Skip to main content
The EMBO Journal logoLink to The EMBO Journal
. 2025 Nov 17;45(1):106–150. doi: 10.1038/s44318-025-00622-x

Homeostatic control of energy metabolism by monocyte-derived macrophages

Rui Martins 1,#, Birte Blankehaus 1,#, Faouzi Braza 1, Miguel Mesquita 1, Pedro Ventura 1, Sumnima Singh 1, Sebastian Weis 2,3,4, Maria Pires 1, Sara Pagnotta 1, Qian Wu 1,5, Sílvia Cardoso 1, Elisa Jentho 1, Ana Figueiredo 1, Pedro Faísca 1, Ana Nóvoa 1, Vanessa Alexandra Morais 1, Stefanie K Wculek 6, David Sancho 7, Moises Mallo 1, Miguel P Soares 1,
PMCID: PMC12759084  PMID: 41249508

Abstract

Multicellular organisms rely on inter-organ communication networks to maintain vital parameters within a dynamic physiological range. Macrophages are central to this homeostatic control system, sensing and responding to deviations of those parameters to sustain organismal homeostasis. Here, we demonstrate that dysregulation of iron (Fe) metabolism, imposed by the deletion of ferritin H chain (FTH) in mouse parenchymal cells, is sensed by monocyte-derived macrophages. In response, monocyte-derived macrophages support tissue function, energy metabolism, and thermoregulation via a mechanism that sustains the mitochondria of parenchymal cells. Mechanistically, FTH supports a transcriptional program promoting mitochondrial biogenesis in macrophages, involving mitochondrial transcription factor A (TFAM). Moreover, FTH sustains macrophage viability and supports intercellular mitochondrial transfer from donor parenchymal cells. In conclusion, monocyte-derived macrophages cross-regulate iron and energy metabolism to support tissue function and organismal homeostasis.

Keywords: Ferritin, Macrophages, Mitochondria, Homeostasis, Metabolism

Subject terms: Immunology, Metabolism

Synopsis

graphic file with name 44318_2025_622_Figa_HTML.jpg

Macrophages play critical roles in the homeostatic control systems that maintain vital parameters within physiological ranges. This study characterizes how mouse monocyte-derived macrophages sense dysregulated iron metabolism in parenchymal cells and subsequently maintain tissue function, energy metabolism, and thermoregulation through intercellular mitochondrial transfer.

  • Monocyte-derived macrophages sense iron metabolism disruption in parenchymal cells with deleted ferritin H chain (FTH).

  • Macrophages respond by supporting parenchymal cell mitochondria, thereby maintaining tissue function, energy metabolism, and thermoregulation.

  • Macrophage FTH regulates a transcriptional program controlled by mitochondrial transcription factor A (TFAM) and supporting mitochondrial biogenesis.

  • Macrophage FTH enables intercellular mitochondrial transfer from parenchymal cells.

  • Macrophages sustain organismal homeostasis.


Macrophages sense dysregulated iron metabolism in parenchymal cells and respond by sustaining mitochondrial function in affected cells.

graphic file with name 44318_2025_622_Figb_HTML.jpg

Introduction

Iron (Fe) was co-opted through evolution to exchange electrons with acceptor (i.e., electrophile) and donor (i.e., nucleophile) molecules, partaking in vital biochemical processes, including some of those supporting mitochondrial function and energy metabolism (Muchowska et al, 2019; Teh et al, 2024). Presumably as an evolutionary trade-off (Stearns and Medzhitov, 2015), Fe can catalyze in a unfettered manner the production of hydroxyl radicals (HO) and other reactive oxygen species (ROS), when exchanging electrons with mitochondrial superoxide (O2•−) or with hydrogen peroxide (H2O2) (Winterbourn, 1995).

Cellular ROS accumulation can catalyze lipid peroxidation and in doing so, trigger programmed cell death via ferroptosis (Dixon et al, 2012). The fitness cost of uncontrolled Fe redox activity is limited by a number of evolutionarily conserved Fe-regulatory genes (Galy et al, 2024). These include ferritin h chain (FTH), the master regulator of Fe redox activity and bioavailability (Blankenhaus et al, 2019; Galy et al, 2024; Gozzelino and Soares, 2014; Harrison and Arosio, 1996).

FTH is highly expressed by Fe-recycling macrophages, a cell compartment that plays a central role in the control of organismal Fe homeostasis (Galy et al, 2024). Fe-recycling macrophages develop from yolk sac progenitors (Gomez Perdiguero et al, 2015), similar to other lineages of tissue-resident macrophages (Ginhoux et al, 2010). Throughout adult life however, these can be replaced by monocyte-derived macrophages (van Furth and Diesselhoff-den Dulk, 1984) that develop from bone marrow (BM) hematopoietic progenitors (van Furth and Cohn, 1968). This process of differentiation, from monocytes into tissue resident macrophages (Guilliams et al, 2018), occurs via the activation of transcriptional and epigenetic programs (Gosselin et al, 2014; Lavin et al, 2014), in response to tissue-specific cues (Amit et al, 2016; Okabe and Medzhitov, 2015). Heme, an Fe-containing protoporphyrin used as prosthetic group of hemoglobin, induces the genetic program supporting the development of Fe-recycling macrophages (Haldar et al, 2014).

Macrophages establish functional interactions with parenchyma cells in all tissues, early through embryonic development (Lazarov et al, 2023) and throughout post-natal life (Nobs and Kopf, 2021; Okabe and Medzhitov, 2015; Zhou et al, 2018). Under this conceptual framework, macrophages are essential to “support” the core effector functions of “primary” parenchyma (Adler et al, 2023; Meizlish et al, 2021; Zhou et al, 2018). Iron metabolism exerts a major impact on macrophage function (Soares and Hamza, 2016), suggesting that macrophages sense and respond to iron in a manner that contributes to “support” cellular and tissue function (Winn et al, 2020).

Having established that regulation of Fe metabolism by FTH exerts a major impact on organismal energy metabolism in adult mice (Blankenhaus et al, 2019) and considering the impact of Fe metabolism energy homeostasis (Joffin et al, 2022), we asked whether FTH expression in macrophages impacts on organismal energy homeostasis. We found that monocyte-derived macrophages respond to dysregulation of Fe metabolism in parenchymal cells via an FTH-dependent mechanism that controls the activation of a transcriptional program associated with mitochondrial biogenesis and regulated in macrophages by the mitochondrial transcription factor A (TFAM). This is essential to support the mitochondria of parenchymal cells and restore organismal energy balance in mice lacking FTH in parenchymal cells. Moreover, FTH expression in macrophages is essential to support macrophage viability as they act as acceptor cells of intercellular mitochondrial transfer from donor parenchymal cells. We infer that monocyte-derived macrophages operate as a central component of an inter-organ surveillance system that cross-regulates Fe and energy metabolism to support organismal homeostasis.

Results

Fth-competent hematopoietic cells rescue chimeric Fth-deleted mice

Having established that regulation of Fe metabolism by FTH exerts a critical role in the control energy metabolism in adult mice (Blankenhaus et al, 2019), we sought to determine the relative contribution of FTH expression in hematopoietic vs. parenchyma (i.e., non-hematopoietic) to energy homeostasis. To this end we used FthR26fl/fl mice allowing for global Fth-deletion (i.e. FthR26Δ/Δ) in response to tamoxifen (TAM) administration and Fthwt/wt or Fthfl/fl mice as controls (Blankenhaus et al, 2019). FthR26fl/fl and control Fthwt/wt or Fthfl/fl mice were lethally irradiated and transplanted with bone marrow (BM) cells from FthR26fl/fl vs. control Fthwt/wt or Fthfl/fl mice, to generate chimeric mice carrying an Fth deletion in hematopoietic vs. parenchyma cells, in response to TAM administration. We confirmed that BM engraftment was >95%, as assessed by the relative proportion of donor vs. recipient CD45.1 vs. CD45.2 cells, respectively, 4 weeks after BM transplantation (Appendix Fig. S1A–C).

Systemic Fth deletion in hematopoietic and parenchyma cells from FthR26Δ/ΔFthR26Δ/Δ chimeras (i.e., FthR26fl/fl mice reconstituted with FthR26fl/fl BM) led to wasting (Fig. 1A,B; Appendix Fig. S1D,E), hypothermia (Fig. 1A,C; Appendix Fig. S1D,F) and death (Fig. 1A,D; Appendix Fig. S1D,G), within 10-40 days after TAM administration, consistent with global Fth deletion in adult FthR26Δ/Δ mice (Blankenhaus et al, 2019). Control Fth-competent Fthwt/wtFthfl/fl chimeric mice (i.e., Fthfl/fl mice reconstituted with Fthwt/wt BM) did not develop this lethal wasting syndrome in response to TAM administration at the same dosage and schedule (Fig. 1B–D; Appendix Fig. S1D–G).

Figure 1. Fth-competent monocyte-derived macrophages rescue Fth-deleted mice.

Figure 1

(A) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0) and vital parameters monitored. Relative (B) Body weight, (C) Temperature and (D) survival of Fthwt/wtFthfl/fl (n = 7–8), FthR26Δ/ΔFthR26Δ/Δ (n = 6), Fthwt/wtFthR26Δ/Δ (n = 10–21) and FthLysMΔ/ΔFthR26Δ/Δ (n = 9–12) chimeric mice. Data in (BD) is pooled from 6 independent experiments with similar trends. Data in (B, C) represented as mean ± SD. (E) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0) and flow cytometry analysis of monocyte/macrophage populations. (F) Absolute number of CX3CR1+LY6Chigh monocyte-derived macrophages (backgated as Ly6GCD11b+F4/80low) in the liver, heart, lungs and kidneys of Fthfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 7) and FthLysMΔ/ΔFthR26Δ/Δ (n = 6) chimeric mice, 7 to 19 days post-TAM administration. Data in (F) presented as individual values (circles) and mean (red bars), pooled from three independent experiments with similar trends. (G) Schematic representation of parabiosis, TAM administration (day 0) and survival of parabiotic Fthfl/flFthfl/fl (n = 7 pairs), FthR26Δ/ΔFthR26Δ/Δ (n = 10 pairs), Fthfl/flFthR26Δ/Δ (n = 14 pairs) and FthLysMΔ/ΔFthR26Δ/Δ (n = 11 pairs). Data in (G) pooled from four independent experiments with similar trends. (H) Schematic representation of adoptive transfer of in vitro-differentiated BMDM into recipient mice, following TAM administration (day 0). (I) Survival of Fthfl/fl or FthR26Δ/Δ mice adoptively transferred with Fth-competent tdTR26 or Fth-deleted tdTR26FthR26Δ/Δ BMDM. Times of adoptive transfer indicated by orange arrows. (J) Number of adoptively-transferred tdT+ cells per liver and spleen from recipient mice, 24 h post-adoptive transfer, on day 7 post-tamoxifen treatment. Data in (J) represented as individual values (circles, n = 5–6 per group) and mean (red bars) and is pooled from two independent experiments. (K) tSNE analysis of tdTomato+ cells recovered from the liver of control (Fthfl/fl) or FTH-deficient (FthR26Δ/Δ) mice, following adoptive transfer with control, or FTH-deficient tdTomato reporter BMDM (tdTR26, tdTR26FthR26Δ/Δ, respectively), with tdTomato expression levels mapped onto the projections (L) tSNE plots showing marker expression profiles in control tdTR26 or tdTR26FthR26Δ/Δ BMDMs, prior to adoptive transfer (top 2 rows), as well as marker expression profiles in tdTomato+ cells recovered from the liver of control Fthfl/fl or FthR26Δ/Δ mice, following adoptive transfer with control, or FTH-deficient tdTomato reporter BMDM (tdTR26, tdTR26FthR26Δ/Δ, respectively). Each plot displays the expression of the designated marker across the tSNE projection for each genotype. Data in (K, L) represented as a dot plot where dots indicate individual cells. tSNE was used to generate projections from 2500 cells (downsampled) for BMDM prior to adoptive transfer, and from 701 to 1932 cells for BMDM recovered from the liver following adoptive transfer (pooled from three mice per group). Survival analysis was performed using Log-rank (Mantel–Cox) test. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001. Source data are available online for this figure.

Fth deletion specifically in parenchyma cells (i.e., Fthwt/wtFthR26Δ/Δ chimeras; FthR26fl/fl mice reconstituted Fthwt/wt BM) did not cause the development of wasting (Fig. 1B), hypothermia (Fig. 1C) or lethality (Fig. 1D). Moreover, Fth deletion specifically in hematopoietic cells (i.e., FthR26Δ/ΔFthfl/fl chimeras; Fthfl/fl mice reconstituted with FthR26fl/fl BM) also did not cause wasting (Appendix Fig. S1D,E), hypothermia (Appendix Fig. S1D,F) nor mortality (Appendix Fig. S1D,G). These observations suggest that Fth-competent hematopoietic cells can rescue the lethal outcome of systemic Fth deletion in chimeric mice.

Fth-competent myeloid cells rescue chimeric Fth-deleted mice

To establish whether myeloid cells are necessary to rescue the lethal outcome of Fth deletion in adult mice, we generated chimeric mice with BM cells from FthLysMΔ/Δ mice, carrying an Fth deletion specifically in myeloid cells (Ramos et al, 2019; Wu et al, 2023). Fth-deleted myeloid cells failed to prevent the development of wasting (Fig. 1B), hypothermia (Fig. 1C) and death in FthLysMΔ/ΔFthR26Δ/Δ chimeras (i.e., FthR26fl/fl mice reconstituted with FthLysMΔ/Δ BM), with all chimeric mice succumbing within 80 days of TAM administration (Fig. 1D). This suggests that FTH expression in myeloid cells is essential to rescue the lethal outcome of global Fth deletion in chimeric mice.

Although FthLysMΔ/ΔFthR26Δ/Δ chimeras succumbed to Fth deletion, the temporal dynamics were delayed, as compared to FthR26Δ/ΔFthR26Δ/Δ chimeras. This likely reflects (i) mosaic/incomplete Fth deletion in LysMCre cells, (ii) in vivo selection for cells that express some FTH or (iii) both. As such, subsequent analyses were conducted as the body weight of FthR26Δ/ΔFthR26Δ/Δ or FthLysMΔ/ΔFthR26Δ/Δ was reduced by more than 10% defining “early onset” and “late onset”, respectively.

To establish whether Fth-competent lymphocytes are necessary to rescue the lethal metabolic collapse caused by systemic Fth deletion, we generated FthCd2Δ/Δ mice, carrying an Fth deletion specifically in lymphocytes. Fth deletion in lymphocytes did not compromise the capacity of hematopoietic cells to prevent the development of wasting (Appendix Fig. S1H,I), hypothermia (Appendix Fig. S1H,J) nor lethality (Appendix Fig. S1H,K) in FthCd2Δ/ΔFthR26Δ/Δ chimeras (i.e., FthR26fl/fl mice reconstituted with FthCd2Δ/Δ BM). This suggests that FTH expression in lymphocytes, the most abundant population of circulating leukocytes in adult mice, is not required to rescue the lethal outcome of Fth deletion in parenchyma cells.

Monocyte-derived macrophage depletion in chimeric Fth-deleted mice

Hematopoietic Fth deletion was associated with the depletion of monocyte-derived macrophages (Ly6GCD11b+F4/80low) expressing C-X3-C Motif Chemokine Receptor 1 (CX3CR1) and high levels of Lymphocyte Antigen 6 Complex, Locus C (LY6C) (CX3CR1+LY6Chigh) in FthR26Δ/ΔFthR26Δ/Δ chimeras, as illustrated in the liver, heart, lungs and kidneys (Figs. 1E,F and  EV1A). In contrast, tissue-resident CD11b−/lowF4/80high macrophages were not affected, with the exception of the lungs (Fig. EV1B,C). Moreover, monocyte-derived (Figs. 1E,F and  EV1A) and tissue-resident macrophages (Fig. EV1B,C) were not depleted when Fth was deleted specifically in parenchyma cells from Fthwt/wtFthR26Δ/Δ chimeras.

Figure EV1. Monocyte-derived macrophages are depleted in chimeric Fth-deleted mice.

Figure EV1

Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0) and representative flow cytometry dot plots for (A) monocyte-derived macrophage (backgated as Ly6G, CD11b+, F4/80low) and (B) tissue-resident macrophage (Ly6G, CD11b−/low, F4/80high) populations present in the liver, heart, lungs and kidneys of Fthfl/fFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 7) and FthLysMΔ/ΔFthR26Δ/Δ (n = 6) chimeric mice, 7 to 19 days post-TAM administration. Data in (A, B) is pooled from 3 independent experiments with similar trends. (C) Absolute number of tissue-resident macrophages (Ly6GCD11b−/lowF4/80high) in the liver, heart, lungs and kidneys of Fthfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 7) and FthLysMΔ/ΔFthR26Δ/Δ (n = 6) chimeric mice, 7 to 19 days post-TAM administration. Data in (C) presented as individual values (circles) and mean (red bars), pooled from 3 independent experiments with similar trends. (D) Schematic representation of TAM-induced Fth deletion (day 0) in chimeric mice, and survival of Fthfl/flFthfl/fl (n = 10), FthCx3cr1Δ/ΔFthR26Δ/Δ (n = 12) and Fthfl/flFthR26Δ/Δ (n = 10) chimeric mice. Data in (D) pooled from 3 independent experiments with similar trends. (E) Schematic representation of TAM-induced Fth deletion in chimeric mice, and survival of Ccr2+/+Fthfl/fl (n = 7), Ccr2−/−FthR26Δ/Δ (n = 6) and Ccr2+/+⇨⇨FthR26Δ/Δ (n = 15) chimeric mice following TAM administration on day 0. Data in (E) is pooled from 3 independent experiments with similar trends. (F) Time course of relative body weight changes of Fthfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 10), Fthfl/flFthR26Δ/Δ (n = 14) and FthLysMΔ/ΔFthR26Δ/Δ (n = 11) parabiotic mouse pairs, following TAM administration on day 0. Data in (F) are presented as mean ± SD, normalized to the initial body weight (t0) and pooled from 4 independent experiments with similar trends. Survival analysis was performed using Log-rank (Mantel–Cox) test. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001.

There was a marked reduction of the number of monocyte-derived macrophages when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras (Figs. 1E,F and  EV1A). This was not associated however with a reduction of tissue-resident macrophages, with the exception of the kidneys (Fig. EV1B,C).

This suggests that when Fth is deleted in parenchyma cells, FTH expression becomes essential to support tissue-dependent differentiation, and/or viability, of CX3CR1+LY6Chigh monocyte-derived macrophages (Guilliams et al, 2018; Trzebanski et al, 2024). Of note this is not observed when FTH is expressed in parenchyma cells from mice in which Fth is deleted specifically in myeloid cells (Bolisetty et al, 2015; Ikeda et al, 2020),

Fth-competent monocyte-derived macrophages rescue chimeric Fth-deleted mice

Monocyte-derived macrophages support tissue function (Amit et al, 2016; Guilliams et al, 2018), suggesting that classical monocytes (CX3CR1+LY6ChighF4/80) prevent the lethal outcome of global Fth deletion in chimeric mice. To test this hypothesis, we generated FthCx3cr1Δ/Δ mice, carrying an Fth deletion under the control of the Cx3cr1 promoter (Jung et al, 2000). Fth-deleted classical monocytes failed to rescue the lethal outcome of Fth deletion in 50% of FthCx3cr1Δ/ΔFthR26Δ/Δ chimeras (i.e., FthR26fl/fl mice reconstituted with FthCx3cr1Δ/Δ BM) (Fig. EV1D). This partial lethality likely reflects some level of mosaicism in CX3CR1 expression, and therefore in CX3CR1-driven Cre expression in monocyte/macrophages (Yona et al, 2013). As such, mosaic FTH deletion may justify why not all in FthCx3cr1Δ/ΔFthR26Δ/Δ chimeras succumb to Fth deletion. These data suggest, nevertheless, that Fth-competent classical monocytes contribute to support organismal homeostasis, when Fth is deleted in parenchyma cells.

