspects of immunity; however, the role of circadian rhythms in dendritic cell function is still unclear. Here, we show greater T cell responses when mice are immunised in the middle of their rest versus their active phase. We find a circadian rhythm in antigen processing that correlates with rhythms in both mitochondrial morphology and metabolism, dependent on the molecular clock gene, Bmal1 . Using Mdivi-1, a compound that promotes mitochondrial fusion, we are able to rescue the circadian deficit in antigen processing and mechanistically link mitochondrial morphology and antigen processing. Furthermore, we find that circadian changes in mitochondrial Ca 2+ are central to the circadian regulation of antigen processing. Our results indicate that rhythmic changes in mitochondrial calcium, which are associated with changes in mitochondrial morphology, regulate antigen processing.

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Introduction.

Dendritic cells (DCs) phagocytose, process and present antigens to naive T cells and thereby play a critical role in priming adaptive immune responses to infection or following vaccination. Cells of the innate and adaptive immune system, including DCs, express all the components of the endogenous molecular clock and display circadian rhythmicity in gene expression 1 . These cellular timers produce daily oscillations in a range of critical immune cell functions, such as phagocytosis 2 , cytokine production 3 ,cell trafficking 4 , cell migration 5 along with anti-parasite 6 , antibacterial and antiviral immune responses 5 , 7 . In elderly individuals, vaccination against influenza in the morning generates higher antibody titres than vaccination in the afternoon 8 . Individuals immunised with the BCG vaccine in the morning showed stronger trained immune responses compared with those vaccinated in the evening 9 . However, the mechanisms modulating these time-of-day differences in immune responses to human vaccines remain poorly understood 8 .

Metabolic changes in DCs can influence their differentiation and activation 10 , 11 , 12 . Mitochondria are central to cellular metabolic changes and are a major site of energy production in the form of ATP. Mitochondria are highly dynamic organelles in terms of their spatial distribution, morphology and inner architecture and change their shape continually to meet the energetic demands of the cell. Cells can alter their mitochondrial morphology through altering the balance of fusion and fission processes within the cell. Mitochondrial fusion results in the joining of two mitochondria into one and is mediated by MFN proteins and the GTPase OPA1 13 . While mitochondrial fission involves the division of a single mitochondrion into two daughter mitochondria and is mediated in part by the cytosolic GTPase DRP1 13 . Recently, we reported that mitochondrial dynamics in mouse macrophages are tightly controlled by the molecular clock. Mitochondria displayed enhanced fusion during the rest phase and fission during the active phase. The fused state at the end of the resting phase correlated with higher ATP production and phagocytic function 14 . These oscillations in oxidative phosphorylation (OXPHOS) and ATP generation have been demonstrated across a range of cell types, and are associated with the NAMPT-NAD-SIRT1/3 axis and dependent on circadian modification of DRP1 phosphorylation 15 , 16 , 17 . However, it is still unknown whether mitochondrial morphology is under clock control in DCs and what impact this might have on DC function.

Mitochondria also act as a calcium sink and regulate the levels of cytosolic calcium and modulate biological pathways. It has been shown that the molecular clock drives oscillations in mitochondrial calcium and ATP production in astrocytes 18 . Calcium is crucial for chemokine-dependent migration of DCs. Engagement of chemokine receptors, such as CCR7, triggers trafficking of DCs by increasing Ca 2+ influx 19 , 20 , 21 . Interestingly, Holtkamp et al. demonstrated that skin DCs preferentially migrate into lymphatic vessels during the mouse rest phase due to clock control of CCR7 22 . Thus, control of cellular Ca 2+ is an important determinant of DC function, but the molecular mechanisms regulating Ca 2+ localisation within DCs and its consequences are not well understood.

Therefore, we sought to investigate the impact of circadian rhythms on DC function and whether this might explain the diurnal variability observed in the protective immune response induced by certain vaccines. There is a growing body of evidence to suggest that cellular metabolism and mitochondria are central to DC function 23 , 24 . However, it is still unclear whether circadian rhythms might intersect with these metabolic pathways to impart time-of-day influences on DC function. In this study, we found that the DC molecular clock controls calcium mobilisation, mitochondrial dynamics and metabolism to influence antigen processing and T cell activation. Understanding these functionally important daily oscillations of DCs may determine a time-of-day that is optimal for vaccination, and may also uncover useful approaches for boosting DC function, to enhance vaccine-induced immunes responses.

DCs play a critical role in the time-of-day T cell response to immunisation

Circadian rhythms regulate many aspects of innate immunity 25 , 26 . Response to vaccination is time-of-day dependent but the underlying mechanisms are unclear 8 , 9 , 27 , 28 . A recent study demonstrated rhythms in T cell proliferation following adoptive transfer of antigen loaded BMDCs in mice 29 . In this study, DCs were pre-loaded with OVA peptide in vitro. Peptides can bypass intracellular processing pathways and directly associate with MHCI/II. Therefore, that experimental design did not assess the effect of circadian rhythms on antigen uptake and processing by DCs and as such prompted us to investigate the impact of the clock on antigen uptake and processing in DCs. We utilised an adoptive transfer model (Fig.  1a ), where CD4 + T cells were isolated from OT-II mice on Day −1 at ZT3 and stained with cell trace violet (CTV). These CTV-stained OTII CD4 + T cells were immediately injected into recipient mice that had been phase shifted to either ZT7 or ZT19 in light cabinets to facilitate simultaneous experimentation. The next day ZT7 and ZT19 mice were immunised with OVA and whole cell pertussis (wcP) as an adjuvant, and 72 h later (again corresponding to either ZT7 or ZT19), mediastinal lymph nodes were harvested from these mice to analyse proliferation and activation of the CTV-stained T cells. We reasoned that the approach of injecting the same CTV-stained OTII CD4 + T cells into phase-shifted recipient mice allowed us to more accurately interrogate the effect of the DC molecular clock on T cell activation (Fig.  1a and Supplementary Fig.  1a ).

a Experimental design for adoptive transfer of labelled T cells and immunisations by circadian phase. CTV + OT-II CD4 + T cells (harvested at ZT3) were transferred directly into ZT7 or ZT19 recipient mice. 24 h later immunisations of ZT7 or ZT19 recipient mice occurred. Immunisations were performed using wcP vaccine + OVA 10 µg/mouse ( n  = 6 mice) or PBS control ( n  = 3 mice) and mediastinal lymph nodes harvested 72 h later. b , c Proliferation of CTV + stained OT-II CD4 + T cells harvested from mediastinal lymph node. d Percentage of divided and undivided CTV + stained OT-II CD4 + T cells ( n  = 6 immunised mice or n  = 3 control mice) p  = 0.04 for divided and undivided cells. e Representative plot of CD69 + expression on CTV + stained OT-II CD4 + T cells. f Percentage of CD69 + expression on CTV + stained OT-II CD4 + T cells ( n  = 6 immunised mice or n  = 3 control mice) p  = 0.02. Data shown is mean with error bars representing ± SEM. Data were compared using two-tailed t -test, * p  < 0.05. Source data are provided as a Source Data file.

Zeitgeber time (ZT) is defined as the time in hours following the onset of light in the animal facility. Mice were maintained in a 12 h:12 h light:dark environment. For example, ZT7 refers to 7 h after lights on and the middle of the rest phase, ZT19 refers to 7 h after lights off and the middle of the active phase.

Flow cytometry analysis of the CTV-stained OTII CD4 + T cells revealed a significant increase in T cell proliferation in the mediastinal lymph node when mice were immunised at ZT7 versus ZT19 (Fig.  1b–d ), with no T cell proliferation observed in PBS controls. There were more CTV + OTII T cells in the mediastinal lymph node in mice that were immunised at ZT 7 compared to ZT 19 (1.7% versus 0.8%) (Fig.  1c ). Using CD69 as a marker of activated T cells, we found more activated CTV + OTII T cells in the mediastinal lymph nodes of mice immunised at ZT7 versus ZT19 (Fig.  1e, f ). These results suggest that molecular processes within the DC required for T cell activation must be under control of the molecular clock. Thus, we decided to further investigate the molecular mechanisms underpinning this effect.