Monocyte-derived macrophages migrate to non-lymphoid tissues via a mechanism that relies on the chemokine/chemokine receptor monocyte chemotactic protein 1 (MCP-1; CCL2) and C-C chemokine receptor type 2 (CCR2; CD192), respectively (Boring et al, 1997). To test whether the CCL2-CCR2 chemotactic axis is required to support the salutary effects of monocyte-derived macrophages, we reconstituted FthR26fl/fl mice with BM from Ccr2 deficient Ccr2/ mice (Boring et al, 1997). Fth deletion in Ccr2/FthR26Δ/Δ chimeras was only partially lethal, compared to control Ccr2+/+Fthfl/fl chimeras (Fig. EV1E). This is likely explained by Ccr2 deletion not fully preventing monocyte BM egression (Tsou et al, 2007), with low numbers of monocyte-derived macrophages being sufficient to support organismal homeostasis, when Fth is deleted in parenchyma cells. As a non-mutually exclusive hypothesis, monocyte-derived macrophages might support organismal homeostasis via a mechanism that is only partially CCL2/CCR2-dependent.

Fth-competent circulating monocytes rescue chimeric Fth-deleted mice

To test whether circulating monocytes carry the capacity to rescue the lethal outcome of systemic Fth deletion we used parabiosis, an experimental approach whereby a common circulatory system is established surgically to enable the transit of circulating cells (and soluble factors) between two mice (Harris, 2013). Global Fth deletion caused severe wasting (Fig. EV1F) and was lethal (Fig. 1G) in parabiotic FthR26Δ/ΔFthR26Δ/Δ pairs. Expression of FTH in one parabiotic mouse restored the survival of the Fth-deleted parabiotic mouse (Fthfl/flFthR26Δ/Δ; Fig. 1G), similar to control Fth-competent parabiotic pairs (Fthfl/flFthfl/fl), receiving TAM at the same dosage and schedule (Figs. 1G and EV1F). This suggests that Fth-competent hematopoietic-derived circulating cells and/or soluble factors generated in a mouse that expresses FTH are sufficient to rescue the lethal outcome of systemic Fth deletion.

The protective effect of Fth-competent circulating cells was contingent on the expression of FTH in myeloid cells, as revealed by the lethal outcome of Fth deletion in FthLysMΔ/ΔFthR26Δ/Δ parabiotic pairs (Fig. 1G and EV1F). This suggests that circulating Fth-competent myeloid cells, which include circulating monocytes, are required to prevent the lethal outcome of systemic Fth deletion, in the absence of lethal irradiation and/or hematopoietic cell reconstitution.

Fth-competent BM-derived monocytes (BMDM) rescue chimeric Fth-deleted mice

To prove unequivocally that Fth-competent monocytes carry the capacity to rescue the lethal outcome of global Fth deletion we generated BM-derived monocytes (BMDM) in vitro and tested their protective effect upon adoptive transfer into adult Fth-deleted FthR26Δ/Δ mice. To trace BMDM, we added a Rosa26-tandem dimer (td) Tomato-Flox-stop-Flox allele driving the expression of td Tomato (tdT) by Cre-driven excision, under the control of Rosa26 promoter (tdTR26 mice). Adoptive transfer of Fth-competent tdT+ BMDM (generated from tdTR26 mice) was sufficient to extend the lifespan of Fth-deleted FthR26Δ/Δ mice (Fig. 1H,I). In contrast, Adoptive transfer of Fth-deleted tdT+ BMDM (generated from tdTR26FthR26Δ/Δ mice) failed to extend the lifespan of Fth-deleted FthR26Δ/Δ mice (Fig. 1H,I). All recipient Fth-deleted FthR26Δ/Δ mice succumbed within 1–2 days after the last BMDM adoptive transfer, suggesting that long-term survival of FthR26Δ/Δ mice is dependent on continuous supply of circulating monocytes, presumably via myelopoiesis.

FTH supports the capacity of BMDM to give rise to tissue macrophages

The number of Fth-deleted tdT+ cells recovered from the liver and spleen of recipient Fth-deleted (FthR26Δ/Δ) mice, 24 h after adoptive transfer of tdT+ BMDM, was markedly lower, as compared to Fth-competent tdT+ cells (Fig. 1H,J). This indicates that Fth-deleted BMDM have an impaired capacity to migrate and/or differentiate into tissue-resident macrophages. Moreover, recovery of FTH-competent tdT+ BMDM from the liver, but not the spleen, of recipient FTH-deleted (FthR26Δ/Δ) was higher than in control (Fthfl/fl) recipient mice (Fig. 1H,J). This suggests that FTH-deficient organs (e.g., liver) have an increased capacity to recruit, and/or retain, monocyte-derived macrophages upon the stress imposed by FTH deletion.

To gain further insight into the differentiation of tdT+ BMDM after adoptive transfer, we performed a t-SNE (t-distributed Stochastic Neighbor Embedding) analysis based on CX3CR1, LY6C, F4/80 and CD11B expression, prior to, and 24 h after BMDM transfer (Fig. 1H,K). The t-SNE profile of tdT+ BMDM before and after adoptive transfer was distinct, as assessed in liver of recipient mice (Fig. 1H,K,L). There was heterogeneity in CX3CR1, LY6C, F4/80 and CD11B expression with a sub-population of cells increasing Ly6C and decreasing CX3CR1 and F4/80 expression, while maintaining CD11b and tdT expression (Fig. 1H,K,L). This suggests that upon adoptive transfer, tdT+ BMDM differentiate into distinct tissue-specific monocyte-derived macrophage subpopulations.

Fth-deleted and Fth-competent BMDM tdT+ cells from the liver of recipient Fth-deleted (FthR26Δ/Δ) mice presented similar t-SNE profiles (Fig. 1H,K,L). There was also no discernable difference in the t-SNE profiles of Fth-competent tdT+ cells from the liver of Fth-deleted (FthR26Δ/Δ) vs. control (Fthfl/fl) mice (Fig. 1H,K,L). This suggests that FTH does not regulate the initial capacity of BMDM to differentiate into monocyte-derived tissue macrophages.

Fth-competent myeloid cells restore Fe homeostasis in chimeric Fth-deleted mice

The lethal outcome of global Fth deletion was associated with systemic dysregulation of Fe metabolism, as illustrated by reduced circulating transferrin and higher transferrin saturation in Fth-deleted FthR26Δ/ΔFthR26Δ/Δ vs. Fth-competent Fthwt/wtFthfl/fl chimeras (Fig. 2A–C). Fth-competent hematopoietic cells restored the levels of circulating transferrin and normalized transferrin saturation (Fig. 2A–C) in plasma from Fthfl/flFthR26Δ/Δ chimeras to levels in the range of those in control Fth competent Fthfl/flFthfl/fl chimeras (Fig. 2A–C). This was not the case however, when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras, which presented a decrease in the levels of circulating transferrin and an increase in transferrin saturation (Fig. 2A–C), as compared to Fth competent Fthfl/flFthfl/fl chimeras (Fig. 2C). This was associated, over time, with an increase in the concentration of circulating Fe in both FthLysMΔ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeras (Fig. 2D,E), suggesting that, over time, Fth-competent monocyte-derived macrophages do not prevent the accumulation of circulating redox-active Fe imposed by global Fth deletion, and that this increase in circulatory Fe is independent from Fth deletion-induced lethality.

Figure 2. Fth-competent myeloid cells restore Fe homeostasis, prevent oxidative stress and restore cardiac function in chimeric Fth-deleted mice.

Figure 2

(A) Schematic representation of chimeric mice and TAM-induced Fth deletion (day 0). (B) Plasma transferrin concentration and (C) transferrin saturation in Fthfl/flFthfl/fl (n = 10–14), FthR26Δ/ΔFthR26Δ/Δ (n = 10–11), Fthfl/flFthR26Δ/Δ (n = 11–13) and FthLysMΔ/ΔFthR26Δ/Δ (n = 23) chimeric mice on days 7–15 (early onset), or 19–35 (late onset) following TAM administration. Data in (B, C) pooled from 6 independent experiments with similar trends. (D) Schematic representation of chimeric mice and TAM-induced Fth deletion. Iron levels in (E) plasma measured in Fthfl/flFthfl/fl (n = 11–13), FthR26Δ/ΔFthR26Δ/Δ (n = 9), Fthfl/flFthR26Δ/Δ (n = 11–13) and FthLysMΔ/ΔFthR26Δ/Δ (n = 23) chimeric mice on days 7–15 (early onset), or 19–35 (late onset) following TAM administration and (F) liver measured in Fthfl/flFthfl/fl (n = 3–5), FthR26Δ/ΔFthR26Δ/Δ (n = 8), Fthfl/flFthR26Δ/Δ (n = 3–5) and FthLysMΔ/ΔFthR26Δ/Δ (n = 7) chimeric mice on day 7 (early onset), or 22 (late onset) following TAM administration. Data in (E, F) pooled from three independent experiments with similar trends. (G) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0). Representative luminescence images depicting oxidative stress, as monitored by OKD48Luc reporter luciferase luminescence, in Fthfl/flOKD48LucFthfl/fl (n = 7–11), FthR26Δ/ΔOKD48LucFthR26Δ/Δ (n = 5), Fthfl/flOKD48LucFthR26Δ/Δ (n = 7-9) and FthLysMΔ/ΔOKD48LucFthR26Δ/Δ (n = 6) chimeric mice on days 7 (G; early onset) or 19 (H; late onset) following TAM administration. Data in (G, H) presented as individual values (circles) and mean (red bars), pooled from six independent experiments with similar trends. (I) Schematic representation of chimeric mice and TAM-induced Fth deletion (day 0) and cardiac iron content (right) in Fthfl/flFthfl/fl (n = 3–5), Fthfl/flFthR26Δ/Δ (n = 3–5) and FthLysMΔ/ΔFthR26Δ/Δ (n = 6–7). (J) Schematic representation of chimeric mice and TAM-induced Fth deletion (day 0) and cardiac function parameters (heart rate; mean arterial pressure) in Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 5) and FthLysMΔ/ΔFthR26Δ/Δ (n = 8) chimeric mice between days 10 and 51 following TAM administration. Data in (J) presented as individual values (circles) and mean (red bars), pooled from two independent experiments with similar trends. Data in (B, C, E, FI) represented as individual values (circles) and mean (red bars), one-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. Data in (J) represented as individual values (circles) and mean (red bars), Welch ANOVA with Dunnett’s T3 test for multiple comparison correction was used for comparison between control and test groups NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Source data are available online for this figure.

Systemic Fth deletion was associated with a decrease of hepatic Fe content, not restored by Fth-competent hematopoietic cells in Fthfl/flFthR26Δ/Δ nor FthLysMΔ/ΔFthR26Δ/Δ chimeras, compared to control Fth-competent Fthwt/wtFthfl/fl chimeras (Fig. 2F). Moreover, systemic Fth deletion was associated with the appearance of electron-dense crystalline inclusions in both the liver (Appendix Fig. S2A) and WAT (Appendix Fig. S2B), from Fth-deleted FthR26Δ/ΔFthR26Δ/Δ and FthLysMΔ/ΔFthR26Δ/Δ chimeras. This is consistent with the formation of hemosiderin Fe deposits formed by a single membrane-bound lysosomal body, likely due to the loss of iron storage capacity imposed by Fth deletion (Fig. 2F). These siderosome-like structures were not observed in the liver (Appendix Fig. S2A) nor the WAT (Appendix Fig. S2B) from Fthfl/flFthR26Δ/Δ chimeras, similar to control Fthfl/flFthfl/fl chimeras. These observations suggest that Fth-competent monocyte-derived macrophages prevent the formation of hemosiderin Fe deposits associated with systemic loss of Fe storage capacity due to Fth deletion.

Fth-competent myeloid cells restore redox homeostasis in chimeric Fth-deleted mice

Using OKD48Luc reporter mice, expressing a luciferase reporter ubiquitously to monitor oxidative stress in vivo (Oikawa et al, 2012), we confirmed that global Fth deletion led to systemic oxidative stress in FthR26Δ/ΔOKD48LucFthR26Δ/Δ chimeras (i.e., OKD48LucFthR26fl/fl mice reconstituted with BM from FthR26fl/fl mice) (Fig. 2G), consistent with described in adult FthR26Δ/Δ mice (Blankenhaus et al, 2019). Fth-competent hematopoietic cells restored systemic redox balance in Fthfl/flOKD48LucFthR26Δ/Δ chimeras (Fig. 2G,H). This was no longer the case however, when Fth was deleted in myeloid cells (Fig. 2H), as assessed at a later point (i.e., late onset) in FthLysMΔ/ΔOKD48LucFthR26Δ/Δ chimeras (Fig. 2H). This suggests that Fth-competent monocyte-derived macrophages are essential to prevent the development of tissue oxidative stress imposed by systemic Fth deletion.

Fth-competent myeloid cells support tissue function in chimeric Fth-deleted mice

Global Fth deletion was associated with the development of multiorgan damage, as illustrated serologically by the accumulation of alanine aminotransferase (ALT; liver damage) (Fig. EV2A,B), aspartate aminotransferase (AST; liver damage) (Fig. EV2A,C), lactate dehydrogenase (LDH) (Fig. EV2A,D), creatinine phosphokinase (CPK; muscle damage) (Fig. EV2A,E) and urea (kidney damage) (Fig. EV2A,F) in the plasma of FthR26Δ/ΔFthR26Δ/Δ chimeras vs. control Fth-competent Fthfl/f/Fthwt/wtFthfl/fl chimeras. Multiorgan damage was confirmed histologically, as illustrated in the liver (i.e., hepatocellular vacuolar degeneration) and in the kidneys (i.e., acute tubular cell necrosis) (Fig. EV2A,G,H).

Figure EV2. Fth-competent myeloid cells support tissue function in chimeric Fth-deleted mice.

Figure EV2

(A) Schematic representation of chimeric mice and TAM-induced Fth deletion. Plasma levels of (B) alanine transaminase (ALT), (C) aspartate transaminase (AST), (D) lactate dehydrogenase (LDH), (E) creatine phosphokinase (CPK) and (F) urea, measured in Fthfl/flFthfl/fl (n = 11–21), FthR26Δ/ΔFthR26Δ/Δ (n = 15–25), Fthfl/flFthR26Δ/Δ (n = 9–18) and FthLysMΔ/ΔFthR26Δ/Δ (n = 11–20) chimeric mice on days 7–15 (early onset), or 19–35 (late onset) following TAM administration. Data in (BF) represented as individual values (circles) and mean (red bars) pooled from 4 to 6 independent experiments with similar trends. (G, H) Representative hematoxylin and eosin (H&E) stained histology images of liver, kidney and heart from Fthfl/flFthfl/fl, FthR26Δ/ΔFthR26Δ/Δ, Fthfl/flFthR26Δ/Δ and FthLysMΔ/ΔFthR26Δ/Δ chimeric mice on day 7 (early onset) (G), or 22 (late onset) (H) following TAM administration. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Fth-competent hematopoietic cells prevented multiorgan damage in Fthfl/flFthR26Δ chimeras (Fig. EV2A,G). This was no longer observed however, when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras, which showed hepatocellular hypertrophic lesions with granular acidophilic cytoplasm, hinting at possible liver mitochondrial dysfunction (Fig. EV2A,H). This suggests that Fth-competent monocyte-derived macrophages are essential to prevent multiorgan damage imposed by systemic Fth deletion.

Fth-deleted mice succumb to life-threatening cardiac dysfunction

FTH is highly expressed in the heart (Munro and Linder, 1978) and Fth deletion in cardiac myocytes leads to cardiac dysfunction (Fang et al, 2020), suggesting that FthR26Δ/Δ mice develop cardiac dysfunction. However, global Fth deletion was not associated with the development of acute cardiac damage, as illustrated by troponin I accumulation in plasma from FthR26Δ/ΔFthR26Δ/Δ vs. control Fthfl/flFthfl/fl chimeras (Fig. EV2I) and confirmed histologically (Fig. EV2J). Nevertheless, global Fth deletion in FthR26Δ/Δ mice led to a profound reduction of heart rate, end-systolic pressure (ESP) and preload recruitable stroke work (PRSW), compared to control R26Cre or Fthfl/fl mice (Appendix Fig. S3A–C). A number of other cardiac function parameters, including cardiac mechanical power (MaxPwr) with ensuing reduction of mean arterial pressure, cardiac output, stroke work, pressure-volume area and peak systolic pressure (Pmax) were also severely impaired in FthR26Δ/Δ vs. control R26Cre or Fthfl/fl mice (Appendix Fig. S3A–C). This suggests that FTH is essential to sustain heart function and blood circulation.

Fth-competent myeloid cells support cardiac function in chimeric Fth-deleted mice

Systemic Fth deletion did not impact on cardiac Fe content in FthR26Δ/ΔFthR26Δ/Δ vs. control Fthfl/flFthfl/fl chimeras (Appendix Fig. S3D). In contrast however, myeloid Fth deletion led to a marked decrease in cardiac Fe content in FthLysMΔ/ΔFthR26Δ/Δ chimeras, at a later time point, compared to control Fthfl/flFthfl/fl chimeras (Fig. 2I). This was prevented by Fth competent hematopoietic cells in Fthfl/flFthR26Δ/Δ chimeras (Fig. 2I), suggesting that over time, Fth-competent myeloid cells become essential to control the cardiac Fe content of chimeric mice in which Fth is deleted globally.

We then asked whether macrophages prevent the development of life-threatening cardiac dysfunction imposed by systemic Fth deletion. Similar to observed upon Fth deletion in adult FthR26Δ/Δ mice (Appendix Fig. S3A–C), global Fth deletion in FthR26Δ/ΔFthR26Δ/Δ chimeric mice led to the development of life-threatening cardiac dysfunction, revealed by a profound reduction of heart rate and mean arterial pressure (Fig. 2J) as well as ESP, PRSW, and MaxPwr (Appendix Fig. S3E), compared to control Fthfl/f/Fthwt/wtlFthfl/fl chimeras (Fig. 2J; Appendix Fig. S3E). Fth-competent hematopoietic cells prevented the development of life-threatening cardiac dysfunction in Fth-deleted Fthfl/flFthR26Δ chimeras (Fig. 2J; Appendix Fig. S3E). This suggests that Fth-competent hematopoietic cells carry the capacity to prevent the development of life-threatening cardiac dysfunction imposed by systemic Fth deletion.

Fth-deletion in the myeloid compartment of FthLysMΔ/ΔFthR26Δ/Δ chimeras was associated with the development of life-threatening cardiac dysfunction (Fig. 2J; Appendix Fig. S3E). This suggests that Fth-competent myeloid cells, including monocyte-derived macrophages, are essential to prevent the development of life-threatening cardiac dysfunction imposed by systemic Fth deletion. This is consistent with monocyte-derived macrophages promoting cardiac function under steady state conditions (Hulsmans et al, 2017) or in response to ischemic damage (Swirski et al, 2009).

Fth-competent myeloid cells support energy metabolism in chimeric Fth-deleted mice

Cardiac function is a highly energy demanding process, entertaining the hypothesis that Fth-competent monocyte-derived macrophages support cardiac function, indirectly, via a mechanism that sustains organismal energy expenditure. In support of this hypothesis, global Fth deletion led to a collapse of energy expenditure (EE) in FthR26Δ/ΔFthR26Δ/Δ chimeras (Fig. 3A,B), similar to observed FthR26Δ/Δ mice (Blankenhaus et al, 2019). Fth-competent hematopoietic cells rescued EE in Fthfl/flFthR26Δ/Δ chimeras (Fig. 3A,B) while Fth-deletion in myeloid cells compromised the capacity of hematopoietic cells to rescue EE in FthLysMΔ/ΔFthR26Δ/Δ chimeras (Fig. 3A,C).

Figure 3. Fth-competent myeloid cells support energy metabolism in chimeric Fth-deleted mice.

Figure 3

(A) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0). (B, C) Time course and mean of energy expenditure (EE) during day/night time in Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 5–6) and FthLysMΔ/ΔFthR26Δ/Δ (n = 4) chimeric mice, assessed from day 7 (B; early onset), or day 20 (C; late onset) post-TAM administration. (D, E) Time course and mean of (D) O2 consumption rate (VO2) and (E) CO2 production rate (VCO2) during day/nighttime in Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5) and Fthfl/flFthR26Δ/Δ (n = 5–6) chimeric mice, assessed from day 7 (early onset). Time course and mean of (F) O2 consumption rate (VO2) and (G) CO2 production rate (VCO2) during day/nighttime in Fthfl/flFthfl/fl (n = 4), FthLysMΔ/ΔFthR26Δ/Δ (n = 4) and Fthfl/flFthR26Δ/Δ (n = 5–6) chimeric mice, assessed from day 20 (late onset). Data in (BG) is displayed as mean ± SD (time course), or as individual values (circles) and mean (red bars) (dot plots). Data in (BG) is pooled from two independent experiments with similar trends. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, **P < 0.01, ***P < 0.001, ****P < 0.0001. Source data are available online for this figure.