Synchronised DCs display robust rhythms in clock gene expression and antigen processing

Antigen uptake (phagocytosis), processing and presentation are essential for DC activation of T cells. Therefore, we investigated which of these, if any, might be under the control of the molecular clock and provide an explanation for the time-of-day vaccine effect observed in Fig.  1 . Firstly, we investigated whether DCs contained a functional clock with circadian rhythms. Cells can be synchronised in vitro to the same circadian phase through the addition of serum rich media (50% horse serum) for 2 h followed by serum withdrawal (serum-shock) 30 (Fig.  2a ). Following synchronisation, PER2::Luc bone marrow-derived dendritic cells (BMDCs) produced strong circadian rhythms as demonstrated by oscillations of luminescence resulting from the cycling of PER2 protein that persisted up to 4–5 days in culture (Fig.  2b ). Analysis of expression of the molecular clock genes, Period 2 , Nr1d1 and Bmal1 by qPCR revealed that they were also cycling (Supplementary Fig.  2a ).

a A schematic summarising how ZT time can be inferred from the in vitro synchonised serum shock model comparing Per2 mRNA oscillation in BMDCs. Shading represents the relative active periods. As mice are nocturnal, 12 h post synchronisation represents ZT0 the onset of the inactive phase, whereas 24 h post synchronisation represents ZT12 the onset of the active phase. b Per2::luciferase BMDCs were synchronised by serum shock and circadian rhythms were measured using lumicycle technology ( n  = 3 biologically independent samples). Bmal1 +/+ and Bmal1 − / − BMDCs were synchronised and antigen processing was measured at c 4 h or d 12 h intervals over a 48 h time course ( n  = 3 independent experiments). Antigen processing was measured by addition of DQ-OVA (1 µg/mL) and fluorescence (blue – DAPI, green – DQ-OVA) was measured at 15 min (uptake) or 60 min (processing) and then fixed and analysed by confocal microscopy. e Spleens were isolated from WT mice at ZT1, ZT7, ZT13 and ZT19 and single cell suspension generated, stained for DQ-OVA (1 μg/mL) as in ( c , d ) and subsequently stained for CD11b+ and CD11c+ and analysed by flow cytometry ( n  = 4 mice). f Spleens isolated from Bmal1 myeloid+/+ and Bmal1 myeloid − / − mice and stained for DQ-OVA as in ( c , d ) and CD11b + and analysed by flow cytometry ( n  = 3 mice) p  = 0.0045. g , h Splenic DCs were expanded by B16-FLT3L cells. g cDCs, cDC1s, cDC2s, plasmacytoid DCs and macrophages, or h migratory and resident DCs were identified by flow cytometry and DQ-OVA processing quantified by flow cytometry ( n  = 3–4 mice). cDC p  = 0.003, cDC1 p  = 0.005, cDC2 p  = 0.04, pDC p  = 0.02, macs p  = 0.001, migratory DCs p  = 0.01, resident DCs p  = 0.0092 Data shown is mean with error bars representing ± SEM. Luciferase data was analysed for circadian rhythmicity by JTK cycle ( b ). Antigen processing in Bmal1 +/+ was predicted to be circadian by cosinor analysis ( c ). Data were compared by one-way ANOVA with Tukey’s post-hoc test for multiple comparisons ( e ) or by a two-tailed t -test ( f–h ). * p  < 0.05, ** p  < 0.01, *** p  < 0.001 and **** p  < 0.0001. Source data are provided as a Source Data file.

We next investigated the regulation of antigen processing in DCs by the molecular clock using DQ-OVA. DQ-OVA is a self-quenched labelled conjugate of the full length ovalbumin protein, which produces a fluorescent green signal following cleavage into peptide fragments 31 . Bmal1 is a core clock gene forming part of the positive arm 32 . Deletion of Bmal1 ablates the oscillation of the proteins in the negative arm of the core clock and cannot be compensated by any other paralogues in the native context. Thus, we used Bmal1 -deleted BMDCs as a model of circadian disruption. Antigen processing was quantified using DQ-OVA in synchronised Bmal1 +/+ and Bmal1 −/− BMDCs at distinct timepoints across the circadian cycle up to 48 h. We found that antigen processing in Bmal1 +/+ BMDCs followed a circadian rhythm, with highest processing at 12 h and 36 h and the lowest at 24 h and 48 h post synchronisation (Fig.  2c, d ). In contrast, BMDCs lacking Bmal1 had low levels of antigen processing and lacked any discernible rhythm at all times tested (Fig.  2c, d ). These findings demonstrate a significant role for the molecular clock in regulation of antigen processing. Differences in antigen uptake, measured by FITC-OVA, did not differ by time-of-day or by genotype (Supplementary Fig.  2c ), suggesting specific clock controlled regulation on antigen processing.

We next tested whether the circadian variation of antigen processing was present in primary antigen presenting cells (APCs). To achieve this, splenic cells were isolated from mice at ZT1, ZT7, ZT13 and ZT19 and antigen processing was measured by DQ-OVA fluorescence.

Analysis of the CD11b and CD11c populations revealed that the percentage of cells processing DQ-OVA increased from 55% at ZT7 to 75% at ZT19 in CD11b + , and from 28% at ZT7 to 43% at ZT19 in CD11c + cells (Fig.  2e ). We also observed that antigen processing was reduced in CD11b + cells within the spleen of Bmal1 myeloid −/− mice when compared with Bmal1 myeloid+/+ mice even though they had similar number of CD11b + cells (Fig.  2f ). In the total DC population, we found approximately 2-fold increase in processing of DQ-OVA from ZT7 and ZT19 (Fig.  2g and Supplementary Fig.  3a ). We next investigated different subpopulations, including cDC1s, which are associated with cross presentation and activation of MHCI, cDC2s which are associated with conventional MHCII presentation and plasmacytoid DCs that are prominent in viral infection (Supplementary Fig.  1b ) 33 . The cDC1 subpopulation increased by over 2-fold (ZT19 – 47.7% vs ZT7 – 20.8%) and the cDC2 population also increasing at ZT19 (62%) compared to ZT7 (44%) (Fig.  2g and Supplementary Fig.  3a ). Plasmacytoid DCs and macrophages also showed a similar time-of-day dependency with higher antigen processing at ZT19 compared to ZT7 (Fig.  2g and Supplementary Fig.  3b ). Both resident and migratory cells also displayed higher antigen processing at ZT 19 as measured by DQ-OVA processing (Fig.  2h and Supplementary Fig.  3c ). The resident cDC are the major DC population in the spleen, and execute their antigen collection, processing and presentation within that lymphoid organ. The migratory cDCs constantly sample the tissue, and once activated, travel to the draining lymph node where they encounter naive T cells 34 . These ex vivo results demonstrate a clear time-of-day difference in the antigen processing function across all DC subtypes and macrophages.

DC mitochondrial metabolism is regulated by the molecular clock and is required for antigen processing

Metabolism is a key regulator of DC function, and the molecular clock controls cellular metabolism 12 , 24 , 35 . We next investigated if DC metabolism varied in a circadian manner and whether this influenced the observed rhythms in antigen processing. We compared mitochondrial metabolism between Bmal1 +/+ and Bmal1 −/− BMDCs at distinct time points post serum synchronisation using the Agilent Seahorse XF Cell Mito Stress Test. We found that mitochondrial metabolism in Bmal1 +/+ BMDC displayed a rhythmic phenotype, with highest maximal respiration, spare respiratory capacity (SRC) and ATP levels at 12 h and 36 h post synchronisation, and lowest at 24 h post synchronisation (Fig.  3a–d ). In contrast, mitochondrial metabolism did not show any rhythmicity in these readouts in Bmal1 −/− BMDC and were consistently lower when compared to Bmal1 +/+ BMDC (Fig.  3a–d ). These results demonstrate that mitochondrial metabolism is regulated by the endogenous molecular clock in DCs. To investigate whether mitochondrial metabolism was involved in antigen processing by DCs, the mitochondrial metabolism inhibitors Oligomycin (an inhibitor of ATP synthase) and FCCP (a mitochondrial oxidative phosphorylation uncoupler) were used in the DQ-OVA antigen-processing assay at 12 h post synchronisation. Oligomycin and FCCP significantly reduced antigen processing in both Bmal1 +/+ and Bmal1 −/− BMDCs (Fig.  3e, f ), indicating the importance of mitochondrial metabolism for antigen processing. As expected both inhibitors significantly reduced ATP levels. (Supplementary Fig.  4a ). To investigate if the reduced antigen processing conferred a biological effect on T cells, coculture experiments were performed with BMDCs and OVA specific OTII CD4 + T cells in the presence or absence of mitochondrial metabolism inhibitors. To rule out any effects of the inhibitors on T cells, BMDCs were pre-treated with mitochondrial inhibitors, followed by OVA and then BMDCs were washed thoroughly before T cells were added. Addition of OVA to the cocultures OTII CD4 + T cells and BMDCs resulted in robust production of IFN-γ and IL-17 from activated T cells that was significantly inhibited with the addition of oligomycin or FCCP (Fig.  3g ). The reduced antigen processing observed in Bmal1 − / − compared with Bmal1 +/+ BMDCs also resulted in significantly lower IFN-γ production by OTII CD4 + T cells (Fig.  3h ). Collectively, these results identify mitochondrial metabolism as a key regulator of antigen processing in DCs and reveal that DC molecular clock regulation of mitochondrial metabolism modulates antigen processing function and subsequent T cell activation.

a Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and OCR was measured at indicated times post serum synchronisation using an XF e 96 Analyzer and from this b maximal respiration and c spare respiratory capacity measurements were derived ( n  = 3 biologically independent samples). d Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and ATP levels were measured at indicated times using an ATP/ADP assay kit ( n  = 3 biologically independent cells). e and f Bmal1 +/+ and Bmal1 −/− BMDCs at 12 h post synchronisation were treated with oligomycin (10 µM) or FCCP (10 µM) and antigen processing was then measured by confocal microscopy using DQ-OVA (1 µg/mL) (n = 5 biologically independent samples). g BMDCs (unsynchronised) were treated with oligomycin (10 µM) and FCCP (10 µM) for 2 h. OVA protein (25 µg/mL) was then added to the BMDCs for 2 h. Supernatants were removed and indicated number of OTII CD4 + T-cells were added. Cells were incubated for 3 days before IFNγ and IL17 were analysed by ELISA ( n  = 3 biologically independent samples) ( h ) Bmal1 +/+ and Bmal1 −/− BMDCs (unsynchronised) were incubated with OVA protein (25 µg/mL) for 2 h. Supernatants were removed and indicated number of OTII CD4 + T-cells were added. Cells were incubated for 3 days before IFNγ was analysed by ELISA ( n  = 3 biologically independent samples). Data shown is mean with error bars representing ± SEM. Statistical significance was determined using one-way ANOVA with Tukey’s post-hoc test for multiple comparisons. Results are from duplicate BMDCs cultures, from two independent experiments. * p  < 0.05, ** p  < 0.01, *** p  < 0.001. Source data are provided as a Source Data file.

DC mitochondrial morphology and mitochondrial potential display circadian rhythmicity

As mitochondrial morphology is known to directly influence mitochondrial metabolism 36 , 37 , we investigated if the observed circadian oscillations in antigen processing were accompanied by alterations in the mitochondrial morphology network of DCs. We observed clear circadian rhythms in mitochondrial morphology within DCs that were dependent on Bmal1 . In Bmal1 +/+ BMDCs, the mitochondria displayed a fragmented phenotype at 24 h and 48 h post serum synchronisation (Fig.  4a ), which correlated with times when antigen processing was lowest (Fig.  2c ). In contrast, mitochondria had a fused phenotype at 12 and 36 h post serum synchronisation in Bmal1 +/+ BMDCs (Fig.  4a, c, d ), correlating with high levels of antigen processing (Fig.  2c ). In Bmal1 −/− BMDCs, mitochondria were predominantly fragmented at all timepoints tested (Fig.  4b–d ) correlating with low antigen processing (Fig.  2c ). These observed changes in mitochondrial fragmentation displayed significant circadian rhythmicity when analysed by cosinor analysis (Fig.  4e ), although, the mitochondrial fusion failed to reach significance for circadian rhythmicity (Fig.  4f ). Mitochondrial membrane potential is a key indicator of mitochondrial metabolism 37 , 38 , and this also displayed a circadian rhythm by cosinor analysis (Fig.  4g ). These circadian changes in mitochondrial potential were not due to changes in mitochondrial mass; analysis of mitochondrial mass using mitotracker green showed no time-of-day or Bmal1 dependent variation (Fig.  4h ). We also investigated mRNA and protein expression of key genes involved in mitochondrial morphology, such as Fis1, Opa1 , Mfn1 and Mfn2 . None of these genes displayed any circadian variation at mRNA level (Supplementary Fig.  5a ), however the mitochondrial fission gene Fis1 was rhythmic at protein level in synchronised Bmal1 +/+ with an increase at 24 h post serum synchronisation but no rhythms were observed in Bmal1 −/− BMDCs (Supplementary Fig.  5b, c ). Together, these results reveal a role for the DC molecular clock in the circadian regulation of mitochondrial metabolism, morphology and accompanying circadian rhythm of DC function.

a–g Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and mitochondria were stained with Mitotracker Red CMXRos (50 nM) at indicated timepoints. Mitochondrial morphology was assessed over a 48 h time course in a Bmal1 +/+ and b Bmal1 −/− using confocal microscopy. Differences in morphology are illustrated in c at 12 h and d at 36 h post synchronisation between Bmal1 +/+ and Bmal1 −/− BMDCs. Arrows highlight examples of mitochondrial fusion and fission. ( e ) Mitochondrial fission (fragmented mitochondria) ( f ) mitochondrial fusion (elongated mitochondria and ( g ) mitochondrial membrane potential were quantified by confocal microscopy ( n  = 3 biologically independent samples). h Bmal1 +/+ and Bmal1 −/− BMDCs were stained with Mitotracker green FM dye at indicated time points post synchronisation and analysed by flow cytometry ( n  = 3 biologically independent samples). Data shown is mean with error bars representing ± SEM. Mitochondrial fission and membrane potential in Bmal1 +/+ were predicted to be circadian by cosinor analysis ( e and g ). Data were compared by one-way ANOVA with Tukey’s post-hoc test for multiple comparisons ( h ). Source data are provided as a Source Data file.

Control of mitochondrial morphology with small molecule inhibitors of DRP1 can alter the circadian-dependent antigen presenting function of DCs

Up to this point, we observed circadian rhythms in mitochondrial metabolism and morphology that correlated with antigen processing in DCs. We next wished to investigate the mechanistic link between circadian controlled mitochondria morphology and DC antigen processing. Firstly, we employed the small molecule Mdivi-1, an inhibitor of the pro-fission protein DRP1 39 , to increase mitochondrial fusion at all timepoints following synchronisation. In Bmal1 +/+ BMDC, Mdivi-1 treatment promoted mitochondrial fusion at 24 h post synchronisation (Fig.  5a ), the time in the circadian cycle when mitochondria were in a fragmented phenotype (Fig.  2e ). However, there was no observable increase in fusion at 12 h post synchronisation in Bmal1 +/+ BMDC (Fig.  5a ) as the mitochondria at this time point already display increased fusion under normal rhythmic control (Fig.  4a, c ). Mitochondria displayed a fragmented phenotype in Bmal1 − / − BMDCs at all timepoints post synchronisation and application of Mdivi-1 promoted mitochondrial fusion (Fig.  5a ). Critically, Mdivi-1 not only promoted mitochondrial fusion but also promoted antigen processing. The low level of antigen processing in Bmal1 +/+ BMDCs at 24 h post synchronisation was significantly boosted with addition of Mdivi-1 (Fig.  5b, d ). Importantly, Mdivi-1 treatment could rescue the defective antigen processing that was consistently observed in Bmal1 − / − BMDCs at 12 and 24 h post synchronisation and Mdivi-1 treated Bmal1 − / − BMDCs had antigen processing levels comparable to Bmal1 +/+ BMDCs (Fig.  5b–d ). These results demonstrate that circadian oscillations in mitochondrial morphology are mechanistically linked to DC antigen processing.

a Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and treated with Mdivi-1 (10 µM) 12 h prior to the designated timepoint. At the designated time point, mitochondria were then stained with Mitotracker Red CMXRos (50 nM) and mitochondrial morphology was measured using confocal microscopy. b Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and treated with Mdivi-1 (10 µM) as in ( a ) and antigen processing was then measured by confocal microscopy at the indicated times post synchronisation using DQ-OVA (1 µg/mL) ( c and d ). Quantification of antigen processing in Bmal1 +/+ and Bmal1 − / − BMDCs using confocal microscopy at indicated times post-synchronisation ( n  = 30 independent images). Data shown is mean with error bars representing ± SEM. Data were analysed by one-way ANOVA with Tukey’s post-hoc test for multiple comparisons. *** p  < 0.001. Source data are provided as a Source Data file.