Systemic Fth deletion reduced consumed O2 (VO2) (Fig. 3D) and exhaled CO2 (VCO2) to the same extent (Fig. 3E) and therefore did not reflect on respiratory quotient (RQ), (Appendix Fig. S2A–C). Fth-competent hematopoietic cells restored VO2 and VCO2 in Fthfl/flFthR26Δ/Δ chimeras (Fig. 3D,E) while Fth-deleted myeloid cells failed to do so in FthLysMΔ/ΔFthR26Δ/Δ chimeras (Fig. 3F,G).

Global Fth deletion in chimeric mice was associated with the suppression of locomotor activity (Fig. EV3D) and food intake (Fig. EV3E). Fth-competent hematopoietic cells restored locomotor activity (Fig. EV3D) and food intake (Fig. EV3E) in Fthfl/flFthR26Δ/Δ chimeras (Fig. EV3D,E). This was no longer observed upon Fth-deletion in myeloid cells (Fig. EV3F,G).

Figure EV3. Fth-competent myeloid cells restore movement and food intake in chimeric Fth-deleted mice.

Figure EV3

(A) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0) and metabolic cage assessment of metabolic parameters. (B, C) Time course of respiratory quotient (RQ, calculated as VO2/VCO2), and mean (red bars) RQ during daytime/nighttime (dot plots) of Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 5–6) and FthLysMΔ/ΔFthR26Δ/Δ (n = 4) chimeric mice, assessed from day 7 (B; early onset), or day 20 (C; late onset) post TAM administration. Time course and mean (red bars) of daytime/nighttime values (dot plots) for mouse movement (m/h; D), and rate of food intake (g/h; E) of Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5) and Fthfl/flFthR26Δ/Δ (n = 6) chimeric mice, assessed from day 7 (early onset). Time course and mean (red bars) of daytime/nighttime values (dot plots) for mouse movement (m/h; F), and rate of food intake (g/h; G) of Fthfl/flFthfl/fl (n = 4), FthLysMΔ/ΔFthR26Δ/Δ (n = 4) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, assessed from day 20 (late onset). Data in (BG) is displayed as mean ± SD (time course), or as individual values (circles) and mean (red bars) (dot plots). Data in (BG) is pooled from 2 independent experiments with similar trend. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, ***P < 0.001, ****P < 0.0001.

These observations suggest that Fth-competent monocyte-derived macrophages are essential to restore energy metabolism under Fth deletion in parenchyma cells. This salutary effect is associated with a regain of locomotor activity and food intake (Fig. EV3F,G).

Fth-competent myeloid cells support BAT thermogenesis in chimeric Fth-deleted mice

Mice allocate up to one-third of their EE to support core body temperature, under standard husbandry conditions (~ 22 °C) (Ganeshan and Chawla, 2017; Ganeshan et al, 2019; Reitman, 2018). This is achieved, to a large extent, via brown adipose tissue (BAT) thermogenesis (Cannon and Nedergaard, 2004; Lowell et al, 1993), entertaining the hypothesis that Fth-competent monocyte-derived macrophages sustain BAT thermogenesis in chimeric mice. In support of this hypothesis, global Fth deletion compromised BAT thermogenesis (Fig. 4A,B) and caused BAT wasting (Fig. EV4A,B) in FthR26Δ/ΔFthR26Δ/Δ chimeras. Fth-competent hematopoietic cells restored BAT thermogenesis in Fthfl/flFthR26Δ/Δ chimeras (Fig. 4A,B): This was no longer the case when Fth was deleted in myeloid cells (Fig. 4C,D), with a tendency for BAT wasting and reduction in average lipid droplet at a later time point (Fig. EV4C,D), albeit not significant. This suggests that Fth-competent myeloid cells, including monocyte-derived macrophages, prevent the collapse of BAT thermogenesis and thermoregulation imposed by systemic Fth deletion.

Figure 4. Fth-competent myeloid cells support adipose tissue function in chimeric Fth-deleted mice.

Figure 4

(A) Schematic representation of chimeric mice and TAM-induced Fth deletion (day 0) with corresponding representative infrared thermal images (FLIR) of Fthfl/flFthfl/fl, FthR26Δ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, on day 7 (early onset) post-TAM administration. (B) BAT (left) and tail (center) temperatures extracted from thermal images, and temperature delta (right; core body temperature – tail temperature) of Fthfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post-TAM administration. (C) Schematic representation of chimeric mice and TAM-induced Fth deletion (day 0) with corresponding representative (FLIR) of Fthfl/flFthfl/fl, FthLysMΔ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, collected between days 16-39 (late onset) post TAM administration using an infrared thermal imaging camera (FLIR). (D) BAT (left) and tail (center) temperatures extracted from thermal images, and temperature delta (right; core body temperature – tail temperature) of Fthfl/flFthfl/fl (n = 7), FthLysMΔ/ΔFthR26Δ/Δ (n = 7) and Fthfl/flFthR26Δ/Δ (n = 3) chimeric mice, collected between days 16-39 (late onset) post TAM administration. Data in (B, D) represented as individual values (circles) and mean (red bars). Data in (AD) is pooled from three independent experiments with similar trends. (E) Schematic representation of chimeric mice and TAM-induced Fth deletion, with corresponding representative macroscopic and histological images of gonadal white adipose tissue pads (gWAT) in Fthfl/flFthfl/fl, FthR26Δ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, collected on day 7 (early onset) post TAM administration. (F) gWAT weight (left) and mean (red bars) adipocyte area (right) in Fthfl/flFthfl/fl (n = 4–5), FthR26Δ/ΔFthR26Δ/Δ (n = 7–8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post TAM administration. (G) Schematic representation of chimeric mice and TAM-induced Fth deletion, with corresponding representative macroscopic and histological images of gonadal white adipose tissue pads (gWAT) in Fthfl/flFthfl/fl, FthLysMΔ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, collected between days 16-39 (late onset) post-TAM administration. (H) gWAT pad weight (left) and mean (red bars) adipocyte area (right) of Fthfl/flFthfl/fl (n = 3–4), FthLysMΔ/ΔFthR26Δ/Δ (n = 7) and Fthfl/flFthR26Δ/Δ (n = 3) chimeric mice, collected between days 16 and 39 (late onset) post-TAM administration. Data in (F, H) represented as individual values (circles) and mean (red bars). Data in (EH) is pooled from three independent experiments with similar trends. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Source data are available online for this figure.

Figure EV4. Fth-competent myeloid cells support BAT and WAT function in chimeric Fth-deleted mice.

Figure EV4

(A) Schematic representation of chimeric mice and TAM-induced Fth deletion, and representative macroscopic and histological images of brown adipose tissue pads (BAT) of Fthfl/flFthfl/fl (n = 5), FthR26Δ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post TAM administration. (B) BAT pad weight (left) and mean (red bars) BAT adipocyte lipid droplet area (right) of Fthfl/flFthfl/fl (n = 5), FthR26Δ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post TAM administration. (C) Schematic representation of chimeric mice and TAM-induced Fth deletion, and representative macroscopic and histological images of BAT of Fthfl/flFthfl/fl (n = 3–4), FthLysMΔ/ΔFthR26Δ/Δ (n = 6) and Fthfl/flFthR26Δ/Δ (n = 3–4) chimeric mice, collected between days 16 and 39 (late onset) post TAM administration. (D) BAT pad weight (left) and mean (red bars) BAT adipocyte lipid droplet area (right) of Fthfl/flFthfl/fl (n = 3–4), FthLysMΔ/ΔFthR26Δ/Δ (n = 6) and Fthfl/flFthR26Δ/Δ (n = 3–4) chimeric mice, collected between days 16 and 39 (late onset) post TAM administration. Data in (B, D) represented as individual values (circles) and mean (red bars), pooled from three independent experiments with similar trends. (E) Schematic representation of chimeric mice and TAM-induced Fth deletion, and representative macroscopic and histological images of inguinal white adipose tissue pads (iWAT) of Fthfl/flFthfl/fl (n = 4–5), FthR26Δ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post TAM administration. (F) iWAT pad weight (left) and mean (red bars) iWAT adipocyte area (right) of Fthfl/flFthfl/fl (n = 4–5), FthR26Δ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 5) chimeric mice, collected on day 7 (early onset) post TAM administration. (G) Schematic representation of chimeric mice and TAM-induced Fth deletion, and representative macroscopic and histological images of iWAT of Fthfl/flFthfl/fl (n = 3–4), FthLysMΔ/ΔFthR26Δ/Δ (n = 7) and Fthfl/flFthR26Δ/Δ (n = 3) chimeric mice, collected between days 16 and 39 (late onset) post TAM administration. (H) iWAT pad weight (left) and mean (red bars) iWAT adipocyte area (right) of Fthfl/flFthfl/fl (n = 3–4), FthLysMΔ/ΔFthR26Δ/Δ (n = 7) and Fthfl/flFthR26Δ/Δ (n = 3) chimeric mice, collected between days 16 and 39 (late onset) post TAM administration. Data in (F, H) represented as individual values (circles) and mean (red bars), pooled from 3 independent experiments with similar trends. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, *P < 0.05, **P < 0.01, ****P < 0.0001.

Fth-competent myeloid cells support WAT function in chimeric Fth-deleted mice

BAT thermogenesis is fueled via white adipose tissue (WAT) lipolysis (Heine et al, 2018), entertaining the hypothesis that Fth-competent monocyte-derived macrophages regulate WAT lipolysis. In keeping with this hypothesis, global Fth deletion led to visceral (i.e., gonadal) (Fig. 4E,F) and subcutaneous (i.e., inguinal) WAT wasting (Fig. EV4E,F), with reduction of lipid droplet (i.e., adipocyte) size in FthR26Δ/ΔFthR26Δ/Δ chimeras (Figs. 4E,F and  EV4E,F). While Fth-competent hematopoietic cells prevented WAT wasting in Fthfl/flFthR26Δ/Δ chimeras (Figs. 4E,F and  EV4E,F), WAT wasting was prominent when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras (Figs. 4G,H and  EV4G,H). This suggests that Fth-competent myeloid cells that give rise to monocyte-derived macrophages, carry the capacity to normalize WAT function and BAT thermogenesis in chimeric mice in which Fth is deleted globally.

Fth-competent myeloid cells partially restore ferritin expression in tissues from chimeric Fth-deleted mice

Macrophages secrete and transfer ferritin (Cohen et al, 2010; Meyron-Holtz et al, 2011), suggesting that FTH might be transferred from Fth-competent monocyte-derived macrophages to Fth-deficient bystander parenchyma cells. In keeping with this hypothesis, Fth-competent hematopoietic cells contribute with 30-40% of the relative level of FTH protein expression in heart, liver, lung and kidneys of Fthfl/flFthR26Δ/Δ chimeras, compared to control Fthfl/flFthfl/fl chimeras (Fig. 5A,B). In contrast, FTH protein expression was barely detectable when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras (Fig. 5A,B). This suggests that under global Fth deletion, Fth-competent monocyte-derived macrophages are essential to partially restore the level of FTH protein expression in different organs.

Figure 5. Fth-competent myeloid cells partially restore tissue ferritin expression but do not deliver ferritin to parenchyma cells in chimeric Fth-deleted mice.

Figure 5

(A) Schematic representation of TAM-induced Fth deletion in chimeric mice (day 0) and analysis of FTH protein expression (Western blot). (B) Relative quantification of FTH protein expression in heart, liver, lungs and kidneys from Fthfl/flFthfl/fl (n = 4), FthLysMΔ/ΔFthR26Δ/Δ (n = 4) and Fthfl/flFthR26Δ/Δ (n = 4) chimeric mice, between days 7 and 23 post-TAM administration. Data in (B) represented as the % of FTH expression relative to Fthfl/flFthfl/fl control chimeras and is pooled from 3 independent experiments. (C) Schematic representation of the CRISPR/Cas 9 editing strategy for V5-tagged FTH. (D) Detection of V5-tagged and endogenous FTH protein expression (Western blot) in control Fthwt/wt and edited FthV5/wt mice. (E) Schematic representation of TAM-induced Fth deletion (day 0) and survival of FthV5/V5Fthfl/fl (n = 13), FthR26Δ/ΔFthR26Δ/Δ (n = 6) and FthV5/V5FthR26Δ/Δ (n = 11) chimeric mice. Data in (E) is pooled from 4 independent experiments with similar trends. (F) Schematic representation of TAM-induced Fth deletion in chimeric mice, and representative images of FTH and V5 immunofluorescence detection in livers from FthV5/V5Fthfl/fl and FthV5/V5FthR26Δ/Δ chimeric mice. (G) Schematic representation of TAM-induced Fth deletion and representative images of CD68 (macrophages) and V5 immunofluorescence detection in livers from FthV5/V5Fthfl/fl and FthV5/V5FthR26Δ/Δ chimeric mice. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. Survival analysis was performed using Log-rank (Mantel–Cox) test. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Source data are available online for this figure.

Fth-competent myeloid cells do not deliver ferritin to parenchyma cells from chimeric Fth-deleted mice

To determine whether or not monocyte-derived macrophages transfer FTH to parenchyma cells we used a CRISPR/Cas 9 based approach (Jinek et al, 2012) to tag the N-terminus of FTH with a 14 amino-acid V5 peptide (FthV5/WT mouse) (Fig. 5C). Expression of V5-tagged FTH protein was validated in whole heart and kidney extracts from hemizygous FthV5/WT mice, by western blot (Fig. 5D).

Hematopoietic cells expressing V5-tagged FTH retained the capacity to rescue the lethal outcome of systemic Fth deletion in FthV5/V5FthR26Δ/Δ chimeras (i.e., FthR26fl/fl mice reconstituted with FthV5/V5 BM) (Fig. 5E). However, the expression of the V5-tagged FTH protein was restricted to CD68+ macrophages, without detectable transfer to parenchyma cells, as assessed by confocal microscopy in the liver of FthV5/V5FthR26Δ/Δ chimeras (Fig. 5F,G). This suggests that Fth-competent monocyte-derived macrophages rescue the lethal outcome of systemic Fth deletion, irrespective of ferritin transfer to Fth-deleted parenchyma cells.

Fth-competent myeloid cells rescue chimeric Fth-deleted mice irrespective of cellular Fe import/export

We hypothesized that Fth-competent macrophages rescue the lethal outcome of global Fth deletion via a mechanism that involves cellular Fe import and/or Fe export to or from Fth-deleted parenchyma cells, respectively. To test these hypothesis, we reconstituted FthR26fl/fl mice with BM cells from mice harboring a myeloid-specific deletion of the main cellular Fe importer transferrin receptor 1 (TfR1; encoded by Tfrc) (Fig. EV5A) or the cellular Fe exporter Ferroportin (FPN1; encoded by Slc40a1) (Fig. EV5B) (Wu et al, 2023). Slc40a1-deleted myeloid cells (Fig. EV5A) or Tfrc-deleted myeloid cells (Fig. EV5B) retained the capacity to rescue the lethal outcome of systemic Fth deletion in Slc40a1LysMΔ/ΔFthR26Δ/Δ or TfrcLysMΔ/ΔFthR26Δ/Δ chimeras, respectively (Fig. EV5). This shows that monocyte-derived macrophages rescue the lethal outcome of global Fth deletion, via a mechanism that does not rely on Fe transit between Fth-competent macrophages and Fth-deleted parenchyma cells.

Figure EV5. Myeloid cells rescue chimeric Fth-deleted mice irrespectively of cellular Fe import/export.

Figure EV5

(A) Schematic representation of TAM-induced Fth deletion in chimeric mice, and (B) survival of Tfrcfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Tfrcfl/flFthR26Δ/Δ (n = 8) and TfrcLysMΔ/ΔFthR26Δ/Δ (n = 7) chimeric mice following TAM administration. Data in (B) is pooled from 2 independent experiments with similar trends. (C) Schematic representation of TAM-induced Fth deletion in chimeric mice, and (D) survival of Fthfl/flFthfl/fl (n = 5), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Fthfl/flFthR26Δ/Δ (n = 5), and Slc40a1LysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice on day 0. (E) quantification of ETC subunits for complexes I-V in the livers of Fthfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 10) and Fthfl/flFthR26Δ/Δ (n = 7) chimeric mice, between days 7–8 (early onset), or from Fthfl/flFthfl/fl (n = 8), FthLysMΔ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 6) chimeric mice, between days 19 and 22 (late onset). Data in (E) is pooled from 4 independent experiments with similar trends. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. Survival analysis was performed using Log-rank (Mantel–Cox) test. NS: non-significant, *P < 0.05, **P < 0.01.

Fth-competent myeloid cells support the mitochondria of Fth-deleted parenchyma cells from chimeric Fth-deleted mice

Whole-body Fth deletion causes a severe disruption of mitochondria structure and function in parenchyma cells (Blankenhaus et al, 2019). This suggests that Fth-competent macrophages rescue the lethal outcome of parenchyma Fth deletion, via a mechanism that supports the mitochondria of Fth-deleted parenchyma cells. In contrast to Fth-deletion in adult FthR26Δ/Δ mice (Blankenhaus et al, 2019), Fth deletion in FthR26Δ/ΔFthR26Δ/Δ or FthLysMΔ/ΔFthR26Δ/Δ chimeras was not associated with a reduction of the number of mitochondria per cell, compared to control Fthfl/flFthfl/fl chimeras, as assessed in the heart, WAT and liver (Fig. 6A–C). However, the mitochondria morphology of parenchyma cells from FthR26Δ/ΔFthR26Δ/Δ chimeras was clearly disrupted, as reveled by swelling and irregular shape of mitochondrial cristae and reduced electron density of the mitochondrial matrix (Fig. 6D). Normal mitochondrial morphological features were restored in Fthfl/flFthR26Δ/Δ but not in FthLysMΔ/ΔFthR26Δ/Δ chimeras (Fig. 6D), suggesting that Fth-competent macrophages are essential to support the mitochondrial structure under systemic Fth deletion.

Figure 6. Fth-competent monocyte-derived macrophages support the mitochondria of parenchyma cells from Fth-deleted chimeric mice.

Figure 6

(A) Schematic representation of chimeric mice, TAM administration (day 0) and mitochondrial analysis. (B, C) Number of mitochondria per cell in liver, WAT and heart of (B) Fthfl/flFthfl/fl (n = 5–8), FthR26Δ/ΔFthR26Δ/Δ (n = 3–12) and Fthfl/flFthR26Δ/Δ (n = 3–9) chimeric mice, between days 7 and 9 (early onset) or (C) Fthfl/flFthfl/fl (n = 6–10), FthLysMΔ/ΔFthR26Δ/Δ (n = 2–8) and Fthfl/flFthR26Δ/Δ (n = 7–8) chimeric mice, on day 22–39 (late onset). Data in (B, C) represented as individual values (circles) and mean (red bars), assessed by quantitative PCR according to the ratio of nuclear (i.e., hexokinase 2; Hk2) and mitochondrial (i.e., NADH-ubiquinone oxidoreductase chain 1; mt-Nd1) DNA. (D) Representative transmission electron microscopy images of mitochondria structure in gWAT adipocytes and liver hepatocytes from Fthfl/flFthfl/fl, FthR26Δ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, on day 8 (early onset), or from Fthfl/flFthfl/fl, FthLysMΔ/ΔFthR26Δ/Δ and Fthfl/flFthR26Δ/Δ chimeric mice, on day 30 (late onset). Red arrows indicate swollen cristae, purple arrows indicate disrupted mitochondrial membranes, blue arrows indicate loss of mitochondrial membrane potential, as suggested by decreased electron density. (E) Schematic representation of chimeric mice, TAM administration (day 0) and qRT-PCR assessment. (F, G) Log2 fold change (FC) in expression of mitochondrial genes or genes involved in regulation of mitochondria in livers from (F) Fthfl/flFthfl/fl (n = 5), FthR26Δ/ΔFthR26Δ/Δ (n = 9) and Fthfl/flFthR26Δ/Δ (n = 6) chimeric mice, between days 7 and 8 (early onset), or from (G) Fthfl/flFthfl/fl (n = 9), FthLysMΔ/ΔFthR26Δ/Δ (n = 4) and Fthfl/flFthR26Δ/Δ (n = 7) chimeric mice, between days 19 and 22 (late onset). Data in (F, G) is pooled from three independent experiments with similar trend and represented as individual values (circles) and mean (red bars), normalized to housekeeping gene expression (acidic ribosomal phosphoprotein P0, Arbp0) and to gene expression values of control Fthfl/flFthfl/fl chimeric mice. (H) Schematic representation of chimeric mice, TAM administration (day 0) and western blot assessment. (I) Representative Western blot and (J) quantification of ETC subunits for complexes I-V in the livers of Fthfl/flFthfl/fl (n = 7), FthR26Δ/ΔFthR26Δ/Δ (n = 10) and Fthfl/flFthR26Δ/Δ (n = 7) chimeric mice, between days 7 and 8 (early onset), or from Fthfl/flFthfl/fl (n = 8), FthLysMΔ/ΔFthR26Δ/Δ (n = 8) and Fthfl/flFthR26Δ/Δ (n = 6) chimeric mice, between days 19 and 22 (late onset). Data in (J) is pooled from 4 independent experiments with similar trends. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. Two-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups within multiple genes. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001. Source data are available online for this figure.

Fth-competent myeloid cells restore mitochondria gene expression in chimeric Fth-deleted mice

Global Fth deletion in FthR26Δ/ΔFthR26Δ/Δ chimeras was associated with a reduction of the relative level of expression of hepatic mitochondrial mRNA, encoded by mitochondrial (i.e., MT-Co1: ETC complex IV Cytochrome C oxidase I, MT-Cyb: ETC complex III cytochrome B; MT-PolG: Mitochondrial DNA polymerase) or nuclear (Cs: Citrate synthase; Nrf1: Nuclear respiratory factor 1) genes, as compared to control Fthfl/flFthfl/fl chimeras (Fig. 6E,F). Fth-competent hematopoietic cells restored the expression of these hepatic mitochondrial mRNAs in Fthfl/flFthR26Δ chimeras (Fig. 6E,F). This was no longer the case when Fth was deleted in myeloid cells from FthLysMΔ/ΔFthR26Δ/Δ chimeras (Fig. 6E,G).

Systemic Fth deletion was also associated with reduction of the relative level of a subset of mitochondrial ETC proteins, as assessed in the liver of FthR26Δ/ΔFthR26Δ/Δ vs. control Fthfl/flFthfl/fl chimeras (Figs. 6H–J and  EV5E). Fth-competent hematopoietic cells restored the expression of these mitochondrial ETC proteins (Figs. 6H–J and  EV5E), while deletion of Fth in myeloid cells compromised this rescuing effect (Figs. 6H–J and  EV5E). These observations suggest that Fth-competent monocyte-derived macrophages engage in an intercellular crosstalk that supports the mitochondria of Fth-deficient parenchyma cells.

Mitochondrial biogenesis is a hallmark of rescuing macrophages

To explore the mechanism via which Fth-competent monocyte-derived macrophages restore the mitochondria of Fth-deficient chimeric mice, we generated tdTLysM mice expressing tdT under the control of the LysM promoter. These were crossed with Fthfl/fl mice, to generate tdTLysMFthLysMΔ/Δ mice, deleting Fth specifically in tdT+ myeloid cells (Fig. EV6A–C).

Figure EV6. RNA sequencing analysis of monocyte/macrophages in chimeric Fth-deleted mice.

Figure EV6

(A) Schematic representation of chimeric mice, TAM administration and fluorescence-activated cell sorting (FACS) of LysM+ monocyte/macrophages (CD45+,CD11b+,Ly6G,CD19,TCRβ) in liver, heart and WAT. (B) Survival of tdTLysMFthfl/fl (n = 4), tdTLysMFthR26Δ/Δ (n = 3), tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) and FthR26Δ/ΔFthR26Δ/Δ (n = 4) chimeric mice until organ collection on day 19 post-TAM administration. (C) Gating strategy for sorting LysM+ monocyte/macrophages (CD45+, CD11b+, Ly6G, CD19, TCRβ) in liver, WAT and Heart. (D) Proportion and number and of viable LysM+ monocyte/macrophages (CD45+, CD11b+, Ly6G, CD19, TCRβ) in the liver, gWAT and heart of tdTLysMFthfl/fl (n = 4), tdTLysMFthR26Δ/Δ (n = 3) and tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice on day 19 post-TAM administration. (E) Schematic representation of chimeric mice, TAM administration and fluorescence-activated cell sorting (FACS) of LysM+ monocyte/macrophages (CD45+, CD11b+, Ly6G, CD19, TCRβ) in liver and WAT. (F) Volcano plots of differentially regulated genes between LysM+ monocyte/macrophages sorted from liver (left) or WAT (right) of tdTLysMFthR26Δ/Δ (n = 3), tdTLysMFthfl/fl (n = 4) chimeric mice, on day 19 post TAM administration. Red dots depict mitochondrial genes that are significantly differentially regulated. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. Survival analysis was performed using Log-rank (Mantel–Cox) test. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001.

There was a marked reduction in the relative proportion and number of viable monocytes/macrophages in the liver WAT and heart from chimeric mice reconstituted with tdT+ Fth-deleted myeloid cells (i.e., FthR26fl/fl mice reconstituted with tdTLysMFthLysMΔ/Δ BM; tdTLysMFthLysMΔ/ΔFthR26Δ/Δ chimeras), compared to control chimeras (i.e., Fthfl/fl mice reconstituted with tdTLysM BM; tdTLysMFthfl/fl) (Fig. EV6A,C,D). This was not observed in chimeric mice reconstituted with Fth-competent hematopoietic cells (i.e., FthR26fl/fl mice reconstituted with tdTLysM BM; tdTLysMFthR26Δ/Δ) (Fig. EV6A,C,D).

To characterize the transcriptional response of rescuing monocyte-derived macrophages, tdT+ (CD45+CD11b+Ly6GCD19TCRβ) monocytes/macrophages were FACS-sorted from the liver and WAT of chimeric mice (Fig. EV6A,C). Analyses of RNA sequencing (RNAseq) revealed a marked upregulation of a large swath of mitochondrial genes in Fth-competent vs. Fth-deleted macrophages from tdTLysMFthR26Δ/Δ vs. tdTLysMFthLysMΔ/ΔFthR26Δ/Δ chimeras, respectively (Figs. 7A,B and  EV6E,F). Gene ontology enrichment showed a wide range of terms directly related to mitochondria (Fig. 7C), suggesting that Fth is strictly required to support this transcriptional response.

Figure 7. Fth-competent monocyte-derived macrophages deploy a mitochondrial gene transcriptional program.

Figure 7

(A) Schematic representation of chimeric mice, TAM administration and fluorescence-activated cell sorting (FACS) of LysM+ monocyte/macrophages (CD45+,CD11b+,Ly6G,CD19,TCRβ) in liver and WAT. (B) Volcano plots of differentially regulated genes between LysM+ monocyte/macrophages sorted from liver (left) or WAT (right) of tdTLysMFthR26Δ/Δ (n = 3), tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice, on day 19 post-TAM administration. Red dots depict mitochondrial genes that are significantly differentially regulated. (C) Gene ontology analysis depicting ontologies that are significantly enriched comparing LysM+ monocyte/macrophages sorted from liver (left) and WAT (right) from tdTLysMFthR26Δ/Δ (n = 3) and tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice on day 19 post-TAM administration. Ontologies significantly enriched in LysM+ monocyte/macrophages from tdTLysMFthR26Δ/Δ are depicted as: enrichment score −log10 P value > 1.301. Ontologies significantly enriched in LysM+ monocyte/macrophages from tdTLysMFthLysMΔ/ΔFthR26Δ/Δ are depicted as: enrichment score −log10 P value < −1.301. Ontology classes: TF = transcription factors; GO:CC = gene ontology : cellular component; GO:MF = GO : molecular function; GO:BP = GO : biological process; KEGG = Kyoto Encyclopedia of Genes and Genomes pathway; REAC = reactome. (D) Heatmap of mean Log2 FC (over control; tdTLysMFthfl/fl) in gene expression of genes involved in mitochondrial function and regulation, in LysM+ monocyte/macrophages sorted from the liver (top) and WAT (bottom) of tdTLysMFthfl/fl (n = 3), tdTLysMFthR26Δ/Δ (n = 3) and tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice on day 19 post-TAM administration. (E) Schematic representation of chimeric mice, TAM administration and flow cytometry analysis of PhAM reporter-expressing mitochondria in LysM+ cells. Representative histograms of PhAM fluorescence intensity, mean fluorescence intensity (MFI) of PhAM, and percentage of PhAM+ cells in LY6Chigh monocytes from the liver (F) and WAT (G) of PhAMLysMFthfl/fl (n = 2–3) and PhAMLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 2–3) chimeric mice, collected on day 100 post-TAM administration. Data in (F, G) dot plots represented as individual values (circles) and mean (red bars). Student’s t test was used for comparison between two groups. NS non-significant, *P < 0.05, ***P < 0.001. Source data are available online for this figure.

Analysis of protein-protein interactions for induced genes from enriched mitochondria related ontologies (Fig. 7C), revealed tight interaction networks involving structural mitochondrial, mitoribosome and respirasome/ETC (oxidative phosphorylation) proteins, in both liver (Appendix Fig. S4A) and WAT (Appendix Fig. S4B) macrophages. In addition, the intersection of upregulated genes revealed a network subset shared in both organs, suggesting that these genes are part of a core effector response (Appendix Fig. S4C). Specifically, the transcriptional response of Fth-competent macrophages included the induction of genes supporting the ETC, such as Uqcrq (complex III subunit), as well as genes involved in mitochondria biogenesis (e.g., Nrf1 and PolG2), maintenance of mitochondrial cristae structure (e.g., ChChd2) and mitochondrial protein translation (Fig. 7D). Moreover, we also observed a downregulation of genes in the mitochondria tricarboxylic acid (TCA) cycle (Fig. 7D).

We noted that mitochondrial fission regulator 1 like (Mtfr1l), showed decreased expression in in Fth-competent vs. Fth-deleted macrophages (Fig. 7D). This suggests that suppression of mitochondrial regulation through fission contributes to the rescuing capacity of Fth-competent macrophages (Fig. 7D).

RNAseq analysis of cardiac Fth-competent vs. Fth-deleted macrophages from chimeric mice, revealed a distinct transcriptional response that did not include the regulation of mitochondrial genes (Fig. EV7A–D). This suggests that Fth-competent monocyte-derived macrophages activate transcriptional programs that are tissue-specific and likely prevent multiorgan dysfunction imposed by global Fth deletion.

Figure EV7. Fth-competent monocyte-derived macrophages in the heart of Fth-deleted chimeras do not employ a mitochondrial gene transcriptional program.

Figure EV7

(A) Schematic representation of chimeric mice, TAM administration and fluorescence-activated cell sorting (FACS) of LysM+ monocyte/macrophages (CD45+, CD11b+, Ly6G, CD19, TCRβ) in liver, WAT and heart. (B) Volcano plots of differentially regulated genes between LysM+ monocyte/macrophages sorted from the heart of tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) vs. tdTLysMFthfl/fl (n = 4; left) or tdTLysMFthR26Δ/Δ (n = 3; right) chimeric mice, on day 19 post TAM administration. Yellow dots depict genes involved in iron/heme metabolism that are significantly differentially regulated. Gene ontology analysis depicting ontologies that are significantly enriched comparing LysM+ monocyte/macrophages sorted from heart of (C) tdTLysMFthLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeras, vs. tdTLysMFthfl/fl (n = 4; left) or (D) tdTLysMFthR26Δ/Δ (n = 3; right) chimeric mice on day 19 post-TAM administration. Ontologies significantly enriched in LysM+ monocyte/macrophages from tdTLysMFthfl/fl are depicted as: enrichment score −log10 P value > 1.301. Ontologies significantly enriched in LysM+ monocyte/macrophages from tdTLysMFthLysMΔ/ΔFthR26Δ/Δ or tdTLysMFthR26Δ/Δ chimeras are depicted as: enrichment score -log10 P value < −1.301. Ontology classes: TF = transcription factors; GO:CC = gene ontology: cellular component; GO:MF = GO: molecular function; GO:BP = GO: biological process; KEGG = Kyoto Encyclopedia of Genes and Genomes pathway; WP = Wiki Pathways. (E) Schematic representation of chimeric mice, TAM administration (day 0), and flow cytometry analysis of livers from positive (PhAMR26; n = 3) and negative control (Fthfl/fl; n = 1) mice, and PhAMLysMtdTR26 (n = 3), PhAMLysMFthLysMΔ/ΔtdTR26FthR26Δ/Δ (n = 3), PhAMLysMtdTR26FthR26Δ/Δ (n = 3) chimeras. (F) Percentage and (G) median fluorescence intensity (MFI) of CD45 cells that are PhAM+. (H) Schematic representation of chimeric mice, TAM administration (day 0), and flow cytometry analysis of livers from positive (PhAMLysMFthfl/fl; n = 3) and negative control (Fthfl/fl; n = 3) mice, and Fthfl/flPhAMR26 (n = 3), FthLysMΔ/ΔPhAMR26FthR26Δ/Δ (n = 3), Fthfl/flPhAMR26FthR26Δ/Δ (n = 3) chimeras. (I) Percentage and (J) median fluorescence intensity (MFI) of LY6CHigh monocyte-derived macrophages (CD11b+, F4/80Int, LY6CHi, Lin, LY6G, CD11C, PhAM+) that are PhAM+. Data in (F) is pooled from 2 independent experiments. Data in (F, G, I, J) is presented as individual values and mean. One-way ANOVA with Tukey’s range test for multiple comparison correction was used for comparison between multiple groups. NS: non-significant, **P < 0.01, ****P < 0.0001.

To monitor the mitochondria of monocyte-derived macrophages, we introduced an additional Rosa26-mito-Dendra2-Flox-stop-Flox allele in LysMCre, driving the expression of a Dendra2 fluorescent protein fused to mitochondria targeting sequence of the cytochrome c oxidase subunit VIII (mito-Dendra2/PhAM) (Pham et al, 2012) mice. PhAMLysM mice were crossed with Fthfl/fl mice to generate PhAMLysMFthfl/fl mice, deleting Fth specifically in PhAM+ myeloid cells.

The relative level of PhAM expression was higher in Fth-competent vs. Fth-deleted monocyte-derived macrophages, from the liver (Fig. 7E,F) and WAT (Fig. 7E,G) of PhAMLysMFthR26Δ/Δ vs. PhAMLysMFthR26Δ/ΔFthR26Δ/Δ chimeras, respectively. This is consistent with the transcriptional program supporting mitochondrial biogenesis increasing the number of mitochondria in Fth-competent vs. Fth-deleted monocyte-derived macrophages.

Of note, the percentage of PhAM+ monocyte-derived macrophages was lower in WAT from PhAMLysMFthR26Δ/Δ vs. PhAMLysMFthR26Δ/ΔFthR26Δ/Δ chimeras (Fig. 7G). This suggests that there is an alteration on the relative percentage of one or several other CD45+ populations in PhAMLysMFthR26Δ/ΔFthR26Δ/Δ or PhAMLysMFthR26Δ/Δ chimeras.

Myeloid cells rescue chimeric Fth-deleted mice via a mechanism that relies on a transcriptional program supporting mitochondrial biogenesis

To test the involvement of mitochondrial biogenesis on the rescuing capacity of Fth-competent macrophages, we deleted TFAM, the master regulator of mitochondrial DNA (mtDNA) transcription and replication (Larsson et al, 1998), specifically in myeloid cells (Wculek et al, 2023). Tfam-deleted myeloid cells failed to prevent the lethal outcome of Fth-deletion in TfamLysMΔ/ΔFthR26Δ/Δ chimeras, as compared to Tfamfl/flFthR26Δ/Δ chimeras reconstituted with Tfam-competent myeloid cells (Fig. 8A). This suggests that mtDNA replication and/or transcription regulation by TFAM is essential to support the rescuing capacity of monocyte-derived macrophage.

Figure 8. Mitochondrial biogenesis supports the rescuing capacity of Fth-competent monocyte-derived macrophages in chimeric Fth-deleted mice.

Figure 8

(A) Schematic representation of chimeric mice, TAM administration (day 0), and survival of Tfamfl/flFthfl/fl (n = 4), FthR26Δ/ΔFthR26Δ/Δ (n = 5), Tfamfl/flFthR26Δ/Δ (n = 6) and TfamLysMΔ/ΔFthR26Δ/Δ (n = 6) chimeric mice on day 0. Data in (B) is pooled from 2 independent experiments with similar trends. (B) Schematic representation of chimeric mice, TAM administration (day 0), and survival of Uqcrqfl/flFthfl/fl (n = 6), Uqcrqfl/flFthR26Δ/Δ (n = 6), FthR26Δ/ΔFthR26Δ/Δ (n = 2), and UqcrqLysMΔ/ΔFthR26Δ/Δ (n = 5) chimeric mice on day 0. (C) Schematic representation of chimeric mice, TAM administration (day 0), and flow cytometry analysis of livers from positive (PhAMR26; n = 3) and negative control (Fthfl/fl; n = 1) mice, and PhAMLysMtdTR26 (n = 3), PhAMLysMFthLysMΔ/ΔtdTR26FthR26Δ/Δ (n = 3), PhAMLysMtdTR26FthR26Δ/Δ (n = 3) chimeras with (D) representative PhAM fluorescence histograms and (E) PhAM expression index of CD45 parenchymal cells. PhAM index is calculated as the percentage of CD45 cells that are PhAM+, multiplied by CD45PhAM+ cells’ MFI. (F) Schematic representation of chimeric mice, TAM administration (day 0), and flow cytometry analysis of livers from positive (PhAMLysMFthfl/fl; n = 3) and negative control (Fthfl/fl; n = 3) mice, and Fthfl/flPhAMR26 (n = 3), FthLysMΔ/ΔPhAMR26FthR26Δ/Δ (n = 3), Fthfl/flPhAMR26FthR26Δ/Δ (n = 3) chimeras with (G) representative PhAM fluorescence histograms and (H) PhAM expression index of LY6CHigh monocyte-derived macrophages (CD11b+, F4/80Int, LY6CHi, Lin, LY6G, CD11C, PhAM+). PhAM index is calculated as the percentage of LY6CHigh monocyte-derived macrophages that are PhAM+, multiplied by their PhAM MFI. Data in H is pooled from 2 independent experiments. (I) Schematic representation of control (Fthfl/fl) or FTH-deficient (FthR26Δ/Δ) BMDM generation, Tamoxifen (TAM) administration and cell viability assessment. (J) Representative brightfield and fluorescent microscopy images of viability staining (PI) of BMDM treated with vehicle, or mitochondria, 15 h post-treatment. (K) Time course of BMDM cell death upon vehicle or mitochondria administration. For (J, K), wells receiving mitochondria were administered mitochondria purified from 60 mg of liver. (L) Time course of BMDM cell death upon vehicle or Fe (FAC, ferric ammonium citrate; 125 µM) administration. Data in (E, H) is presented as individual values and mean. Data in (K, L) is presented as mean +/− SEM (n = 3 replicates per condition). Two-way ANOVA was used for comparison between two groups within time courses. Survival analysis was performed using Log-rank (Mantel–Cox) test. Survival analysis in (A) is corrected for multiple comparisons using Bonferroni test. NS: non-significant, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. Source data are available online for this figure.

TFAM regulates the transcription of several components of the mitochondrial ETC (i.e., complex I, III, IV, and V), supporting oxidative phosphorylation (OXPHOS) (Wculek et al, 2023). To disentangle OXPHOS from other mitochondrial functions supported by TFAM, we deleted Uqcrq, the gene encoding the Ubiquinol-cytochrome c reductase, complex III subunit VII, specifically in myeloid cells from UqcrqLysMΔ/Δ mice (Wculek et al, 2023; Weinberg et al, 2019). Uqcrq-deleted myeloid cells retained the capacity to prevent the lethal outcome of Fth-deletion in UqcrqLysMΔ/ΔFthR26Δ/Δ chimeras, similar to Uqcrq-competent myeloid cells in Uqcrqfl/flFthR26Δ/Δ chimeras (Fig. 8B). This suggests that OXPHOS is not essential to support the rescuing capacity of monocyte-derived macrophages.