Circadian rhythms drive oscillations in mitochondrial calcium levels to coordinate antigen processing

The ability of mitochondria to act as a calcium sink has been reported to decrease cytosolic calcium concentrations, while also increasing mitochondrial ATP production 18 . Changes in cytosolic calcium concentrations will impact on calcium regulated enzymes, one of which is calcineurin, an enzyme that also drives mitochondrial fission through its effects on DRP1 phosphorylation 40 , 41 . We thus asked if calcium or calcium regulated enzymes influenced circadian controlled antigen processing in DCs. Firstly, we investigated if there was a time-of-day difference in the calcium localisation within the cell between the cytosol and mitochondria. Using Rhod-2, a mitochondrial calcium indicator, we observed that Bmal1 +/+ BMDCs showed nearly 3-fold more calcium localised to the mitochondria at 12 h, relative to 24 h, post synchronisation (Fig.  6a, b ). The opposite was true for cytosolic calcium levels assessed by Fluo-4 staining where we observed nearly 3-fold less cytosolic calcium at 12 h relative to 24 h post serum synchronisation (Fig.  6a–c ). Bmal1 − / − BMDCs showed no time-of-day difference in the location of their calcium with low levels of mitochondrial calcium and high cytosolic calcium at both time points tested (Fig.  6a–c ). This demonstrates that changes in calcium localisation are circadian and it suggests that the molecular clock may be using mitochondria as a calcium sink to control this temporal localisation. Mdivi-1, a compound that increases mitochondrial fusion, also increased mitochondrial calcium levels in both Bmal1 +/+ and Bmal1 − / − (Fig.  6d ). We used a second molecule to increase mitochondrial fusion, a selective peptide P110 which promotes fusion by inhibiting DRP1 GTPase activity and the DRP1/FIS1 interaction 42 . We found that while P110 promotes mitochondrial fusion in Bmal1 +/+ , it did not promote antigen processing to the same extent as Mdivi-1 (Supplementary Fig.  6a ). Concurrently, we found that P110 did not increase mitochondrial calcium uptake (Supplementary Fig.  6b ). Therefore, we reasoned that Mdivi-1 has such pronounced effects on antigen processing as it promotes both fusion and mitochondrial calcium uptake.

a Confocal microscopy analysis of calcium localisation in synchronised Bmal1 +/+ and Bmal1 −/− BMDCs by staining with Fluo-4 (cytosolic) or Rhod-2 (mitochondrial). b Mitochondrial calcium quantification and c cytosolic calcium quantification from confocal analysis ( n  = 10 independent images). d Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and pre-treated with Mdivi-1 (10 μM). Mitochondrial calcium uptake was quantified using Rhod-2 by confocal microscopy at 24 h post synchronisation ( n  = 28–50 independent images). e Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and treated with FK506 (12 h; 1 μM) and mitochondria morphology quantified by confocal microscopy at 24 h post synchronisation ( n  = 3 biologically independent samples). f Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised and antigen processing was quantified by confocal microscopy at indicated timepoints by the addition of DQ-OVA (1 µg/mL) in the presence or absence of FK506 (1 µM). ( n  = 50 independent images). Data shown is mean with error bars representing ± SEM. Data were analysed by one-way ANOVA with Tukey’s post-hoc test for multiple comparisons. * p  < 0.05, ** p  < 0.01 and **** p  < 0.0001. Source data are provided as a Source Data file.

As calcineurin is a key regulator of mitochondrial morphology and is itself regulated by cytosolic calcium levels, we wished to investigate if calcineurin was mechanistically involved. Inhibition of calcineurin using FK506 was able to promote mitochondrial fusion and reduce mitochondrial fission at 24 h post synchronisation in both Bmal1 +/+ and Bmal1 − / − genotypes (Fig.  6e ). Importantly, FK506 was also able to boost the deficit in antigen processing in Bmal1 +/+ BMDCs observed at 24 h post serum synchronisation (Fig.  6f ). FK506 had no effect on antigen processing at 12 h or 36 h post serum synchronisation in Bmal1 +/+ as mitochondria were in a naturally fused state at this time-of-day due their circadian regulation (Fig.  6f ). Similarly to Mdivi-1, FK506 was able to rescue the defect in antigen processing observed at all timepoints post synchronisation in Bmal1 − / − BMDCs (Fig.  6f ). We hypothesised that the circadian control of antigen processing via mitochondria could be through ATP (Fig.  3d ). However, neither Mdivi-1 or FK506 was able to enhance ATP levels (Supplementary Fig.  4b ). Nonetheless, these results demonstrate a previously uncharacterised role for the endogenous molecular clock in controlling cellular calcium localisation to then impact on calcineurin activity. This in turn affects mitochondrial morphology and metabolism to influence DC antigen processing.

Circadian variation in mitochondrial calcium is regulated by circadian control of the mitochondrial calcium uniporter

While we demonstrated that calcium localisation displayed a circadian pattern, we wished to understand the mechanism underpinning these effects. As the recently discovered mitochondrial calcium uniporter (MCU) complex is the major calcium transporter of the mitochondria, we reasoned that the molecular clock might regulate components of the MCU complex and control mitochondrial calcium levels throughout the day 43 , 44 . To investigate this, we isolated CD11c + cells from mouse spleens at ZT1, ZT7, ZT13 and ZT19. Genes associated with the MCU were analysed by qPCR and their oscillations were investigated for circadian rhythmicity using the JTK_Cycle component within MetaCycle 45 . We confirmed circadian rhythmicity in splenic DCs in both Bmal1 and Per2 (Fig.  7a ) and also found that genes associated with mitochondrial calcium uptake, Mcub and Emre , were cycling in a similar circadian pattern and phase. This suggested that circadian control of antigen processing in DCs could be regulated through circadian control of mitochondrial calcium transport. To confirm this, we investigated antigen processing potential of BMDCs in the presence or absence of the MCU inhibitor, ruthenium red 46 . We found a significant decrease in mitochondrial calcium uptake in both Bmal1 +/+ and Bmal1 − / − in the presence of ruthenium red (Fig.  7b ) and critically, ruthenium red also inhibited the BMDCs potential to process DQ-OVA (Fig.  7c ). The inhibition of the mitochondrial calcium uptake with ruthenium red also reduced DC’s potential for activation of OTII CD4 + T cells, as indicated by IFNγ levels (Fig.  7d ). These data show that components of the MCU complex are regulated in a circadian manner and that this temporal control of calcium transport plays a key mechanistic role in regulating antigen processing within DCs. Accompanying materials and methods are listed in the supplementary section.

a Spleens were isolated from WT mice at ZT 1, 7, 13 and 19. CD11c + cells were isolated and mRNA analysed by qPCR. Circadian analysis was performed using Metacycle and cycMethod set to “JTK”. P value for each gene is specified on the graph. ( n  = 3 mice) ( b, c ) Bmal1 +/+ and Bmal1 −/− BMDCs were synchronised by serum shock. DQ-OVA and mitochondrial calcium uptake was quantified at 12 h post synchronisation in the presence and absence of ruthenium red (5 µM) ( n  = 3 biologically independent samples). d CD11c + cells were isolated from WT spleen at ZT4 and treated with ruthenium red (10 µM) for 3 h. OVA protein (25 µg/mL) was then added for 2 h. Supernatants were removed and indicated number of OTII CD4 + T-cells were added to CD11c + cells. Cells were incubated for 3 days before IFNγ were analysed by ELISA (n = 3 biologically independent samples) p  = 0.02. e Schematic showing proposed mechanisms by which the circadian clock in DCs controls antigen processing as inferred from the present study. Data shown are means with error bars representing ± SEM. Data were analysed by Ordinary one-way ANOVA with Tukey’s post-hoc test for multiple comparisons ( b , c ) or by a two-tailed t -test ( d ). ** p  < 0.01 and **** p  < 0.0001. Source data are provided as a Source Data file.

The significant finding of this study is that the molecular clock in DCs influences T cell responses. We demonstrate that the DC molecular clock orchestrates a series of events, including altering mitochondrial morphology and coordinating calcium localisation to regulate antigen processing and presentation. Any change to cytoplasmic calcium will in turn regulate cytosolic, calcium-dependent enzymes. Calcineurin is one such calcium-dependent phosphatase that is also essential in regulating mitochondrial morphology via DRP1 40 . Furthermore, it has been reported mitochondrial calcium buffering can regulate calcineurin activity 47 . We showed that as mitochondrial calcium increased during the circadian cycle, cytoplasmic calcium decreased. Reduced cytoplasmic calcium lowered calcineurin’s phosphatase activity, thereby promoting mitochondrial fusion. Consistent with our findings increased concentrations of mitochondrial calcium and fusion morphology are both associated with higher mitochondrial metabolism 38 , 48 , 49 . Increasing mitochondrial fusion, by inhibition of calcineurin or DRP1, enhanced antigen processing. Therefore, these daily oscillations in mitochondrial morphology and its associated metabolic output impact on the capacity of DC to process and present antigens to T cells.