Fth-competent myeloid cells engage in intercellular mitochondria transfer with parenchyma cells from chimeric Fth-deleted mice

Intercellular mitochondria transfer is an evolutionarily conserved process whereby mitochondria are delivered from donor to acceptor cells, as a mechanism to maintain mitochondria quality in donor cells and/or to provide metabolic support to acceptor cells (Borcherding and Brestoff, 2023; Brestoff et al, 2025; Nakai et al, 2024). We reasoned that Fth-competent monocyte-derived macrophages support the mitochondria of Fth-deleted parenchyma cells through a mechanism associated with intercellular mitochondrial transfer. To test this hypothesis, we generated chimeric mice expressing mito-Dendra2/PhAM specifically in mitochondria from myeloid vs. parenchyma cells. Intercellular mitochondria transfer, from donor to acceptor cells, was quantified by the PhAM index of acceptor cells (median mito-Dendra2/PhAM fluorescence intensity x % mito-Dendra2/PhAM+ cells).

Intercellular mitochondria transfer from donor PhAM+ monocyte-derived macrophages to acceptor parenchyma (tdT+) cells was not detectable, as assessed in the liver of control PhAMLysMtdTR26 chimeras (i.e., tdTR26 mice reconstituted with PhAMLysM BM) (Figs. 8C–E and  EV7E–G). There was also no detectable intercellular mitochondria transfer from donor PhAM+ Fth-competent or Fth-deleted monocyte-derived macrophages to acceptor Fth-deleted parenchyma cells, as assessed in the liver of PhAMLysMtdTR26FthR26Δ/Δ and PhAMLysMFthLysMΔ/ΔtdTR26FthR26Δ/Δ chimeras, respectively (Figs. 8C–E and  EV7E–G). This suggests that the mechanism via which Fth-competent monocyte-derived macrophages support the mitochondria of Fth-deleted parenchyma cells is not associated with intercellular mitochondrial transfer from macrophages to parenchyma cells.

In contrast, there was intercellular mitochondria transfer from donor PhAM+ parenchyma cells to acceptor monocyte-derived macrophages, as assessed in the liver of control Fthfl/flPhAMR26 chimeras (i.e., PhAMR26 reconstituted with Fthfl/fl BM) (Fig. 8F–H and  EV7H–J). Intercellular mitochondria transfer from parenchyma cells to macrophages was also observed in the liver from FthLysMΔ/ΔPhAMR26FthR26Δ/Δ (i.e., PhAMR26FthR26fl/fl mice reconstituted with FthLysMΔ/Δ BM) and Fthfl/flPhAMR26FthR26Δ/Δ (i.e., PhAMR26FthR26fl/fl mice reconstituted with Fthfl/fl BM) chimeras (Figs. 8F–H and  EV7H–J). Importantly, there was tenfold reduction in the PhAM index of hepatic monocyte-derived macrophages from FthLysMΔ/ΔPhAMR26FthR26Δ/Δ vs. Fthfl/flPhAMR26FthR26Δ/Δ chimeras or control Fthfl/flPhAMR26 chimeras (Figs. 8F–H and  EV7H–J). This suggests that Fth-competent monocyte-derived macrophages support the mitochondria of Fth-deleted parenchyma cells via a mechanism associated with intercellular mitochondrial transfer, from donor parenchyma cells to acceptor. Moreover, this also suggest that FTH is required to support the capacity of macrophages to accept mitochondria from parenchyma cells.

Mitochondria are iron-rich organelles (Ben Zichri-David et al, 2025), suggesting that their transfer and uptake by macrophages is cytotoxic in the absence of FTH. Mitochondria purified from the liver of Fth-deficient mice were cytotoxic to Fth-deficient but not Fth-competent BMDM (Fig. 8I–K). This was mimicked by exposure of Fth-deficient BMDM to exogenous Fe (ferric ammonium citrate), at a concentration not lethal to Fth-competent BMDM (Fig. 8I–L). This suggests that FTH is strictly required to maintain macrophage viability following the uptake of exogenous mitochondria.

Discussion

Our findings suggest that monocyte-derived macrophages carry an intrinsic capacity to sense the iron status of parenchyma cells and to respond in a manner that supports tissue function and organismal homeostasis. This is consistent with the notion of tissues representing an emergent property of the interactions between “primary” and “supportive” cells (Adler et al, 2023; Meizlish et al, 2021; Zhou et al, 2018), whereby macrophages act as ferrostats to facilitate tissue-specific parenchyma cell functions (Winn et al, 2020).

The interaction of macrophages with parenchyma cells is thought to give rise to integrated cellular modules (Bonnardel et al, 2019). Additional interactions with peripheral neurons provide these with capacity to surveil and respond to systemic variations of vital parameters (Godinho-Silva et al, 2019; Veiga-Fernandes and Mucida, 2016). In adipose tissue, these integrated cellular modules regulate WAT lipolysis (Ko et al, 2020; Pirzgalska et al, 2017) and BAT thermoregulation (Wolf et al, 2017; Zeng et al, 2015). This occurs via stable physical interaction of macrophages with adipocytes, vascular endothelial cells (Moura Silva et al, 2021; Silva et al, 2019), mesenchymal cells (Ko et al, 2020) and peripheral neurons (Pirzgalska et al, 2017). Our finding that Fth-competent monocyte-derived macrophages control BAT thermogenesis as well as BAT and WAT lipolysis in Fth-deleted chimeras (Figs. 4 and EV4) is consistent with this tissue organizing principle (Adler et al, 2023; Meizlish et al, 2021; Zhou et al, 2018).

The notion that Fth-competent macrophages act as ferrostats, sensing and responding to tissue iron status, to control WAT and BAT function provides further understanding of how regulation of Fe metabolism modulates WAT function (Blankenhaus et al, 2019; Romero et al, 2022; Wang et al, 2024; Yook et al, 2021), BAT thermogenesis (Blankenhaus et al, 2019; Wang et al, 2024; Yook et al, 2021) and energy balance (Blankenhaus et al, 2019; Lu et al, 2024; Wang et al, 2024). This is also consistent with dietary Fe-deficiency compromising thermoregulation in rodents (Dillmann et al, 1979) and humans (Beard et al, 1990; Brigham and Beard, 1996; Lukaski et al, 1990) as well as with dietary Fe overload causing a negative energy balance in rodents (Romero et al, 2022).

That circulating Fth-competent monocyte-derived, rather than tissue-resident, macrophages take control of energy homeostasis is demonstrated using parabiosis (Fig. 1I) as well as by the adoptive transfer of BMDM (Fig. 1J). While illustrating the extraordinary capacity of circulating monocytes to partake in the inter-organ crosstalk that regulates systemic Fe and energy metabolism, this does not exclude other circulating myeloid-derived, such as myeloid-derived suppressor cells (Veglia et al, 2021), from contributing to this process.

Fe exerts a major impact on macrophage function (Soares and Hamza, 2016) suggesting that macrophages act as ferrostats via a mechanism that senses and responds directly to the Fe status of parenchyma cells. This hypothesis, however, is not supported by macrophages retaining the capacity to rescue the lethal outcome of global Fth deletion irrespectively of cellular Fe import via TFR1 (Fig. EV5A,B) or Fe export via SLC40a1 (Fig. EV5C,D). Moreover, macrophages rescue the lethal outcome of global Fth deletion irrespectively of ferritin secretion and transfer to parenchyma cells (Fig. 5C–G). Overall, this suggests that Fth-competent macrophages do not rely on intercellular Fe sensing and/or transfer to support Fth-deleted parenchyma cells.

As an alternative hypothesis, macrophages act as ferrostats via a mechanism that senses and responds to the consequences of dysregulated tissue Fe metabolism, namely, mitochondrial dysfunction (Fig. 6D-G) (Blankenhaus et al, 2019). In support of this hypothesis, macrophages respond to a number of cues released from dysfunctional mitochondria, including mtDNA (Murphy and O’Neill, 2024). In support of with this hypothesis Fth-competent macrophages respond to Fth deletion in parenchyma cells via the induction of a gene expression profile consistent with a type I interferon response (Fig. 7A–C), a hallmark of the macrophage response to mtDNA (Al Amir Dache and Thierry, 2023; He et al, 2022). Moreover, Fth deletion in parenchyma cells is associated with remodeling of the mitochondria cristae structure (Fig. 6D) (Blankenhaus et al, 2019), which regulate mtDNA release from mitochondria to induce a type I interferon response in macrophages (He et al, 2022).

Fth-competent macrophages respond to Fth deletion in parenchyma cells via induction of a singular gene expression profile associated with maintenance of mitochondrial function (i.e., ETC, TCA) and structure (i.e., cristae), as well as with mitochondrial biogenesis (Fig. 7A–G). This genetic program is controlled by the mitochondrial transcriptional regulator TFAM (Larsson et al, 1998), which is required for macrophages to rescue from the lethal outcome of global Fth deletion (Fig. 8A).

While TFAM supports the expression of mitochondrial ETC genes (Wculek et al, 2023), this is probably not essential to rescue the lethal outcome of global Fth deletion (Fig. 8B). This suggests that mitochondria biogenesis is a functional hallmark of macrophages with the capacity to rescue the lethal outcome of Fth deletion in parenchyma cells. This transcriptional program (Fig. 7A–D) was activated exclusively in Fth-competent macrophages (Fig. EV6C–F), suggesting that FTH is essential to support this response.

There are several possible mechanisms via which FTH can regulate the transcriptional program supporting mitochondria biogenesis in macrophages. One possibility is that this occurs via the regulation of DNA methyl transferase 3 A (DNMT3A), consistent with FTH supporting DNMT3A expression (Ye et al, 2019) and with DNMT3A inducing the expression of TFAM in macrophages (Cobo et al, 2022). In support of this hypothesis, DNMT3A was highly induced in Fth-competent macrophages that rescue the lethal outcome of global Fth deletion (Fig. 7D). A non-mutually exclusive possibility is that FTH regulates TFAM via a mechanism involving the ten-eleven translocation (TET) dioxygenases, which use Fe as an essential co-factor and the TCA-derived α-ketoglutarate as a substrate to catalyze cytosine demethylation (Lopez-Moyado et al, 2024). This is consistent with FTH regulating cytosine demethylation by TET dioxygenases (Wu et al, 2024) and with TET inducing the expression of TFAM in macrophages (Pan et al, 2017).

The capacity of Fth-competent macrophages to restore the mitochondria of Fth-deleted chimeric mice (Figs. 6D–J and EV5E) was associated with intercellular mitochondrial transfer from donor Fth-deleted parenchyma cells to acceptor monocyte-derived macrophages (Figs. 8F–H and  EV7H–J). In contrast there is no intercellular mitochondrial transfer from donor Fth-competent macrophages to acceptor Fth-deleted parenchyma cells (Figs. 8C–E and  EV7E–G).

These observations are consistent with Fth-competent macrophages supporting the mitochondria of parenchyma cells via a mechanism involving intercellular transfer of dysfunctional mitochondria from donor Fth-deleted parenchyma cells. Presumably, this allows Fth-deleted parenchyma cells to outsource energetically demanding mitophagy via intercellular transfer of their dysfunctional mitochondria. This process termed transmitophagy (Nicolás-Ávila et al, 2022) was reported in other experimental systems (Brestoff et al, 2021; Nicolás-Ávila et al, 2020; Rosina et al, 2022).

The cytoprotective effect of FTH (Berberat et al, 2003; Gozzelino et al, 2012; Pham et al, 2004) is required for macrophages to handle the Fe contained in the mitochondria transferred from Fth-deleted parenchyma cells. Presumably, this explains the loss of Fth-deleted monocyte-derived macrophages when FTH is also deleted in parenchyma cells (Figs. 1F,J and EV6D).

In conclusion, monocyte-derived macrophages act as ferrostats to take control of organismal Fe, redox and energy metabolism in response to global Fth deletion. This extraordinary capacity relies on a mechanism whereby FTH supports a transcriptional program that acts in a cell autonomous manner to promote mitochondrial biogenesis and in a non-cell autonomous manner to regulate the mitochondria of parenchyma cells in different tissues. These findings support the notion that macrophages play a central role in supporting the function of parenchyma cells in different tissues to sustain homeostatic control of multicellular organisms.

Methods

Reagents and tools table

Reagent/resource Reference or source Identifier or catalog number
Experimental models
Fthfl/fl (C57BL/6) Prof. Lukas Kuhn (ETH, Switzerland) N/A
R26 CreERT2 The Jackson Laboratory Strain: 008463
Cx3cr1 Cre The Jackson Laboratory Strain: 025524
LysM Cre The Jackson Laboratory Strain: 004781
CD2 Cre The Jackson Laboratory Strain: 027406
OKD48 Luc Oikawa et al, 2012 Prof. Iwawaki T. (RIKEN 2-1, Wako, Japan)
OKD48LucFthfl/fl Blankenhaus et al, 2019 N/A
OKD48LucR26CreERT2 Blankenhaus et al, 2019 N/A
OKD48LucR26CreERT2FthΔ/Δ Blankenhaus et al, 2019 N/A
R26 CreERT2 Fth Δ/Δ This manuscript N/A
LysM Cre Fth Δ/Δ This manuscript N/A
CD2 Cre Fth Δ/Δ This manuscript N/A
Cx3CR1 Cre Fth Δ/Δ This manuscript N/A
C57BL/6 Ly5.1 The Jackson Laboratory Strain: 002014
Ccr2 -/- The Jackson Laboratory Strain: 004999
B6.129S Tfrcfl/fl The Jackson Laboratory Strain: 028363
C57BL/6 Slc40a1fl/fl Wu et al, 2023 N/A
C57BL/6 Tfamfl/fl Larsson et al, 1998 MGI: 1860962
C57BL/6 Uqcrqfl/fl Weinberg et al, 2019 Referred to as CIIIfl/fl; MGI: 6358198
LysMCre TfrcΔ/Δ This manuscript N/A
LysMCre Slc40a1fl/fl This manuscript N/A
LysMCre Tfamfl/fl Prof. David Sancho, CNIC, Spain N/A
LysMCre Uqcrqfl/fl Prof. David Sancho, CNIC, Spain N/A
R26 tdTomato The Jackson Laboratory Strain: 007909
R26 tdTomato/CreERT2 This manuscript N/A
R26 tdTomato/CreERT2 Fth Δ/Δ This manuscript N/A
LysMCre R26tdTomato This manuscript N/A
LysMCre R26tdTomatoFthΔ/Δ This manuscript N/A
Fth V5/V5 This manuscript N/A
R26 PhAM The Jackson Laboratory Referred to as PhAMfl/fl; Strain: 018385
R26 PhAM/CreERT2 This manuscript N/A
R26 PhAM/CreERT2 Fth Δ/Δ This manuscript N/A
LysM Cre R26 PhAM This manuscript N/A
LysM Cre R26 PhAM Fth Δ/Δ This manuscript N/A
Antibodies
Anti-mouse-FTH1 Cell Signaling #4393
Anti-V5-HRP Invitrogen #46-0708
Anti-GAPDH SICGEN # AB0049-200
Anti- β-actin Sigma #A5441
HRT-conjugated anti-rabbit IgG– SantaCruz Biotechnology sc-2030
HRT-conjugated anti-mouse IgG– SantaCruz Biotechnology sc-2005
HRT-conjugated anti-goat IgG– ThermoFisher PA1-28664
OxPhos Rodent WB Antibody Cocktail ThermoFisher #45-8099
HRT-conjugated anti-mouse IgG antibody Cell signalling #7076P2
Flow cytometry antibodies
Cx3CR1-APC Biolegend #149007
CD11b-FITC BD #553310
Ly6C-PerCPCy5.5 Biolegend #128012
Ly6G-PE BD #551461
F4/80-PE-Cy7 Biolegend #123114
CD45-APC-e780 Invitrogen #47045182
CD3-biotin BioLegend #100243
CD11b-BV785 BioLegend #101243
CD11c-BV605 BioLegend #11733
CD19-biotin BD #553784
CD31-BV605 BioLegend #102427
CD49b-biotin BioLegend #103521
CD90.1-Thy1.1-PE BioLegend #202524
F4/80-PE-Cy5 BioLegend #123112
Ly6C-PE-Cy7 eBioscience #25-5932-8
Ly6G-AF700 Invitrogen #56-9668-8
SAV-PE-Fire-700 BioLegend #405174
LIVE/DEADTM Fixable viability dye ThermoFisher #L34957
LIVE/DEADTM Fixable viability dye ThermoFisher #L34959
Fc-block (anti-CD16/32) In-house N/A
CD45.1-FITC BioLegend #110705
CD45.2-APC BioLegend #109813
TCRb-FITC In-house N/A
CD19-FITC In-house N/A
CD11b-BV421 BioLegend #101235
Ly6G-AF700 Invitrogen #56-9667-82
Zombie aqua viability dye BioLegend #423101
Recombinant DNA
pgRNAbasic Casaca et al, 2016 N/A
pgRNA-V5-Fth This study N/A
Oligonucleotides and other sequence-based reagents
RT-qPCR primer Arbp0 IDT

Fwd: 5’-CTTTGGGCATCACCACGAA-3’

Rev: 5’-GCTGGCTCCCACCTTGTCT-3’

RT-qPCR primer MT-CO1 IDT

Fwd 5’-TTCGGAGCCTGAGCGGGAAT-3’

Rev 5’-ATGCCTGCGGCTAGCACTGG-3’

RT-qPCR primer MT-CyB IDT

Fwd 5’-CTTAGCCATACACTACACATCAG-3’

Rev 5’-ATCCATAATATAAGCCTCGTCC-3’

RT-qPCR primer PolG IDT

Fwd 5’-GCCCCACTGTAGAATCCGCTG-3’

Rev 5’-AGCAGCAGGCAGAACTAGAGG-3’

RT-qPCR primer Cs IDT

Fwd 5’-TGGGGTGCTGCTCCAGTACTAT-3’

Rev 5’-AGTCTTAAAGGCCCCTGAAACAA-3’

RT-qPCR primer Nrf1 IDT

Fwd 5’-CCAGVAAGTCCAGCAGGTCC-3’

Rev 5’-TTCCCTGTTGCCACAGCAGC-3’

RT-qPCR primer Nd1 IDT

Fwd 5′-CTAGCAGAAACAAACCGGGC-3′

Rev 5′-CCGGCTGCGTATTCTACGTT-3′

RT-qPCR primer Hk2 IDT

Fwd 5′-GCCAGCCTCTCCTGATTTTAGTGT-3′

Rev 5′-GGGAACACAAAAGACCTCTTCTGG-3′

PCR primer Fth-Chk IDT

Fwd 5’-GGCCGCTTCGAGCCTGAGCCC-3’

Rev 5’-GGTTGATCTGGCGGTTGATGG-3’

V5-Fth RNA-up IDT 5’-AGGGCGAGGGAGACGCGGTGGTCA-3’
V5-Fth RNA-down IDT 5’-AAACTGACCACCGCGTCTCCCTCG-3’
V5-Fth replace IDT 5’-TGCAACTTCGTCGTTCCGCCGCTCCAGCGTCGCCACCGCGCCTCGCCCCGCCGCCACCATGACCGGCAAGCCCATCCCCAACCCCCTGCTGGGCCTGGACAGCACCACCACCGCGTCTCCCTCGCAAGTGCGCCAGAACTACCACCAGGACGCGGAGGCTGCCATCA-3’
Chemicals, enzymes and other reagents
Collagenase D Sigma-Aldrich #11088866001
DNase I Sigma-Aldrich #10104159001
ECL western blotting substrate ThermoFisher #32106
4-hydroxytamoxifen Sigma-Aldrich #H6278
Tamoxifen Sigma-Aldrich #T5648
Corn oil Sigma-Aldrich #C8267
Mitochondria Isolation Kit for Tissue Thermo Fisher #89801
MEGAshortscriptTM T7 Transcription kit Thermo Fisher #AM1354
MEGAclearTM Transcription Clean-up kit Thermo Fisher #AM1908
Meloxicam Meloxidyl, 5 mg/ml, Ceva GTIN 03411111913498
Ketamine Ketabel, Bela-pharm GmbH 1346/01/20DFVPT
Xylazine Rompun, Elanco, Bayer Animal Health GmbH 440/01/12NFVPT
RPMI 1640 Thermo Fisher #61870044
Pen/Strep Gibco #15140122
FCS Gibco #A5256701
L929 conditioned medium This study N/A
Ferric ammonium citrate Sigma-Aldrich 1185-57-5
Propidium iodide Life Technologies #P3566
Hoechst 33342 Invitrogen #H1399
RNeasy Mini Kit QIAgen #74104
RNeasy MinElute Cleanup Kit QIAgen #74204
Transcriptor first strand cDNA synthesis kit Roche #04896866001
Syber Green Master Mix Applied Biosystems #4309155
Bathophenanthroline disulfonic acid Sigma-Aldrich #52746-49-3
Buffer RLT plus QIAgen #1053393
RNA 6000 pico kit Agilent Technologies #50671513
llumina Tagment DNA Enzyme and Buffer Illumina #20034211
KAPA HiFi HotStart ReadyMix Roche #07958935001
Nextera XT Index Kit v2 Set A Illumina #15052166
PFA Alfa Aesar #043368-9 M
Low-melting point agarose Invitrogen #15517-014
Mowiol mounting medium Merck #81381-50 G
DAPI
Glutaraldehyde Polysciences #NC9072609
Formaldehyde EMS #15700
Osmium tetroxide EMS #19104
Potassium ferrocyanide Sigma-Aldrich #702587
Tannic acid EMS #21700
EPON resin EMS #14910
Phenol:Chloroform:Isoamyl Alcohol (25:24:1, v/v) Sigma-Aldrich #77617
Software
Fiji software (ImageJ). https://imagej.net/ij/index.html v.1.54 f
Primer Blast Ye et al, 2012 N/A
FlowJo software FlowJo, LLC v.10.3
bcl2fastq Illumina v.2.19.1.403
STAR alignment Dobin et al, 2013 v.2.5.2a
FeatureCounts Liao et al, 2014 v.1.5.0-p1
R https://www.r-project.org/ v.4.1.0
R Studio Desktop https://posit.co/download/rstudio-desktop/ v.2024.12.0 + 467
DESeq2 R package Love et al, 2014 v.1.32
ashr algorithm Stephens, 2016 v.2.2–47
biomaRt R package Durinck et al, 2005, Durinck et al, 2009 v.2.48.2
ggplot2 R package Wickham, 2016 v.3.3.5
gprofiler2 R package Kolberg et al, 2020 v.0.2.1
Cytoscape Shannon et al, 2003 v.3.9.0
FLIR Tools software FLIR Systems v.6.4
Macro Interpreter Sable Systems v.2.41
Labscribe2 iWorx Systems v2
Other
Pressure-volume conductance catheter Scisense FTS-1912B-8018
pressure-volume control unit Scisense FV896B
Cytation 5 Agilent/BioTek N/A
Hamamatsu Aequoria Hamamatsu N/A
Rodent Thermometer Bioseb BIO-TK8851
Silk suture 3-0 Mersilk W212
Ultra low-adherence T75 cell culture flasks Corning #734-4139
Leica DMLB2 microscope Leica
NanoZoomer-SQ Digital slide scanner Hamamatsu
BD LSRFortessa X-20 BD Biosciences
Aurora spectral flow cytometer Biotek
CyanADP Beckman Coulter
BD FACSAria II BD Biosciences
ABI QuantStudio - 384 Real-Time PCR System Applied Biosystems
Agilent Bioanalyzer 2100 Agilent Technologies
NextSeq500 Illumina
FLIR E96 Compact-Infrared-Thermal-Imaging-Camera FLIR Systems
Promethion Core metabolic cages system Sable Systems
Leica Vibratome VT 1000 S Leica
Leica SP5 confocal Leica
Leica DM6000 inverted microscope Leica
PELCO BioWave Microwave Processor PELCO
Leica UC7ultramicrotome Leica
FEI Tecnai G2 Spirit electron microscope BioTWIN
Qiagen TissueLyser II Qiagen

Animals

Mice were bred and maintained under specific pathogen-free (SPF) conditions at the Gulbenkian Institute for Molecular Medicine (GIMM). For strains used, please see “Reagents and Tools Table”. All experimental protocols were approved by the Ethics Committee of the IGC, the “Órgão Responsável pelo Bem-estar dos Animais” (ORBEA) (license A009/2011 and A006-2022) and the Portuguese National Entity (Direcção Geral de Alimentação e Veterinária). Experimental procedures were performed according to the Portuguese (Portaria no. 1005/92, Decreto-Lei no. 113/2013 and Decreto-lei no. 1/2019) and European (Directive 2010/63/EU) legislations, concerning housing, husbandry, and animal welfare. R26CreERT2FthΔ/Δ; LysMCreFthΔ/Δ; CD2CreFthΔ/Δ and Cx3CR1CreFthΔ/Δ mice were generated by crossing C57BL/6 Fthfl/fl mice obtained from Prof. Lukas Kuhn (ETH, Switzerland) with C57BL/6 R26CreERT2, LysMCre, CD2Cre and Cx3cr1Cre mice, respectively. LysMCreTfrcΔ/Δ and LysMCreSlc40a1fl/fl mice were generated by crossing B6.129S Tfrcfl/fl and C57BL/6 Slc40a1fl/fl mice with LysMCre mice, respectively. R26tdTomato/CreERT2 and LysMCre R26tdTomato mice were generated by crossing R26tdTomato mice with R26CreERT2 and LysMCre mice, respectively. R26tdTomato/CreERT2FthΔ/Δ and LysMCre R26tdTomatoFthΔ/Δ mice were generated by further crossing R26tdTomato/CreERT2 and LysMCre R26tdTomato with C57BL/6 Fthfl/fl mice. FthV5 mice contain an allele encoding the FTH protein fused to a V5 epitope at its N-terminal end, just downstream of its natural ATG. This allele was generated through CRISPR/Cas 9-mediated homologous recombination. The sgRNA was generated by in vitro transcription from the “gRNA-V5-Fth” plasmid. This plasmid was built by hybridizing oligonucleotides “V5-Fth-gRNA-up” and “V5-Fth-gRNA-down” (see “Reagents and Tools Table”) and introduced into the BbsI sites of the pgRNA-basic plasmid (Casaca et al, 2016). The gRNA-V5-Fth plasmid was linearized and transcribed with T7 RNA polymerase using the MEGAshortscriptTM T7 Transcription kit (Thermo Fisher cat. #AM1354) and purified with the MEGAclearTM Transcription Clean-up kit (Thermo Fisher cat. #AM1908). The replacement single stranded DNA oligonucleotide “V5-Fth replace” (see “Reagents and Tools Table”) containing the V5 coding region flanked by genomic 60 nucleotide homology sequences was obtained from IDT. To generate the FthV5 mice, a mix containing V5-Fth-sgRNA (10 ng/μl), Cas 9 mRNA (10 ng/μl), and the V5-Fth replace oligo (10 ng/μl) was introduced into fertilized C57BL/6 mouse oocytes by pronuclear microinjection. Identification of the recombinant allele was done by PCR on genomic DNA purified from tail biopsies using the oligonucleotide pair “Fth-Chk-Fwd” and “Fth-Chk-Rev” (see “Reagents and Tools Table”) that amplifies the relevant genomic area from both the wild type and the V5-tagged alleles (160 and 205 bps, respectively). The PCR fragments were separated by electrophoresis in a 15% polyacrylamide/TBE gel, the band corresponding to the V5-containing allele recovered, and its sequence confirmed. R26PhAM/CreERT2 and LysMCreR26PhAM mice were generated by crossing R26PhAM mice with R26CreERT2 and LysMCre mice, respectively. R26PhAM/CreERT2FthΔ/Δ and LysMCreR26PhAMFthΔ/Δ mice were generated by further crossing R26PhAM/CreERT2 and LysMCreR26PhAM mice with C57BL/6 Fthfl/fl mice.

Bone marrow chimeras

All bone marrow chimera combinations were generated by lethally irradiating (8.5 Gy) recipient mice and reconstituted 4 h post-irradiation with freshly isolated or cryo-preserved bone marrow cells isolated from donor mice (retroorbital injection of 2–3 × 106 cells in 100 μL RPMI). Successful hematopoietic cell reconstitution was confirmed 6–8 weeks after bone marrow transfer via flow cytometry using differential CD45.1/CD45.2 haplotype markers and corresponding to cells derived from donor or recipient hematopoietic progenitors, respectively, or by concomitant lethal irradiation of control mice that were not reconstituted with bone marrow cells.

Tamoxifen treatment

Conditional Fthfl/fl deletion (Δ) in bone marrow chimeras generated with either R26CreERT2FthΔ/Δ recipient and/or donor mice was induced at 6–10 weeks post-transplantation by oral gavage of tamoxifen (Sigma-Aldrich, Cat. #T5648; 50 mg/kg body weight in 100 µL Corn Oil (Sigma, Cat. #C8267)/5% EtOH; 3× every other day). Conditional deletion of the Fthfl/fl allele in R26CreERT2Fthfl/fl mice was achieved via oral gavage with tamoxifen, as described above with the following change in dosage: 225 mg/kg in 100 μL corn oil /5% ethanol; 3x every second day. Body weight and temperature (Rodent Thermometer BIO-TK8851, Bioseb, France) were monitored from daily to once a week and further downstream analyses were performed when the body weight loss of FthR26Δ/ΔFthR26Δ/Δ or FthLysMΔ/ΔFthR26Δ/Δ bone marrow chimeras was 10% or higher.

Parabiosis

Parabiosis was performed essentially as described (Kamran et al, 2013). Briefly, age and weight-matched male mice were cohoused at least 2 weeks before surgery to ensure harmonious cohabitation. Mice were injected with Meloxicam (2 mg/kg, subcutaneous, s.c.) 30 min prior to surgery. Mice were anaesthetized (intraperitoneal, i.p.) using ketamine (75 mg/kg) and xylazine (15 mg/kg) (~ 140 µL/mouse, 1:1 vol/vol in sterile 0.9% saline) and placed on a heating pad. The corresponding lateral body parts were shaved and disinfected with Betadine® solution. A longitudinal skin incision was made starting at 0.5 cm above the elbow to 0.5 cm below the knee joint, and the subcutaneous fascia was bluntly dissected to create about 0.5 cm of free skin. The corresponding elbow and knee joints were sutured together using a silk suture (3-0 Mersilk #W212) and the corresponding dorsal and ventral skin were attached using continuous sutures (5-0 Vicryl). Mice were resuscitated with 0.9% saline solution (1 mL, s.c.) and placed on a heating pad (30 min–2 h) until recovery from anesthesia. Following recovery, each parabiotic pair was placed in a clean cage and provided with free access to food and water by placing hydrogel or food pellets on the bottom of the cage. Mice were injected with analgesics buprenorphine (0.1 mg/kg s.c.) every 12 h for 48 h and Meloxicam (1 mg/kg s.c.) every 24 h for 48 h. Mice were monitored for signs of pain, distress and weight loss for 6–8 weeks until at least 80% of the combined original weight was recovered. Tamoxifen food was given for 10 days after which it was replaced by normal food. The survival and weight loss of the parabiotic mouse pairs were monitored for 100 days.

Adoptive cell transfer

Adoptive transfer of bone marrow-derived monocytes (BMDM) was performed essentially as described (Wagner et al, 2014). Briefly, BMDM cells were generated from both Fth-competent (tdTR26) and Fth-deleted (tdTR26FthR26fl/fl). To this end, bone marrow was freshly isolated from the tibia and femurs of tdTR26 and tdTR26FthR2fl/fl mice and placed in culture for 7 days in Ultra low-adherence T75 cell culture flasks (Corning cat. #734-4139) with BMDM differentiation culture medium (RPMI, 10%FCS, 1%Pen/Strep, supplemented with 10% L929 culture supernatant containing M-CSF1). On culture day 5, 4-hydroxytamoxifen was added to the medium (1 µM) to induce the CreERT2-mediated deletion of Fth. Concomitantly, Fthfl/fl and FthR26fl/fl mice were treated with tamoxifen as described above to induce the deletion of Fth. Differentiated BMDM were collected from cell culture flasks, washed in RPMI (10 ml; 300 g, 5 min, 4 °C) and resuspended in RPMI (final concentration: 20–50 × 106 cells/ml). On days 4, 8, 12 and 15 post-tamoxifen treatment, 100 µL of BMDM cell suspension was injected retroorbitally in each mouse (2–5 × 106 cells/mouse/injection).

Real-time imaging of cell death

Cell death kinetics was monitored using a Cytation 5 (Agilent/BioTek) live-cell analysis system in primary mouse BMDMs, that were generated as described before (Martins et al, 2016). Briefly, bone marrow cells were freshly collected from tibia and femur from Fthfl/fl and FthR26fl/fl mice and differentiated in tissue culture dishes containing RPMI-1640 with 10% FCS, pen/strep and 10% L929 conditioned medium for 6 days. On culture day 5, 4-hydroxytamoxifen was added to the medium (1 µM) to induce the CreERT2-mediated deletion of Fth. BMDM were seeded at a density of 1.25 × 105 cells/well in 96-well tissue culture plates and treated with either vehicle, Fe (125 µM ferric ammonium citrate; FAC) or mitochondria. Mitochondria were purified from the liver of FthR26Δ/Δ mice (day 6 post-tamoxifen administration), using Mitochondria Isolation Kit for Tissue (ThermoFisher) according to the manufacturer’s protocol. For cells treated with mitochondria, each well was given mitochondria purified from 60 mg of liver. Cells were stained with 100 nM of Hoechst for 30 min prior to stimulation. Cell death was measured by propidium iodide (PI; P3566, Life Technologies) incorporation following the manufacturer’s protocol. The plate was scanned for the indicated time points where fluorescent and brightfield images were acquired in real-time every 3 h (technical replicates n = 3), and nine images per technical replicate and per time point were taken. Dead cells were identified as Hoechst and PI-positive and quantified using the software Gen5 (Agilent/BioTek).

qRT-PCR

RNA was isolated from organs using RNeasy Mini Kit (QIAGEN). Briefly, mice were euthanized and transcardially perfused with ice cold PBS. Organs were collected into Eppendorf tubes and snap frozen in liquid nitrogen. RNA was isolated and processed according to the manufacturer instructions. cDNA was transcribed from total RNA with transcriptor first strand cDNA synthesis kit (Roche). Quantitative real-time PCR (qRT-PCR) was performed using 1 μg cDNA and Syber Green Master Mix (Applied Biosystems, Foster City, CA, USA) in duplicate on an ABI QuantStudio - 384 Real-Time PCR System (Applied Biosystems) under the following conditions: 95 °C/10 min, 40 cycles/95 °C/15 s, annealing at 60 °C/30 s and elongation 72 °C/30 s. Primers were designed using Primer Blast (Ye et al, 2012). Primer sequences are available in “Reagents and Tools Table”.

Cardiovascular function

Cardiovascular function was measured using pressure–volume conductance catheter technique (Pacher et al, 2008). Briefly, 7 days post-tamoxifen treatment as described above, Fthfl/fl, R26CreERT2 and R26CreERT2FthΔ/Δ mice were anesthetized with isoflurane, tracheotomized and artificially ventilated. Temperature was recorded continuously and kept stable. The apex of the left ventricle was punctured with a 27 G needle using the open chest approach and a pressure-volume conductance catheter (FTS-1912B-8018; Scisense, London, Canada) was inserted in the left ventricle. Mice were stabilized for 3–10 min. Baseline values, values with varying preload caused by inferior vena cava clamps using a blunt forceps and aortic pressures, were recorded with the Scisense pressure-volume control unit FV896B and analyzed using the Labscribe2 (Labscribe, iWorx Systems, USA) software. The machine was calibrated with internal and cuvette calibration, as described (Pacher et al, 2008). Bone marrow chimeras were monitored following Fth deletion and analyzed when body temperature dropped below 32 °C.

In vivo luciferase assay

Following deletion of Fth via Tamoxifen treatment as described above bone marrow chimeric mice on OKD48Luc genetic background were monitored daily for luciferase activity. Mice were anesthetized using intraperitoneal Ketamine/Xylasine injection. The abdomen was shaved, and mice received an intravenous injection of luciferin (2 mg/mouse in 100 µL PBS). Luciferase signal was acquired in a Hamamatsu Aequoria using an electron multiplying CCD (EMCCD) camera with highest sensitivity (255) and maximum gain (5) for 10 s, 30 s, 60 s, 120 s and 240 s. Quantification was performed using Fiji software (ImageJ).

Iron quantification in organs and plasma

Non-heme iron concentration in heart and livers of bone marrow chimeras was assessed as previously described (Martins et al, 2016). Briefly, liver or heart were homogenized 1:5 in PBS and 100 µL (equivalent to 20 mg tissue) of homogenate or 20 µL plasma were hydrolyzed (65 °C; overnight) by adding 50 µL of 26% HCl, 1.8 M trichloroacetic acid. The hydrolyzed samples were then clarified by centrifugation (3000×g; RT). Clarified samples (60 µL) were transferred to a 96-well plate and mixed with 160 µL of 3.8 M sodium acetate, 575 µM bathophenanthroline disulfonic acid and 2.5 mM ascorbic acid. Samples were incubated (5 min; RT) and absorbance was measured at λ540nm and iron concentration was calculated using [Fe]=(((AsAb)×V×MW))/((e×l×t)), where As is the sample absorbance, Ab is the blank absorbance, V is the reaction volume (0.22), MW is the molecular weight of iron (56 g∙mol−1), e is the millimolar absorptivity of bathophenanthroline disulfonic acid (22.14 mM-1∙cm−1), l is the path length (0.6 cm) and t is the weight of tissue used. In addition, measured concentrations were confirmed using standard iron serial dilutions.

Western blot

Proteins were extracted, electrophoresed, and transferred essentially as described (Blankenhaus et al, 2019). Briefly, organs were collected from mice following euthanasia and perfusion with ice cold PBS (20 mL) and snap frozen in liquid nitrogen. For protein extraction tissue was homogenized in RIPA buffer using a tissue douncer kit, sonicated and centrifuged. Supernatant was collected and total protein was quantified using Bradford assay. Anti-mouse-FTH1 (clone D1D4; 1:1000; Cell Signaling cat. #4393), anti-V5-HRP (1:5000; Invitrogen cat. #46-0708), Anti-GAPDH (1:5000; SICGEN cat. # AB0049-200) and anti- β-actin (1:5000; Sigma cat. #A5441) were detected using peroxidase conjugated secondary antibodies (HRP-conjugated anti-rabbit IgG—Santa Cruz Biotechnology sc-2030; HRP-conjugated anti-mouse IgG— SantaCruz Biotechnology sc-2005; HRP-conjugated anti-goat IgG—Thermo Fisher PA1-28664; 1:5000; 1 h; RT) and developed with ECL western blotting substrate (ThermoFisher Scientific). Detection of proteins of the ETC by Western blot was performed using OxPhos Rodent WB Antibody Cocktail (ThermoFisher cat. #45-8099; 1:1000; 4 °C overnight), followed by washing and incubation with secondary HRP-conjugated anti-mouse IgG antibody (1:2000, RT; Cell Signalling cat. #7076P2). WB quantification was performed using FiJi (ImageJ) or ImageLab Software (BioRad).

Serology

Bone marrow chimeras were euthanized using CO2 inhalation and blood was collected by cardiac puncture and placed in heparin tubes. Blood samples were sent to DNAtech (Clinical and veterinary analysis laboratory, Lisbon) for analysis of serologic parameters including ALT, AST, Urea, CPK, Troponin I and LDH as well as Transferrin and Transferrin saturation.