There is now a growing body of evidence that circadian rhythms play a key role in the immune response to vaccination. It has been shown that immunisation with BCG, influenza or hepatitis A vaccines in the morning resulted in higher antibody responses when compared with vaccination in the afternoon 8 , 9 , 27 , 28 . While it has been shown that T cells proliferated to a greater extent when stimulated either through MHC-TCR or anti-CD3 at ZT8 29 , 50 , these studies used peptides rather than whole protein thereby bypassing antigen processing by DCs 29 . We adoptively transferred CTV + labelled OTII CD4 + T cells which were harvested from mice at one circadian phase and transferred into mice that were phase shifted to ZT7 or ZT19. Transfer of T cells from one circadian phase into either ZT7 or ZT19 mice allowed us to examine more specifically the DC circadian response in vivo. Our work shows that Bmal1 control of antigen processing also contributes to the circadian regulation of vaccination. To our knowledge, there are no studies investigating the role of DCs in circadian responses to vaccination. Ex vivo analysis showed a steady increase in DC antigen processing from ZT7 to a peak at ZT19 and a decline. We rationalise that ZT7 injections align with a time that allows optimal antigen processing capacity of DCs. Hence, immunising mice at ZT7 shows a higher response in comparison to ZT19. Our results are consistent with Holtkamp et al. who demonstrate that skin DCs preferentially migrate into lymphatic vessels at ZT7 due to rhythmic gradients in the chemokines CCL21, LYVE, JAM-A and CD99 on skin lymphatic endothelial cells and CCR7, the receptor on DCs for CCL21 22 . Thus, our results, along with others, show that activation of T cell responses is greatest when mice are immunised around ZT7. Taken together, this suggests that the molecular clock of the immune system coordinates DC and T cell functions for optimal activation to invading pathogens at distinct times-of-day.

Significant evidence suggests that circadian rhythms regulate glucose homoeostasis, lipid metabolism and amino acid metabolism at both the cellular and organism level 51 , 52 , 53 , 54 , 55 , 56 . The strong links between circadian control of metabolism provoked our current study given the significant number of studies showing that metabolism is a major regulator of DC function 14 , 57 in particular via mitochondrial metabolism 24 , 35 . Similarly to the results on antigen processing, we found significant circadian rhythmicity in DC mitochondrial morphology and metabolism 12 , 35 , 57 . Mitochondrial metabolism was essential for antigen processing as electron transport chain inhibitors decreased antigen processing by DCs and their ability to activate of T cells. This places mitochondrial metabolism as an upstream regulator of antigen processing adding to the growing list of immune processes regulated by metabolism.

Altering mitochondrial morphology is one way a cell can alter its mitochondrial metabolism with increased mitochondrial fusion being linked to increased OXPHOS and energy production 38 , 48 . Bmal1 dependent rhythms in antigen processing temporally aligned with the rhythms in mitochondrial fusion, implicating a previously uncharacterised role for clock controlled mitochondrial morphology and metabolism in antigen processing. Our data suggests that the molecular clock controls mitochondrial morphology by regulating levels and activity of the key fission proteins, Fis1 and Drp1. In a key rescue experiment we found that the Drp1 inhibitor Mdivi-1 could reverse the circadian decrease in antigen processing back to peak levels 39 . More impressively, increasing mitochondrial fusion in DCs lacking a functional circadian clock also rescued the antigen processing deficit observed in these cells. Increasing antigen processing through promoting mitochondrial fusion demonstrates the mechanistic link between mitochondrial morphology and antigen processing in DCs. Thus, artificially fusing the mitochondria with small molecules could increase antigen processing and might be considered for future vaccine formulations 58 .

The ability of circadian rhythms to regulate antigen processing/presenting was intricately linked to calcium localisation. Mitochondria provide calcium buffering capacity to regulate cellular cytosolic calcium 59 , 60 . Furthermore, mitochondrial Ca 2+ buffering capacity lowered cytosolic Ca 2+ that increased in mitochondrial fusion, boosting OXPHOS and ATP production, due to decreased calcineurin activity 40 , 41 , 47 , 61 . Synchronised HepG2 cell cultures display a circadian rhythm in mitochondrial Ca 2+ which drives rhythmic mitochondrial respiration 17 . Given calcium’s importance in energy production, it is perhaps unsurprising it plays an important role in DC antigen processing/presentation. Experiments over the last number of decades with ruthenium red suggested the existence of a mitochondrial calcium transporter, however, the molecular identity of the MCU complex was only recently discovered 43 . Here, we report, that genes associated with the MCU complex are circadian regulated. More specifically, we found that Emre and Mcub , negative regulators within the MCU complex, were expressed in a circadian manner. In addition to our own findings, we have also identified genes associated with the MCU complex, such as, Mcu and Micu1 in existing circadian datasets 14 , 62 . As the molecular clock drives an increase in mitochondrial calcium, cytosolic calcium decreases in a circadian pattern and this allows broad circadian regulation of many calcium regulated enzymes while also boosting mitochondrial metabolism. We predict that circadian control of MCU will regulate diverse functions in many cell types. Calcineurin is indirectly circadian regulated through circadian manipulation of calcium location 40 . Inhibition of calcineurin phenocopied the boost of antigen processing seen with Mdivi-1. This was surprising as calcineurin is an inhibitor of T cell activation and proliferation, we show that when inhibited in DCs, it can increase antigen processing and boost T cell activation and proliferation. A number of aspects including exactly how the molecular clock regulates components of the MCU complex are beyond the scope of this study and will require further investigation. Future work should help to determine the mitochondrial metabolites that enhance antigen processing, and whether ATP is a contributing factor. The importance of the ER in terms of mitochondrial Ca 2+ efflux and antigen processing will also be the subject of future investigations 17 .

Collectively, this research has provided insights on the regulation of antigen processing by circadian rhythms and could inform the development of chronotherapeutic vaccination strategies. The finding that mitochondrial morphology and metabolism play a key role in enhancing antigen processing/presentation and T cell activation may enhance vaccination efficacy or longevity. The use of small molecules to modify mitochondrial morphology and metabolism could be a useful approach to enhancing vaccine responses irrespective of time of day.

Ethical regulations

All research complied with all relevant ethical regulations. All mice were maintained according to European Union regulations and the Irish Health Products Regulatory Authority. Experiments were performed under Health Products Regulatory Authority license with approval from the Trinity College Dublin BioResources Ethics Committee. All animal procedures were in line with the EU Directive 2010/63/EU and with a project authorisation number AE19136/P007.

All mice were 6–10 weeks old at the initiation of experiments and housed in a specific pathogen–free facility in the Comparative Medicine Unit (CMU), Trinity College Dublin. The environmental conditions maintained in all rodent rooms in CMU were temperature 20–24 °C with 45–65% humidity. All mice were on a C57BL/6 J background, with wild-type mice obtained from the CMU at Trinity College Dublin. For the adoptive transfer experiments (Fig.  1 ) only male mice were used. Mice with the gene Bmal1 containing LoxP sites were kindly provided by Christropher Bradfield. Bmal1LoxP/LoxP were crossed with Lyz2Cre mice, which express Cre recombinase under the control of the Lyz2 promoter to produce progeny that have Bmal1 excised in the myeloid lineage. Bmal1LoxP/LoxP::Lyz2Cre ( Bmal1 myeloid−/− ) mice where compared with control Lyz2Cre ( Bmal1 myeloid+/+ ). Offspring were genotyped to confirm the presence of LoxP sites and Cre recombinase. C57Bl/6J mice, OVA-specific CD4+ (OT-II) T-cell receptor-transgenic mice ( H-2b ) 63 for the adoptive transfer of OT-II cells and PERIOD2::luciferase 64 were also bred in CMU. All mice were maintained on a 12 h:12 h light:dark regimen with ad libitum food and water prior to experimentation.

Isolation and staining of OT-II cells for adoptive transfer experiments

OT-II transgenic mice (B6.Cg-Tg(TcraTcrb)425Cbn/J) were euthanized, and spleens were removed by dissection. Tissues were mashed onto a cell strainer, and the cells obtained were pooled, washed twice in PBS solution, and resuspended in PBS at 1 × 10 8 cells/ml. OTII CD4 + T cells were isolated by negative selection, using EasySep magnetic nanoparticles (StemCell Technologies), according to the manufacturer’s protocol. The purity of the CD4 + cell population in the enriched fraction was >95%, as determined by flow cytometry analysis. CD4 + isolated T cells were pooled and stained with CellTrace™ Violet (CTV; 5 μM Invitrogen) for 20 min at 37 °C. 4 × 10 6 of CTV-labelled T cells were transferred by intraperitoneal (i.p.) injections to mice phase shifted to ZT7 or ZT19 (described in more detail in next section).

Adoptive transfer of CTV-labelled T cells, immunisations and isolation of mediastinal lymph nodes to conduct T cell characterisation by flow cytometry

For the adoptive transfer experiment (Fig.  1 ), light cabinets were used to shift animals to specific light-dark cycles. Mice were given at least two weeks to entrain to any altered lighting schedule changes. This allowed us to transfer CTV-labelled OT-II T cells from donor mice taken at ZT3 into recipient mice who had been phase shifted to ZT7 or ZT19. This allowed simultaneous experimentation at ZT7 and ZT19. 24 h later ZT7/ZT19 mice were immunised simultaneously with 1/50 human dose of a whole cell Pertussis (wcP) vaccine (Shan-5, Shantha Biotechnics Private, India) and OVA (EndoFit Ovalbumin, InvivoGen) 10 µg/mouse. Mice were immunised intraperitoneally (i.p.) with a final volume of 200 µl. 72 h later, again corresponding to the respective phase of ZT7 and ZT19, mice were euthanised by CO 2 and mediastinal lymph nodes were harvested.

Mediastinal lymph nodes were passed through a 40 μm and 70 μm cell strainer to a obtain single-cell suspension. Cells were incubated with Zombie NIR TM Fixable Viability kit (Biolegend), for 20 min and then washed with PBS, followed by surface staining with fluorochrome-conjugated anti-mouse antibodies for various markers. Cells were incubated with the antibodies CD69-FITC (H1.2F3), CD11c-BV605 (N418), CD4-BV785 (RM4-5), CD11b-PE-Dazzle TM 594 (M1/70), CD45R-PE-Cy5 (RA3-6B2) from Biolegend, MHC-II-APC (M5/114.15.2), CD3-PE (145-2C11), CD8-PECy7 (53–6.7) from Thermo Scientific, and with CD16/CD32 FcγRIII (BD Pharmingen) to block IgG Fc receptors. Then cells were fixed in 2% PFA (Thermo Scientific) for 15 min on ice. Flow cytometric analysis was performed on an Cytek® Aurora, and data were acquired using SpectroFlo® software (Cytek Biosciences). The results were analysed using FlowJo software (TreeStar).

Bone marrow-derived DCs (BMDCs)

Bone marrow cells were obtained from the femurs and tibiae of 6–10 week old mice of both sexes. This included Bmal1LoxP/LoxP::Lyz2Cre ( Bmal1 myeloid−/− ) which where compared with control Lyz2Cre ( Bmal1 myeloid+/+ ). This also included bone marrow harvest from PERIOD2::luciferase mice which were used for lumicycle analysis and also C57Bl/6J mice as WT BMDCs. Bone marrow cells were cultured in Dulbecco’s modified eagle medium (DMEM) medium (Gibco) supplemented with 10% foetal bovine serum (FBS) (Gibco), 100 U/ml penicillin, 100 μg/ml streptomycin, and 20 ng/ml GM-CSF (Biolegend, San Diego CA, USA) or 10% J558 cultured supernatants. Cells were maintained at 37 °C in a 5% CO 2 atmosphere for 7 days, to allow for cell differentiation into BMDCs. Culture medium was freshly replaced every 2–3 days.

BMDC synchronisation

In order to detect circadian rhythmicity at the population levels, cells were synchronised by serum shock treatment. BMDCs (0.5 × 10 6 ) were cultured in 12-well culture plates overnight in either RPMI or DMEM medium and supplemented with 10% FBS, 1% Penicillin-Streptomycin (100 U/ml), 1% sodium pyruvate and 20 ng/ml GM-CSF.The following day cells were incubated with RPMI medium supplemented with 50% of horse serum (Gibco) for 2 h and then replaced with fresh 5% FBS DMEM, as described previously 30 . BMDCs were considered at 0 h post synchronisation following removal of 50% horse serum. BMDCs from an individual well (0.5 × 10 6 cells) were harvested at indicated time points post synchronisation.

Lumicycle analysis

BMDCs from PERIOD2::luciferase mice were plated at a density of 1.8 × 10 6 in 35 mm dishes in RPMI medium and supplemented with 10% FBS, 1% Penicillin-Streptomycin (100 U/ml), 10 mM HEPES and 20 ng/ml GM-CSF. The following day, BMDCs were synchronised by serum shock as described above. To monitor circadian rhythmicity, synchronisation media was replaced with Lumicycle recording media (DMEM containing l-glutamine and 1000 mg glucose, without phenol red and sodium bicarbonate (Sigma product code D-2902), 10% FBS, 1% Pen/Strep, 10 mM HEPES, GM-CSF; 20 ng/mL, 0.1 mM beetle luciferin potassium salt (Promega E1603). The 35 mm dishes were sealed using 40 mm coverslips with Dow Corning® high-vacuum silicone grease. Bioluminescence was recorded with the 32-channel Lumicycler by Actimetrics for 5 days beginning at 16 h post serum shock. Analysis was performed using the Actimetrics Lumicycle Analysis programme.

Harvesting and dissociation of spleen for cell isolation

Bmal1 myeloid−/− , Bmal1 myeloid+/+ and C57Bl/6J mice, were maintained on 12 h:12 h light:dark regimen with ad libitum food and water prior. Spleens were harvested at the designated ZT in RPMI medium with 2 mM L-glutamine (Gibco) supplemented with 10% FBS (Sigma Aldrich) and 100 U/ml penicillin and 100 mg/ml streptomycin (Sigma Aldrich). Spleens were homogenised and passed through a 70 μm cell strainer to generate a single cell suspension and used for subsequent analysis.

Antigen processing assays

Antigen processing assays were performed as described using DQ-OVA 65 and were analysed either by confocal microscopy or flow cytometry. DQ-OVA is a self-quenched conjugate of the ovalbumin protein which is strongly labelled with BODIPY dyes, it will exhibit bright fluorescence upon proteolytic degradation into singly, dye labelled peptides. Antigen processing by DQ-OVA was analysed either by confocal microscopy or flow cytometry.

For confocal microscopy analysis, BMDCs (2 × 10 5 cells/well) were grown in Lab-Tek chambers (Thermo Fisher Scientific) and DQ-OVA (1 μg/mL; Life technologies) was added to cells for 15 min at 37 °C (to measure uptake but not processing and is used as a control) or 60 min at 37 °C (to measure processing) at indicated time points. At the end of each incubation period, BMDCs were washed and fixed with 4% paraformaldehyde. Fixed cells were mounted with DAPI-containing Vectashield (Vector) and analysed by using a Leica SP8 scanning confocal microscope (Wetzlar, Germany), using a 63× oil immersion objective. Mean Fluorescence Intensity (MFI) of DQ-OVA was assessed on 25–30 images for each experimental condition and from three independent experiments using ImageJ software (National Institutes of Health, Bethesda, MD).

To investigate the impact of mitochondrial metabolism/function on antigen processing, BMDCs were pre-treated with oligomycin (10 μM) and FCCP (100 μM) for 1 h prior to performing the antigen processing assay and quantification by fluorescence on confocal microscopy.

For flow cytometry analysis, antigen processing analysis of splenic DCs was performed the same way as described above except cells were plated in 96 well plates (0.5 × 10 6 ) per well. After either 15 min or 60 min of DQ-OVA, cells were fixed with paraformaldehyde and analysed by flow cytometry.

Synchronised BMDCs were pretreated with Mdivi-1 (10 μM–M0119, Sigma) or FK506 (1 μM – TLRL-FK5, Invivogen) for 12 h prior to harvesting.

B16-FLT3L cell culture and in vivo expansion of splenic DCs

B16-FLT3L cell line was cultured in a humidified 5% CO 2 atmosphere at 37 °C with DMEM medium with 2 mM L-glutamine (Invitrogen Biosciences) supplemented with 10% (v/v) heat-inactivated FCS (Labtech, International) and 100 U/ml penicillin and 100 mg/ml streptomycin (Invitrogen/Biosciences). This cell line was tested for absence of mycoplasma using the PCR Mycoplasma Test Kit (AppliChem) according to manufacturer’s instructions. For splenic DC expansion, 2.5 × 10 6 B16-FLT3L cells in 100 μl of PBS were injected subcutaneously (sc) in the right flank of the mice. Mice were sacrificed 10–13 days after cell injection at the corresponding ZTs and splenic DC subsets and antigen processing analysed by flow cytometry.