Histology

Organs were harvested, fixed in 10% formalin, embedded in paraffin, sectioned into 3 μm-thick sections and stained with Hematoxylin and Eosin (H&E). Whole sections were analyzed and images acquired with a Leica DMLB2 microscope (Leica) and NanoZoomer-SQ Digital slide scanner (Hamamatsu). For WAT adipocytes area and BAT lipid droplets measurements, H&E-stained paraffin-embedded sections (3 μm sections) were scanned into digital images (NanoZoomer-SQ Digital slide scanner -Hamamatsu). The average WAT adipocyte size in adipose tissue sections (expressed as the mean cross-sectional area per cell (μm2)) was determined using Fiji software, as described elsewhere (Blankenhaus et al, 2019). Briefly, a slide scanned picture was captured at 2.5x magnification. An average of 1500 adipocytes were measured per sample. The following macro was applied: run (“Set Scale…”, “distance=560 known=250 pixel=1 unit=um global”); run (“Duplicate…”, “ “); run (“Subtract Background…”, “rolling=50 light separate sliding”); run (“Despeckle”); run (“8-bit”); setAutoThreshold(“Mean dark”); //run (“Threshold…”); //setThreshold(250, 255); setOption(“BlackBackground”, false); run (“Convert to Mask”); run (“Make Binary”); run (“Dilate”); run (“Close-“); run (“Invert”); run (“Analyze Particles…”, “size=330–15,000 circularity=0.50–1.00 display exclude clear summarize add”). The average BAT lipid droplet size (expressed as the mean cross-sectional area per lipid droplet (μm2)) were quantified in three non-overlapping ×40 magnification fields for each mouse. The following macro was applied: run (“Set Scale…”, “distance=452 known=100 pixel=1 unit=um global”); run (“Duplicate…”, “ “); run (“Subtract Background…”, “rolling=50 light separate sliding”); run (“Despeckle”); run (“8-bit”); setAutoThreshold(“Mean dark”); //run (“Threshold…”); //setThreshold(245, 255); setOption(“BlackBackground”, false); run (“Convert to Mask”); run (“Make Binary”); run (“Dilate”); run (“Close-“); run (“Invert”); run 25 (“Watershed”); run (“Analyze Particles…”, “size=1-5000 circularity=0.4-1.00 display exclude clear summarize add”).

Flow cytometry

Reconstitution of bone marrow chimeras was tested by staining peripheral blood leukocytes with CD45.1-FITC (BioLegend cat. #110705), CD45.2-APC (BioLegend cat. #109813), to determine the relative contribution of donor bone marrow towards engraftment. To quantify the numbers of tissue leukocytes, animals were transcardially perfused with 10 mL cold PBS. Briefly, liver, kidney, lung and heart were cut into small pieces, digested in 10 mL digestion medium (HBSS supplemented with 1 mg/mL Collagenase D (Sigma-Aldrich cat. #11088866001) and 10 µg/mL DNase I (Sigma-Aldrich cat. #10104159001)), shaking at 220 rpm, 37 °C for 45 min. The digested solution was passed through a cell strainer (100 µm) and washed with 5 mL of RPMI. Cells were pelleted by centrifugation (300× g; 4 °C; 10 min) and resuspended in 5 mL ACK red blood cell (RBC) lysis buffer. After 5 min at RT RBC lysis was stopped by adding 5 mL of FACS buffer (1× PBS 3% FCS) and cells were passed through a 40 µm cell strainer. Cells were again centrifuged (300× g; 4 °C; 10 min) and finally resuspended in 3 mL (liver and kidney) or 1 mL (heart and lung) FACS buffer. In total, 300 µL of cell suspension were used for the staining of leukocytes with the following antibodies: Cx3CR1-APC (Biolegend, cat. #149007), CD11b-FITC (BD, cat. #553310), Ly6C-PerCPCy5.5 (Biolegend, cat. #128012), Ly6G-PE (BD, cat. #551461), F4/80-PE-Cy7 (Biolegend, cat. #123114), CD45-APC-e780 (Invitrogen, cat. #47045182), CD3-biotin (BioLegend, cat. #100243), CD11b-BV785 (BioLegend, cat. #101243), CD11c-BV605 (BioLegend, cat. #11733), CD19-biotin (BD, cat. #553784), CD31-BV605 (BioLegend, cat. #102427), CD49b-biotin (BioLegend, cat. #103521), CD90.1-Thy1.1-PE (BioLegend, cat. #202524) F4/80-PE-Cy5 (BioLegend, cat. #123112) Ly6C-PE-Cy7 (eBioscience, cat. #25-5932-8), Ly6G-AF700 (Invitrogen, cat. #56-9668-8), and SAV-PE-Fire-700 (BioLegend, cat. #405174). In addition, Fc-block (in-house anti-CD16/32) was used to minimize unspecific Ig binding and LIVE/DEADTM Fixable viability dye (ThermoFisher cat. #L34957), and LIVE/DEADTM Fixable Yellow viability dye (ThermoFisher cat. # L34959) were used to assess cell viability. Data acquisition was performed using either CyanADP (Beckman Coulter), BD LSRFortessa X-20 (BD Biosciences) or Aurora (Cytek) flow cytometers. Samples were analyzed using FlowJo software.

Cell sorting

Monocyte/macrophages were sorted from the liver, WAT and heart of bone marrow chimeras, as indicated in Fig. EV6C. Briefly, Fth deletion was induced via tamoxifen treatment as described above, and 19 days later, bone marrow chimeras were euthanized, and organs were collected. Liver, and heart were cut into small pieces and incubated with digestion buffer (liver: 4 ml; heart: 1 ml; 0.2 mg/mL Liberase (Roche cat. #5401127001) and 100 µg/mL DNAse I (Sigma-Aldrich cat. #10104159001). After digestion, cell suspensions passed through a 40 µm cell strainer. Liver and heart cells were then pelleted (350 g, 5 min, 4 °C) and resuspended in 40% Percoll (GE Healthcare cat. #10607095) in RPMI (liver: 15 ml, heart: 6 ml). A density gradient was made by overlaying the cell suspension onto 80% Percoll in RPMI (liver: 5 ml, heart: 2 ml), and centrifuged (700 g no brake/lowest acceleration, 20 min RT). Liver and heart cells were collected from the density interface and washed once with FACS buffer (10–15 ml; 1× PBS 3%FCS 2 mM EDTA) and centrifuged (350× g, 5 min 4 °C). Plate for antibody staining. WAT was cut into small pieces and placed in 3 mL WAT digestion buffer (4 mg/mL Collagenase IV, 10 mM CaCl2, 0.5% BSA, in PBS without Ca2+/Mg2+). After digestion, WAT cell suspensions were passed through a 100 µm cell strainer and centrifuged (500× g, 10 min, 4 °C). Liver and heart cell pellets were resuspended in 5 mL FACS buffer, and WAT cell pellets were resuspended in 0.25-1 mL FACS buffer. Cells were counted using trypan blue and 1–2 × 106 cells were placed on a 96-well. Cells were centrifuged (700× g, 2 min 4 °C), resuspended in 150 µL of ACK buffer for red blood cell lysis and incubated (5 min, RT). Lysis was stopped by adding 50 µL FACS buffer and cells were washed (700× g, 2 min 4 °C). Cells were resuspended in 50 µL FACS buffer and antibody staining was performed using: CD11b-BV421 (BioLegend, cat. #101235), Ly6G-AF700 (Invitrogen, cat. #56-9668-82), CD45.2-APC (BioLegend cat. #109813), TCRb-FITC (In-house) and CD19-FITC (In-house). In addition, Fc-block (in-house anti-CD16/32) was used to minimize unspecific Ig binding and Zombie aqua viability dye (BioLegend cat. #423101) was used to assess cell viability. Cell sorting and data acquisition was performed using BD FACSAria II (BD Biosciences) cell sorter. 500 cells/sample were sorted directly into 0.2 mL Eppendorf tubes containing 2.5 µL Buffer RLT plus (Qiagen, cat. #1053393). Flow cytometry data were analyzed using FlowJo software.

Bulk RNA sequencing

RNA was extracted, cleaned (RNeasy MinElute Cleanup Kit, Qiagen) and its quality assessed using an Agilent Bioanalyzer 2100 (Agilent Technologies) together with an RNA 6000 pico kit (Agilent Technologies). Full-length cDNAs and sequencing libraries were generated according to the SMART-Seq2 protocol, as previously described (Ramos et al, 2022). Library preparation including cDNA ‘tagmentation’, PCR-mediated adaptor addition and amplification of the adapted libraries was done following the Nextera library preparation protocol (Illumina Tagment DNA Enzyme and Buffer, Illumina #20034211; KAPA HiFi HotStart ReadyMix, Roche #07958935001; Nextera XT Index Kit v2 Set A, Illumina #15052163; Nextera XT Index Kit v2 Set D, Illumina #15052166), as previously described (Ramos et al, 2022). Libraries were sequenced (NextSeq500 sequencing; Illumina) using 75 SE high throughput kit. Sequence information was extracted in FastQ format, using Illumina’s bcl2fastq v.2.19.1.403, producing on average ~38 × 106 (liver), 32 × 106 (WAT) and 43 × 106 (heart) reads per sample. Library preparation and sequencing were optimized and performed at the Gulbenkian Institute for Molecular Medicine Genomics Unit.

FastQ reads were aligned against the mouse reference genome GRCm39 using the GENCODE vM27 annotation to extract splice junction information (STAR; v.2.5.2a) (Dobin et al, 2013). Read summarization was performed by assigning uniquely mapped reads to genomic features using FeatureCounts (v.1.5.0-p1) (Liao et al, 2014). Gene expression tables were imported into the R programming language and environment (v.4.1.0) to perform differential gene expression and functional enrichment analyses, as well as data visualization.

Differential gene expression was performed using the DESeq2 R package (v.1.32) (Love et al, 2014). Gene expression was modeled by genotype for each organ, which included the following factors: tdTLysMFthfl/fl, tdTLysMFthLysMΔ/ΔFthfl/fl or tdTLysMFthLysMΔ/ΔFthR26Δ/Δ bone marrow chimeras. Genes not expressed or with fewer than 10 counts across the samples were removed, leaving 22,529 (liver), 23,327 (WAT) and 29,821 (heart) genes for downstream differential gene expression analysis. We subsequently ran the function DESeq to estimate the size factors (by estimateSizeFactors), dispersion (by estimateDispersions) and fit a binomial GLM fitting for βi coefficient and Wald statistics (by nbinomWaldTest). Pairwise comparisons tested with the function results (alpha = 0.05), were: 1) tdTLysMFthfl/fl, vs. tdTLysMFthLysMΔ/ΔFthfl/fl; 2) tdTLysMFthfl/fl vs. tdTLysMFthLysMΔ/ΔFthR26Δ/Δ and 3) tdTLysMFthLysMΔ/ΔFthfl/fl vs. tdTLysMFthLysMΔ/ΔFthR26Δ/Δ. In addition, the log2 fold change for each pairwise comparison was shrunken with the function lfcShrink using the algorithm ashr (v.2.2–47) (Stephens, 2016). Differentially expressed genes were considered for genes with an adjusted P value < 0.05 and an absolute log2 fold change >0. Normalized gene expression counts were obtained with the function counts using the option normalized = TRUE. Regularized log transformed gene expression counts were obtained with rlog, using the option blind = TRUE. Ensembl gene ids were converted into gene symbols from Ensembl (v.107) by using the mouse reference (GRCm39) database with biomaRt R package (v.2.48.2)(Durinck et al, 2005; Durinck et al, 2009). All scatterplots, including volcano plots, were done with the ggplot2 R package (v.3.3.5)(Wickham, 2016). Functional enrichment analysis was performed with the gprofiler2 R package (v.0.2.1)(Kolberg et al, 2020). Enrichment was performed using the function gost based on the list of up- or downregulated genes (genes with an adjusted P value < 0.05 and a log2 fold change >0 or <0), between each pairwise comparison (independently), against annotated genes (domain_scope = “annotated”) of the organism Mus musculus (organism = “mmusculus”). Gene lists were sorted according to adjusted p value (ordered_query = TRUE) to generate GSEA (Gene Set Enrichment Analysis) style p values. Only statistically significant (user_threshold = 0.05) enriched functions are returned (significant = TRUE) after multiple testing corrections with the default method g:SCS (correction_method = “analytical”). The gprofiler2 queries were run against all the default functional databases for mouse which include: Gene Ontology (GO:MF, GO:BP, GO:CC), KEGG (KEGG), Reactome (REAC), TRANSFAC (TF), miRTarBase (MIRNA), Human phenotype ontology (HP), WikiPathways (WP), and CORUM (CORUM). For future reference, gprofiler2 was performed using database versions Ensembl 107, Ensembl genomes 54 (database updated on 12/07/2022). For STRING database network analysis, genes contained within enriched gene sets associated related to mitochondrial proteins, mitochondrial ribosome, electron transport chain, respirasome were merged and uploaded to the STRING database (v11.5) (Shannon et al, 2003) and queried for known protein-protein interactions (organism: Mus musculus; interaction score >0.4). The resulting network was imported into Cytoscape (v.3.9.0) (Shannon et al, 2003) for network layout design.

Thermal imaging

BAT and tail temperatures were measured in mice that were allowed to move freely in a cage, using an infrared camera, (FLIR E96 Compact-Infrared-Thermal-Imaging-Camera; FLIR Systems). At least 2 days prior, mice were anesthetized (1–2% Isoflurane) and the interscapular area was shaved. Acquired images were analyzed using FLIR Tools software (v6.4) and individual BAT and tail temperatures were taken as the maximum temperature measured at the interscapular area or tail base, respectively.

Metabolic phenotyping

Promethion Core (Sable Systems, USA) was used to measure indirect calorimetry. Fth deletion was induced via tamoxifen administration as described above and 7 (early onset) or 20 (late onset) days post-tamoxifen treatment, bone marrow chimeras were placed in metabolic cages for metabolic phenotyping. Mice were kept on a 14/10 h light/dark cycle with controlled temperature and humidity. Recording continued for the following 5–6 days. The system consists of a standard GM-500 cage with a food hopper and a water bottle connected to load cells (2 mg precision) with 1 Hz rate data collection. Additionally, the cage contains a red house enrichment. Ambulatory activity was monitored at 1 Hz rate using an XY beam break array (1 cm spacing). Oxygen, carbon dioxide and water vapor were measured using a CGF unit (Sable Systems). This multiplexed system operated in pull-mode. Air flow was measured and controlled by the CGF (Sable Systems) with a set flow rate of 2 L/min. Oxygen consumption and carbon dioxide production were reported in milliliters per minute (mL/min). Energy expenditure was calculated using the Weir equation and Respiratory Exchange Ratio (RER) was calculated as the ratio of VCO2/VO2. Raw data was processed using Macro Interpreter v2.41 (Sable Systems), as described (Ramos et al, 2022).

Fluorescence microscopy

Bone marrow chimeras were treated with tamoxifen to induce Fth deletion, as described above. 21 days post tamoxifen treatment, bone marrow chimeras were euthanized and transcardially perfused with 20 mL cold PBS, followed by prefusion with 10 mL 4%PFA (Alfa Aesar cat. #043368-9 M) in PBS. Livers were collected and fixed in 4%PFA in PBS overnight in the dark. Organs were then washed in PBS overnight and embedded in 4% low-melting point agarose (Invitrogen cat. #15517-014). Tissue sections (100 µm) were obtained using a Leica Vibratome VT 1000 S (Leica Biosystems) and placed in Eppendorf tubes with PBDO permeabilization solution (1% Bovine Serum Albumin; 1% DMSO; 0.6% Triton X-100 in PBS; overnight; 4 °C). Tissue slices were then incubated with primary Abs (overnight; 4 °C): anti-FTH (1:100, Cell Signalling cat. #4393), Anti-V5 (1:200, Abcam cat. # AB9137) and Anti-CD68 (1:200, BioLegend cat. #123102). Tissue slices were further washed with PBDO (overnight; 4 °C) and were then incubated (1:500; overnight; 4 °C) with secondary antibodies: Cy5-conjugated donkey anti-goat IgG antibody (Jackson IR; cat. #705-175-147), Alexa 568 conjugated anti-rabbit (ThermoFisher, cat. #A-11011) and Alexa 568 conjugated anti-rat (ThermoFisher, cat. #A-11077). Tissue slices were washed once more with PBDO (overnight, 4 °C) and mounted with Mowiol mounting medium with 10 µg/mL of DAPI (Merck, cat. #81381-50 G). Images were then acquired on a Leica SP5 confocal-based and on a Leica DM6000 inverted microscope (458, 476, 488, 514, 561 and 633 nm lasers).

Transmission electron microscopy

Animals were euthanized and perfused with fixating media (2% formaldehyde (EMS), 2.5% glutaraldehyde (Polysciences) in 0.1 M Phosphate Buffer (PB); pH 7.4). Organs were dissected and immersed in the same primary fixative (1 h; RT). Further processing was achieved using a PELCO BioWave Microwave Processor at 23 °C, restricted by a PELCO SteadyTemp Pro. Samples were additionally fixed in the primary fixative using a time-sequence of 7 × 2 min with ON and OFF sequential cycles of 0 and 100 W irradiating power in vacuum and rinsed with PB before post-fixation in 1% (v/v) osmium tetroxide (®EMS) with 1% (w/v) potassium ferrocyanide (®Sigma-Aldrich) in PB for 8 × 2 min, also with ON and OFF sequential cycles of 100 W in vacuum. Subsequently, samples were washed with PB and dH2O twice and immersed in 1% (w/v) tannic acid (®EMS) followed by en-bloc staining with 0.5% (w/v) uranyl acetate. Both steps were made using a time-sequence of 7 × 2 min with ON and OFF sequential cycles of 0 and 150 W irradiating power in vacuum. Between the steps, samples were rinsed with dH2O. Dehydration was done in a graded ethanol series of 30%, 50%, 75%, 90% and 100%, for 40 s at 150 W each. EPON resin (®EMS), 25%, 50%, 75% and 100% was infiltrated, for 3 min at 250 W in vacuum each step, and cured overnight, at 60 °C. Sections of 70 nm were obtained on a Leica UC7 and mounted on palladium-copper grids coated with 1% (w/v) formvar (®Agar Scientific) in chloroform (®VWR). Sections were stained with 1% (w/v) uranyl acetate and Reynolds lead citrate for 5 min each and imaged on an FEI Tecnai G2 Spirit BioTWIN Transmission Electron Microscope operating at 120 keV.

Mitochondria quantification

Livers, WAT and heart were harvested and snap frozen as described above. A piece of the tissue was cut and placed into lysis buffer (100 mM NaCl, 10 mM EDTA, 0.5% SDS and 20 mM Tris-HCl, pH 7.4) and homogenized in a Qiagen TissueLyser II using tungsten carbide beads. Upon homogenization, an equal volume of Phenol:Chloroform:Isoamyl Alcohol (25:24:1, v/v) was added. DNA, present in the aqueous phase, was precipitated using 1vol. isopropanol and 0.3 M sodium acetate for 3 h at −20 °C. The isolated DNA was used to perform the quantification of mitochondrial DNA (mtDNA) as compared to nuclear DNA (nDNA) using a qRT-PCR-based method, similar to what was previously described (Blankenhaus et al, 2019; Quiros et al, 2017). Briefly, qRT-PCR was performed using 20 ng of DNA and SYBR Green Master Mix (Applied Biosystems, Foster City, CA, USA), in duplicate on a ABI QuantStudio - 384 Real-Time PCR System (Applied Biosystems), under the following conditions: 50 °C/2 min and 95 °C/5 min (Hold stage), 45 cycles/95 °C/10 s, annealing at 60 °C/30 s, and elongation 72 °C/20 s, followed by melting curve: 95 °C for 15 s, 60 °C for 1 min, and gradual increase in temperature up to 95 °C. Primers for NADH-ubiquinone oxidoreductase chain 1 encoded by the mitochondrial gene MT-Nd1 (Nd1) and for the nuclear encoded hexokinase 2 gene (Hk2) (Blankenhaus et al, 2019; Quiros et al, 2017) are available in “Reagents and Tools Table”. Mitochondria number per cell was calculated by the ratio of mRNA expression of the single copy mitochondrial gene Nd1 and the single copy nuclear gene Hk2.

Statistical analysis

Statistical analysis was conducted using GraphPad Prism v8.4.2 software. All data are displayed as means ± standard deviation of the mean (SD) unless otherwise noted. Sample sizes were estimated based on previous experience and publications, using the Power/sample-size calculator (http://www.stat.ubc.ca/~rollin/stats/ssize/n2.html). Statistical comparison between two groups was performed using either a Student’s T test or Mann–Whitney U test. Groups of three or more were analyzed by one-way analysis of variance (ANOVA), Welch ANOVA or the Kruskal–Wallis test, using Tukey’s range test, Dunnett’s T3 test, or Dunn’s test for multiple comparison correction, respectively. Survival was assessed using a log-rank (Mantel–Cox) test. No experiment blinding was performed. Statistical outliers (ROUT Q = 1%) were excluded from analysis. Statistical parameters for each experiment can be found within the corresponding figure legends. P values for each statistical comparison can be found in Appendix Table S1.