Flow cytometry for ex vivo analysis of splenic DCs

Splenocytes were cultured in U-bottom 96-well plates (VWR) at 1 × 10 6 cells/200 μl of supplemented RPMI medium and incubated as described for antigen processing assays. Thereafter, cells were washed and incubated for 5 min at 4 °C with Fc blocking antibody (2.4G2) (BD Pharmingen) before stained for 20 min in the dark at 4 °C with saturating concentrations of surface-targeted antibodies and viability markers. Cells were fixed with Cytofix/Cytoperm kit (BD Biosciences), measured by FACS Fortessa (BD Biosciences) and analysed by FlowJo software (Tree Star, Ashland, OR). Dead cells were excluded using Zombie Yellow (Biolegend). Antibodies used as follows: CD3-APC (145-2c11, Biolegend), F4/80-AF700 (cat. MCA497A700, BioRad), LY6G/6C-APC-Cy7 (RB6-8C5, BD), NK1.1-BV421 (PK136, Biolegend), MHCII-BV711 (M5/114, BD), CD11c-BV785 (N418, Biolegend), CD11b-PE-Cy7 (M1/70, BD), CD45R/B220-V500 (RA3-6B2, BD), CD103-PE (2E7, Invitrogen), CD8-Percp-Cy5.5 (53–6.7, Biolegend) and CD317-BV650 (927, Biolegend).

Bioenergetic assays and analysis

Oxygen consumption rate (OCR) or mitochondrial respiration was analysed using the Agilent Seahorse XF Cell Mito Stress Test and measured on a XF e 96 Analyzer. Briefly, 8 × 10 4 BMDCs were seeded in each well, excluding background wells, of an XF e 96 cell culture plate and subjected to serum synchronisation for the time points indicated. A utility plate containing the injector ports and probes was filled with calibrant solution and placed in a CO 2 -free incubator at 37 °C over-night. Before metabolism was measured, the culture medium was removed from cells and replaced with XF assay media pH 7.4 (Agilent). The XF assay media was supplemented with 10 mM glucose, 1 mM pyruvate and 2 mM glutamine. The cell culture plate was then incubated in a CO 2 -free incubator at 37 °C for 45 min. Oligomycin (1 μM), an ATP synthase (complex V) inhibitor, Carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP) (0.9 μM), an uncoupling reagent that collapses the proton gradient and Rotenone/Antimycin A (0.5 μM) were added to the appropriate ports of the utility plate for a standard MitoStress test according to the instruction manual (Agilent, 103015-100). This plate was run first on the flux analyser for calibration. Once complete the utility plate was replaced with the cell culture plate and run on the real-time Seahorse XF e 96 analyser using the software’s Mito Stress template programme.

The Mito Stress test profile allows calculation of the following parameters.

Basal respiration : shows energetic demand of the cell under baseline conditions,

Maximal respiration : the maximal oxygen consumption rate attained by adding the uncoupler FCCP, which stimulates the respiratory chain to operate at maximum capacity. This measurement shows the maximum rate of respiration that the cell can achieve.

Spare respiratory capacity : this measurement indicates the cells ability to respond to an energetic demand, this can be an indicator of cell fitness or flexibility.

BMDCs (1 × 10 6 ) were plated and synchronised. Cells were treated with FCCP (10 µM) or Oligomycin (10 µM) for 3 h and then harvested at indicated time points post-synchronisation and ATP measured using Abcam ATP assay kit (ab83355).

Mito Tracker Red CMXRos staining and mitochondrial dynamic analysis

BMDCs (0.5 × 10 6 ) were plated on a 35 mm, high glass bottom µ-Dish (Ibidi, Germany) and maintained overnight at 37 °C in a 5% CO 2 atmosphere. Cells were synchronised by serum shock as previously described. Cells were stained for 30 min with MitoTracker Red CMXRos (50 nM; Life technologies). Cells were washed with PBS followed by addition of fresh medium and cells were imaged on a Leica SP8 scanning confocal microscope (Wetzlar, Germany), with a 63× immersion objective. Cell images were obtained at indicated hours post synchronisation. Automated image analysis was performed in Fiji using custom-written macros. Fiji macros and a short user guide are available as part of the supplementary material online accompanying this article (Supplementary Software  1 ). In short, confocal slices of MitoTracker-stained macrophages were normalised to the full 16-bit range. Binary masks of approximate cell outlines were generated by intensity thresholding, binary operations to smoothen outlines and fill holes, watershedding to separate touching cells, and manual error correction. Binary masks of mitochondria were determined by band-pass filtering of raw mitochondrial images followed by auto-thresholding, removal of tiny objects, and splitting of touching mitochondria by marker controlled watershed segmentation using MorphoLibJ 66 restricted to maxima candidates pre-determined by the detection of prominent maxima in a distance transform image of the masks. For determining morphological characteristics of all mitochondria and of the mitochondria within each single cell, a batch process was performed on a set of experimental images with its masks. The “Analyze Particles” function was used to measure size and shape descriptors of all mitochondria per cell, from which median area, aspect ratio, length, circularity, and total area were determined. Results were saved as spreadsheet files and as ROI overlays to the original images that enabled the look-up between the statistics and images of every single mitochondrion. Mitochondria were then divided into three different categories, based on length, namely as mitochondria of less than 1 μm, 1–3 μm, and greater than 3 μm 67 .

Mitochondrial membrane potential (ΔΨm)

Labelling of mitochondria with MitoTracker Red CMXRos Life technologies is dependent on mitochondrial membrane potential as indicated by the manufacturer´s instructions. Confocal microscopy was used to take images of 25 individual cells from BMDCs at each time point (hr) post-synchronisation. Mean Fluorescence Intensity (MFI) of mitochondrial staining intensity was measured by Image J.

MitoTracker Green FM staining

Cells were washed with PBS, scraped, transferred to FACS tubes, and centrifuged at 300 ×  g for 5 min. MitoTracker Green (Invitrogen, cat. no. M7514) was used at a final concentration of 100 nM diluted in PBS containing 1 mM EDTA and 2% FCS (FACS buffer). Fifty microliters of 100 nM MitoTracker Green was added to each sample and incubated for 15 min at 37 degrees Celsius. Cells were washed with 1 mL FACS buffer, centrifuged at 300 ×  g for 5 min, and resuspended in 200 μL FACS buffer. Data was acquired using FACS Canto II and mean fluorescent intensity (MFI) was obtained through analysis with FlowJo Software (V10.8.1).

Immunoblot analysis

Cells were lysed in SDS PAGE sample buffer, samples boiled for 7 min, then cooled and loaded on to a SDS polyacrylamide gel for separation by electrophoresis. Following separation, samples were transferred onto nitrocellulose membranes. Membranes were probed with primary antibodies for BMAL1 (cat. #14020S, Cell Signalling Technology, dilution 1:1000), OPA1 (cat. #80471, Cell Signalling Technology, dilution 1:1000), FIS1 (cat. #PA5-22142 Thermo fisher Scientific, dilution 1:1000), MFN1 (cat. # ab126575, Abcam, dilution 1:500), MFN2 (cat. #9482S, Cell Signalling Technology, dilution 1:1000), DRP1 (cat. # 5391S, Cell Signalling Technology, dilution 1:1000), p-DRP1 (S637) (cat. # 4867S. Cell Signalling Technology, dilution 1:1000), α-Tubulin (cat. # 3873S, Cell Signalling Technology, dilution 1:1000) and β-Actin (cat. # MAB1501, EMD Millipore, dilution 1:10,000) followed by incubation with appropriate Peroxidase-conjugated AffiniPure Goat anti-rabbit IgG (cat. # 111-0350144, Jackson ImmunoResearch, dilution 1:2000) or Peroxidase-conjugated AffiniPure Goat anti-mouse IgG (cat. # 115-035-146, Jackson ImmunoResearch, dilution 1:2000). Bands were detected by chemiluminescence using Immobilion Western Chemiluminescent HRP Surbstrate (PVBKLSO500, Sigma). Bands were visualised and quantified using an Amersham 680 Imager (GE Healthcare) and ImageStudioLite and normalised to the intensity of the α-Tubulin or β-Actin band.

Real-time polymerase chain reaction

Total RNA was isolated using the Invitrogen PureLink RNA Mini Kit (Thermo Fisher, 12183025) and quantified using a Nano-Drop 1000 Spectrophotometer (Thermo Scientific Fisher). cDNA was prepared using 50–100 ng/μl total RNA using a High Capacity cDNA Reverse Transcription Kit (Thermo Fisher, 4368813), according to the manufacturer’s instructions. Primers were designed using the NCBI database ( https://ncbi.nlm.nih.gov/tools/primer-blast ) and provided by Eurofins. Please refer to Supplementary Table  1 for a list of primers used. Real-time quantitative PCR (RT-PCR) was performed on cDNA, diluted 1 in 2 with RNAase-free water, using SYBR Green probes on a 7900 HT Real-Time PCR System (Applied Biosystems). Fold changes in expression were calculated by the Delta-Delta (ΔΔ) Ct method using 18 s as a control for mRNA expression. All fold changes were normalised to untreated/non-targeting controls.

Calcium localisation analysis

BMDCs were plated in glass bottom plates (Ibidi) and synchronised, as previously described. At 12 h and 24 h post synchronisation, BMDCs were washed with PBS and labelled with either Fluo-4 AM (8 µM) (Invitrogen) rhodamine-2 AM (4 µM) (Invitrogen), which are cytosolic and mitochondrial calcium indicators respectively, for 1 h at 37 °C in 5% CO 2 . Following incubation with calcium stains, cells were rinsed six to seven times with cold PBS, replenished with fresh DMEM and incubated for 20 min before imaging. Ca 2+ imaging was conducted at room temperature on a Leica SP8 scanning confocal microscope (Wetzlar, Germany), using a 20× objective. Cell images were analysed with the ImageJ software.

DC and CD4 T cell coculture

BMDCs or splenic DCs (CD11c + ) were plated at 2.5 × 10 4 cells per well in a U-bottomed 96 well plate. BMDCs were treated with oligomycin (10 μM), Trifluoromethyoxy carbonlcyanide phenylhydraxone (FCCP; 10 μM) or ruthenium red (10 μM) for 3 h before addition of Ovalbumin (25 μg/mL) for 2 h followed by treatment with LPS (10 ng/mL) for 4 h (or remainder of experiment). Cells were then washed with PBS to remove inhibitors from culture medium and prevent any carry over effects on T cells. CD4+ T cells were isolated from spleens of OTII transgenic mice using CD4 negative selection kit (Stem Cell) according to manufacturer’s instructions. 1.25 × 10 5 CD4 + T cells were then added to the wells containing treated BMDCs or splenic DCs (CD11c+) and incubated for 3 days. Supernatants were collected on day 3 and analysed for IFNγ and IL17 by ELISA (RnD systems).

Circadian data analysis

Mitochondrial morphology, membrane potential, antigen processing in cultured BMDCs were investigated for the presence of circadian patterns using multiple regression to fit a linearised cosinor model with a pre-determined period of 24 h. Circadian patterns were indicated by statistical significance of the predicted cosinor (sine and cosine) regression coefficients 68 . The cosinor model was defined by linear sine and cosine terms of transformations of the time variable in hours:

Where Y is time in hours post serum shock, and M , β and γ were predicted by regression (1). The intercept (M) is the mean level of the curve predicted from Eq. ( 1 ), and the acrophase (Φ) is the peak x axis value of the curve, calculated as:

The amplitude (A) was the distance from the mean to the acrophase, providing an estimate of the magnitude of rhythmicity.

The cosinor curve provided a graphical representation of how closely the data approximated to the 24 h periodicity of a circadian dataset, and the statistical significance of this was determined by testing the null hypothesis that the amplitude of the curve was equal to zero. Statistical significance was accepted at values of p  < 0.05 and all analyses were performed using Stata 14 statistical software (StataCorp, College Station, TX).

MetaCycle was used to detect the presence of circadian rhythms in lumicycle data from synchronised PER2::Luciferase BMDCs and mRNA expression in splenocytes over the 24 h cycle. In MetaCycle, default settings and period length were set to 24 (h) for min and max period, cycMethod was set to “JTK” and circadian rhythms were identified with statistical significance p  < 0.05.

Statistical and reproducibility

GraphPad Prism 8.00 (GraphPad Software) was used for statistical analysis. A one-way ANOVA test was used for the comparison of more than two groups, with Tukey test for multiple comparisons. A two-tailed Student’s t -test was used when there were only two groups for analysis. All error bars represent SEM. Significance was defined as * p  < 0.05, ** p  < 0.01, *** p  < 0.001, **** p  < 0.0001. Any specific statistical tests and details of ‘n’ numbers done for experiments are listed under the corresponding figures. Measurements were taken from distinct samples. No statistical method was used to predetermine sample size. No data were excluded from the analysis. The experiments were not randomised and Investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

Source data are provided with this paper.

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Acknowledgements

The majority of this study was supported through the funding provided by Science Foundation Ireland through a Career Development Award (17/CDA/4688) and by the Irish Research Council through a Laureate Award (IRCLA/2017/110) and an RCSI Strategic Academic Recruitment Program (StAR) award all provided to AMC. Further support was provided by a Conacyt grant to MCS (CVU440823), a Science Foundation Ireland Investigator Award (16/IA/4468) to K.H.G.M. and a European Research Council Consolidator Award (ERC-CoG_771419) to D.K.F. Flow cytometry was performed at the Science Foundation Ireland funded Flow Cytometry Facility at Trinity Biomedical Sciences Institute. We wish to acknowledge the laboratory operations staff within the RCSI School of Pharmacy and Biomolecular Sciences for their technical assistance throughout the project. Figures  1 a, 2 a and 7e were created with BioRender.com.

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These authors contributed equally: Mariana P. Cervantes-Silva, Richard G. Carroll.

Authors and Affiliations

Curtis Clock Laboratory, School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland RCSI, Dublin, Ireland

Mariana P. Cervantes-Silva, Richard G. Carroll, Cloe A. Payet, James R. O’Siorain, Shannon L. Cox, Lauren E. Fagan, Paula A. Klavina, Yan He, Tabea Drewinski, Alan McGinley, George A. Timmons, James O. Early & Annie M. Curtis

School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland

Mieszko M. Wilk, Diana Moreira, David K. Finlay, Kingston H. G. Mills & Annie M. Curtis

Department of Immunology, Faculty of Biochemistry, Biophysics and Biotechnology, Jagiellonian University, Krakow, Poland

Mieszko M. Wilk

Tissue Engineering Research Group (TERG), Royal College of Surgeons in Ireland RCSI, Dublin, Ireland

Lauren E. Fagan, James O. Early & Annie M. Curtis

Irish Centre for Vascular Biology, School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons in Ireland RCSI, Dublin, Ireland

Paula A. Klavina, Roger J. S. Preston, Ingmar Schoen & Annie M. Curtis

Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou, China

Department of Biological Sciences & Center for Biotechnology and Interdisciplinary Sciences, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA

Sharleen M. Buel & Jennifer M. Hurley

Immunoregulation Laboratory, Department of Immunology, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, Mexico

F. Javier Sánchez-García

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Contributions

M.P.C.S. and R.G.C. conceived, designed and performed the majority of experiments, analysed the data and wrote and edited the manuscript. M.M.W., D.M., D.K.F. and K.H.G.M. assisted in the design, execution and analysis of the in vivo experiments. C.A.P. performed experiments with P110 and Mdivi-1, J.R.O.S. performed and analysed luciferase reporter experiments. J.R.O.S., S.M.B. and J.M.H. provided bioinformatic expertise and analysis. S.L.C. conducted mitochondrial mass experiments. T.D., L.E.F., P.A.K., R.J.S.P., G.A.T. and J.O.E. assisted in qPCR, western blot, bioenergetic, antigen processing and flow cytometry experiments and analysis. I.S. developed the semi-automated programme for mitochondria analysis. Y.H. and A.M. provided Bmal1 myeloid−/− mice and BMDC generation. J.S.G. conceived the mitochondrial morphology and antigen processing studies. K.H.G.M. assisted in editing the manuscript. A.M.C. led the project, acquired the funding for the project, conceived and designed experiments, wrote and edited the manuscript.

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Correspondence to Annie M. Curtis .

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Cervantes-Silva, M.P., Carroll, R.G., Wilk, M.M. et al. The circadian clock influences T cell responses to vaccination by regulating dendritic cell antigen processing. Nat Commun 13 , 7217 (2022). https://doi.org/10.1038/s41467-022-34897-z

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Received : 05 October 2021

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DOI : https://doi.org/10.1038/s41467-022-34897-z

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