Supplementary information

Appendix (5.5MB, pdf)
Peer Review File (1.6MB, pdf)
Source data Fig. 1 (74.8KB, zip)
Source data Fig. 2 (2.3MB, zip)
Source data Fig. 3 (178.8KB, zip)
Source data Fig. 4 (53.8MB, zip)
Source data Fig. 5 (13.6MB, zip)
Source data Fig. 6 (41.9MB, zip)
Source data Fig. 7 (17.9KB, zip)
Source data Fig. 8 (3.9MB, zip)
Expanded View Figures (7.1MB, pdf)

Acknowledgements

The authors are indebted to all members of the Inflammation laboratory (GIMM) for insightful technical and intellectual contributions, to Erin M. Tranfield and Ana L. Vinagre at the Electron Microscopy Unit (GIMM), to the flow cytometry, genomics and animal facility staff at GIMM. MPS was supported by Gulbenkian, ‘la Caixa’ Foundation (HR18-00502) and Fundação para a Ciência e a Tecolnogia (FCT, PTDC/IMI-IMU/5723/2014; FEDER/29411/2017; PTDC/MED-FSL/4681/2020; and 2022.02426.PTDC), Oeiras-ERC Frontier Research Incentive Awards, SymbNET Research Grants (H2020-WIDESPREAD-2020-5-952537), Deutsche Forschungsgemeinschaft Cluster of Excellence “Balance of the Microverse” (DFG, EXC 2051; 390713860) and Congento (LISBOA-01-0145-FEDER-022170). RM was supported by an EMBO long-term fellowship (ALTF290-2017ARC), Marie Skłodowska-Curie Research Fellowship (MSCA-IF-EF-ST-753236) and Fundação para a Ciência e a Tecnologia (FCT, 2021.03494.CEECIND/CP1674/CT0004). BB and SC were supported in part by European Community 7th Framework 294709-DAMAGECONTROL ERC-2011-AdG to MPS, FB by Marie Skłodowska-Curie Research Fellowship (REGDAM 707998). SW was supported by the German Ministry of Education and Research (BMBF; grant 01 EO 1502) via the Jena Center of Sepsis Control and Care. MM was supported by Fundação para a Ciência e a Tecnologia (FCT, UI/BD/152257/2021). QW was supported by a Marie Skłodowska-Curie Research Fellowship (MSCA-IF2019-892773), the International Postdoctoral Exchange Fellowship Program from the People´s Republic of China (20190090), and the National Natural Science Foundation of China (32171166, 82030003).

Expanded view

Author contributions

Rui Martins: Conceptualization; Formal analysis; Supervision; Investigation; Visualization; Methodology; Writing—original draft; Writing—review and editing. Birte Blankenhaus: Conceptualization; Validation; Investigation; Methodology. Faouzi Braza: Investigation; Methodology. Miguel Mesquita: Investigation; Methodology. Pedro Ventura: Investigation. Sumnima Singh: Investigation; Methodology. Sebastian Weis: Investigation; Methodology. Maria Pires: Investigation. Sara Pagnotta: Investigation. Qian Wu: Investigation. Sílvia Cardoso: Investigation. Elisa Jentho: Investigation. Ana Figueiredo: Investigation. Pedro Faísca: Investigation. Ana Nóvoa: Resources. Vanessa Alexandra Morais: Resources. Stefanie K Wculek: Resources. David Sancho: Resources. Moises Mallo: Resources. Miguel P Soares: Conceptualization; Resources; Supervision; Funding acquisition; Visualization; Writing—original draft; Project administration; Writing—review and editing.

Source data underlying figure panels in this paper may have individual authorship assigned. Where available, figure panel/source data authorship is listed in the following database record: biostudies:S-SCDT-10_1038-S44318-025-00622-x.

Data availability

Data from RNA sequencing studies are available at GEO database GSE292630 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE292630; Figs. 7A–D,  EV6E,F, Appendix Fig. S4A–C, EV7A–D).

The source data of this paper are collected in the following database record: biostudies:S-SCDT-10_1038-S44318-025-00622-x.

Disclosure and competing interests statement

The authors declare no competing interests.

Footnotes

These authors contributed equally: Rui Martins, Birte Blankehaus.

Supplementary information

Expanded view data, supplementary information, appendices are available for this paper at 10.1038/s44318-025-00622-x.

References

  1. Adler M, Chavan AR, Medzhitov R (2023) Tissue biology: in search of a new paradigm. Annu Rev Cell Dev Biol 39:67–89 [DOI] [PubMed] [Google Scholar]
  2. Al Amir Dache Z, Thierry AR (2023) Mitochondria-derived cell-to-cell communication. Cell Rep 42:112728 [DOI] [PubMed] [Google Scholar]
  3. Amit I, Winter DR, Jung S (2016) The role of the local environment and epigenetics in shaping macrophage identity and their effect on tissue homeostasis. Nat Immunol 17:18–25 [DOI] [PubMed] [Google Scholar]
  4. Beard JL, Borel MJ, Derr J (1990) Impaired thermoregulation and thyroid function in iron-deficiency anemia. Am J Clin Nutr 52:813–819 [DOI] [PubMed] [Google Scholar]
  5. Ben Zichri-David S, Shkuri L, Ast T (2025) Pulling back the mitochondria’s iron curtain. NPJ Metab Health Dis 3:6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Berberat PO, Katori M, Kaczmarek E, Anselmo D, Lassman C, Ke B, Shen X, Busuttil RW, Yamashita K, Csizmadia E et al (2003) Heavy chain ferritin acts as an antiapoptotic gene that protects livers from ischemia reperfusion injury. FASEB J 17:1724–1726 [DOI] [PubMed] [Google Scholar]
  7. Blankenhaus B, Braza F, Martins R, Bastos-Amador P, Gonzalez-Garcia I, Carlos AR, Mahu I, Faisca P, Nunes JM, Ventura P et al (2019) Ferritin regulates organismal energy balance and thermogenesis. Mol Metab 24:64–79 [DOI] [PMC free article] [PubMed]
  8. Bolisetty S, Zarjou A, Hull TD, Traylor AM, Perianayagam A, Joseph R, Kamal AI, Arosio P, Soares MP, Jeney V et al (2015) Macrophage and epithelial cell H-ferritin expression regulates renal inflammation. Kidney Int 88:95–108 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bonnardel J, T’Jonck W, Gaublomme D, Browaeys R, Scott CL, Martens L, Vanneste B, De Prijck S, Nedospasov SA, Kremer A et al (2019) Stellate cells, hepatocytes, and endothelial cells imprint the Kupffer cell identity on monocytes colonizing the liver macrophage niche. Immunity 51:638–654.e639 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Borcherding N, Brestoff JR (2023) The power and potential of mitochondria transfer. Nature 623:283–291 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Boring L, Gosling J, Chensue SW, Kunkel SL, Farese JrRV, Broxmeyer HE, Charo IF (1997) Impaired monocyte migration and reduced type 1 (Th1) cytokine responses in C-C chemokine receptor 2 knockout mice. J Clin Invest 100:2552–2561 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Brestoff JR, Singh KK, Aquilano K, Becker LB, Berridge MV, Boilard E, Caicedo A, Crewe C, Enríquez JA, Gao J et al (2025) Recommendations for mitochondria transfer and transplantation nomenclature and characterization. Nat Metab 7:53–67 [DOI] [PubMed] [Google Scholar]
  13. Brestoff JR, Wilen CB, Moley JR, Li Y, Zou W, Malvin NP, Rowen MN, Saunders BT, Ma H, Mack MR et al (2021) Intercellular mitochondria transfer to macrophages regulates white adipose tissue homeostasis and is impaired in obesity. Cell Metab 33:270–282.e278 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Brigham D, Beard J (1996) Iron and thermoregulation: a review. Crit Rev Food Sci Nutr 36:747–763 [DOI] [PubMed] [Google Scholar]
  15. Cannon B, Nedergaard J (2004) Brown adipose tissue: function and physiological significance. Physiol Rev 84:277–359 [DOI] [PubMed] [Google Scholar]
  16. Casaca A, Nóvoa A, Mallo M (2016) Hoxb6 can interfere with somitogenesis in the posterior embryo through a mechanism independent of its rib-promoting activity. Development 143:437–448 [DOI] [PubMed] [Google Scholar]
  17. Cobo I, Tanaka TN, Chandra Mangalhara K, Lana A, Yeang C, Han C, Schlachetzki J, Challcombe J, Fixsen BR, Sakai M et al (2022) DNA methyltransferase 3 alpha and TET methylcytosine dioxygenase 2 restrain mitochondrial DNA-mediated interferon signaling in macrophages. Immunity 55:1386–1401.e1310 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Cohen LA, Gutierrez L, Weiss A, Leichtmann-Bardoogo Y, Zhang DL, Crooks DR, Sougrat R, Morgenstern A, Galy B, Hentze MW, Lazaro FJ, Rouault TA, Meyron-Holtz EG (2010) Serum ferritin is derived primarily from macrophages through a nonclassical secretory pathway. Blood 116:1574–84 [DOI] [PubMed]
  19. Dillmann E, Johnson DG, Martin J, Mackler B, Finch C (1979) Catecholamine elevation in iron deficiency. Am J Physiol 237:R297–R300 [DOI] [PubMed] [Google Scholar]
  20. Dixon SJ, Lemberg KM, Lamprecht MR, Skouta R, Zaitsev EM, Gleason CE, Patel DN, Bauer AJ, Cantley AM, Yang WS et al (2012) Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149:1060–1072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Durinck S, Moreau Y, Kasprzyk A, Davis S, De Moor B, Brazma A, Huber W (2005) BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis. Bioinformatics 21:3439–3440 [DOI] [PubMed] [Google Scholar]
  23. Durinck S, Spellman PT, Birney E, Huber W (2009) Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat Protoc 4:1184–1191 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Fang X, Cai Z, Wang H, Han D, Cheng Q, Zhang P, Gao F, Yu Y, Song Z, Wu Q et al (2020) Loss of cardiac ferritin H facilitates cardiomyopathy via Slc7a11-mediated ferroptosis. Circ Res 127:486–501 [DOI] [PubMed] [Google Scholar]
  25. Galy B, Conrad M, Muckenthaler M (2024) Mechanisms controlling cellular and systemic iron homeostasis. Nat Rev Mol Cell Biol 25:133–155 [DOI] [PubMed]
  26. Ganeshan K, Chawla A (2017) Warming the mouse to model human diseases. Nat Rev Endocrinol 13:458–465 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Ganeshan K, Nikkanen J, Man K, Leong YA, Sogawa Y, Maschek JA, Van Ry T, Chagwedera DN, Cox JE, Chawla A (2019) Energetic trade-offs and hypometabolic states promote disease tolerance. Cell 177:399–413.e312 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Ginhoux F, Greter M, Leboeuf M, Nandi S, See P, Gokhan S, Mehler MF, Conway SJ, Ng LG, Stanley ER et al (2010) Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science 330:841–845 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Godinho-Silva C, Cardoso F, Veiga-Fernandes H (2019) Neuro-immune cell units: a new paradigm in physiology. Annu Rev Immunol 37:19–46 [DOI] [PubMed] [Google Scholar]
  30. Gomez Perdiguero E, Klapproth K, Schulz C, Busch K, Azzoni E, Crozet L, Garner H, Trouillet C, de Bruijn MF, Geissmann F et al (2015) Tissue-resident macrophages originate from yolk-sac-derived erythro-myeloid progenitors. Nature 518:547–551 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Gosselin D, Link VM, Romanoski CE, Fonseca GJ, Eichenfield DZ, Spann NJ, Stender JD, Chun HB, Garner H, Geissmann F et al (2014) Environment drives selection and function of enhancers controlling tissue-specific macrophage identities. Cell 159:1327–1340 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Gozzelino R, Andrade BB, Larsen R, Luz NF, Vanoaica L, Seixas E, Coutinho A, Cardoso S, Rebelo S, Poli M et al (2012) Metabolic adaptation to tissue iron overload confers tolerance to malaria. Cell Host Microbe 12:693–704 [DOI] [PubMed] [Google Scholar]
  33. Gozzelino R, Soares MP (2014) Coupling heme and iron metabolism via ferritin H chain. Antioxid Redox Signal 20:1754–1769 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Guilliams M, Mildner A, Yona S (2018) Developmental and functional heterogeneity of monocytes. Immunity 49:595–613 [DOI] [PubMed] [Google Scholar]
  35. Haldar M, Kohyama M, So AY, Kc W, Wu X, Briseno CG, Satpathy AT, Kretzer NM, Arase H, Rajasekaran NS et al (2014) Heme-mediated SPI-C induction promotes monocyte differentiation into iron-recycling macrophages. Cell 156:1223–1234 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Harris RBS (2013) Contribution made by parabiosis to the understanding of energy balance regulation. Biochim et Biophys Acta ((BBA)) - Mol Basis Dis 1832:1449–1455 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Harrison PM, Arosio P (1996) Ferritins - molecular properties, iron storage function and cellular regulation. Biochim et Biophys Acta - Bioenerg 1275:161–203 [DOI] [PubMed] [Google Scholar]
  38. He B, Yu H, Liu S, Wan H, Fu S, Liu S, Yang J, Zhang Z, Huang H, Li Q, Wang F, Jiang Z, Liu Q, Jiang H (2022) Mitochondrial cristae architecture protects against mtDNA release and inflammation. Cell Rep 41:111774 [DOI] [PubMed]
  39. Heine M, Fischer AW, Schlein C, Jung C, Straub LG, Gottschling K, Mangels N, Yuan Y, Nilsson SK, Liebscher G et al (2018) Lipolysis triggers a systemic insulin response essential for efficient energy replenishment of activated brown adipose tissue in mice. Cell Metab 28:644–655.e644 [DOI] [PubMed] [Google Scholar]
  40. Hulsmans M, Clauss S, Xiao L, Aguirre AD, King KR, Hanley A, Hucker WJ, Wulfers EM, Seemann G, Courties G et al (2017) Macrophages facilitate electrical conduction in the heart. Cell 169:510–522.e520 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Ikeda Y, Watanabe H, Shiuchi T, Hamano H, Horinouchi Y, Imanishi M, Goda M, Zamami Y, Takechi K, Izawa-Ishizawa Y et al (2020) Deletion of H-ferritin in macrophages alleviates obesity and diabetes induced by high-fat diet in mice. Diabetologia 63:1588–1602 [DOI] [PubMed] [Google Scholar]
  42. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337:816–21 [DOI] [PMC free article] [PubMed]
  43. Joffin N, Gliniak CM, Funcke J-B, Paschoal VA, Crewe C, Chen S, Gordillo R, Kusminski CM, Oh DY, Geldenhuys WJ et al (2022) Adipose tissue macrophages exert systemic metabolic control by manipulating local iron concentrations. Nat Metab 4:1474–1494 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Jung S, Aliberti J, Graemmel P, Sunshine MJ, Kreutzberg GW, Sher A, Littman DR (2000) Analysis of fractalkine receptor CX(3)CR1 function by targeted deletion and green fluorescent protein reporter gene insertion. Mol Cell Biol 20:4106–4114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Kamran P, Sereti KI, Zhao P, Ali SR, Weissman IL, Ardehali R (2013) Parabiosis in mice: a detailed protocol. J Vis Exp 80:50556 [DOI] [PMC free article] [PubMed]
  46. Ko JH, Kim HJ, Jeong HJ, Lee HJ, Oh JY (2020) Mesenchymal stem and stromal cells harness macrophage-derived amphiregulin to maintain tissue homeostasis. Cell Rep 30:3806–3820.e3806 [DOI] [PubMed] [Google Scholar]
  47. Kolberg L, Raudvere U, Kuzmin I, Vilo J, Peterson H (2020) gprofiler2 - an R package for gene list functional enrichment analysis and namespace conversion toolset g:Profiler. F1000Research 9:ELIXIR-709 [DOI] [PMC free article] [PubMed]
  48. Larsson NG, Wang J, Wilhelmsson H, Oldfors A, Rustin P, Lewandoski M, Barsh GS, Clayton DA (1998) Mitochondrial transcription factor A is necessary for mtDNA maintenance and embryogenesis in mice. Nat Genet 18:231–236 [DOI] [PubMed] [Google Scholar]
  49. Lavin Y, Winter D, Blecher-Gonen R, David E, Keren-Shaul H, Merad M, Jung S, Amit I (2014) Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment. Cell 159:1312–1326 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Lazarov T, Juarez-Carreno S, Cox N, Geissmann F (2023) Physiology and diseases of tissue-resident macrophages. Nature 618:698–707 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30:923–930 [DOI] [PubMed] [Google Scholar]
  52. Lopez-Moyado IF, Ko M, Hogan PG, Rao A (2024) TET enzymes in the immune system: from DNA demethylation to immunotherapy, inflammation, and cancer. Annu Rev Immunol 42:455–488 [DOI] [PubMed] [Google Scholar]
  53. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Lowell BB, S-Susulic V, Hamann A, Lawitts JA, Himms-Hagen J, Boyer BB, Kozak LP, Flier JS (1993) Development of obesity in transgenic mice after genetic ablation of brown adipose tissue. Nature 366:740–742 [DOI] [PubMed] [Google Scholar]
  55. Lu B, Guo S, Zhao J, Wang X, Zhou B (2024) Adipose knockout of H-ferritin improves energy metabolism in mice. Mol Metab 80:101871 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Lukaski HC, Hall CB, Nielsen FH (1990) Thermogenesis and thermoregulatory function of iron-deficient women without anemia. Aviat Space Environ Med 61:913–920 [PubMed] [Google Scholar]
  57. Martins R, Maier J, Gorki AD, Huber KV, Sharif O, Starkl P, Saluzzo S, Quattrone F, Gawish R, Lakovits K et al (2016) Heme drives hemolysis-induced susceptibility to infection via disruption of phagocyte functions. Nat Immunol 17:1361–1372 [DOI] [PubMed] [Google Scholar]
  58. Meizlish ML, Franklin RA, Zhou X, Medzhitov R (2021) Tissue homeostasis and inflammation. Annu Rev Immunol 39:557–581 [DOI] [PubMed] [Google Scholar]
  59. Meyron-Holtz EG, Moshe-Belizowski S, Cohen LA (2011) A possible role for secreted ferritin in tissue iron distribution. J Neural Transm (Vienna) 118:337–47 [DOI] [PubMed]
  60. Moura Silva H, Kitoko JZ, Queiroz CP, Kroehling L, Matheis F, Yang KL, Reis BS, Ren-Fielding C, Littman DR, Bozza MT et al (2021) c-MAF-dependent perivascular macrophages regulate diet-induced metabolic syndrome. Sci Immunol 6:eabg7506 [DOI] [PubMed] [Google Scholar]
  61. Muchowska KB, Varma SJ, Moran J (2019) Synthesis and breakdown of universal metabolic precursors promoted by iron. Nature 569:104–107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Munro HN, Linder MC (1978) Ferritin: structure, biosynthesis, and role in iron metabolism. Physiol Rev 58:317–396 [DOI] [PubMed] [Google Scholar]
  63. Murphy MP, O’Neill LAJ (2024) A break in mitochondrial endosymbiosis as a basis for inflammatory diseases. Nature 626:271–279 [DOI] [PubMed] [Google Scholar]
  64. Nakai R, Varnum S, Field RL, Shi H, Giwa R, Jia W, Krysa SJ, Cohen EF, Borcherding N, Saneto RP et al (2024) Mitochondria transfer-based therapies reduce the morbidity and mortality of Leigh syndrome. Nat Metab 6:1886–1896 [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Nicolás-Ávila JA, Lechuga-Vieco AV, Esteban-Martínez L, Sánchez-Díaz M, Díaz-García E, Santiago DJ, Rubio-Ponce A, Li JL, Balachander A, Quintana JA et al (2020) A network of macrophages supports mitochondrial homeostasis in the heart. Cell 183:94–109.e123 [DOI] [PubMed] [Google Scholar]
  66. Nicolás-Ávila JA, Pena-Couso L, Muñoz-Cánoves P, Hidalgo A (2022) Macrophages, metabolism and heterophagy in the heart. Circ Res 130:418–431 [DOI] [PubMed] [Google Scholar]
  67. Nobs SP, Kopf M (2021) Tissue-resident macrophages: guardians of organ homeostasis. Trends Immunol 42:495–507 [DOI] [PubMed] [Google Scholar]
  68. Oikawa D, Akai R, Tokuda M, Iwawaki T (2012) A transgenic mouse model for monitoring oxidative stress. Sci Rep 2:229 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Okabe Y, Medzhitov R (2015) Tissue biology perspective on macrophages. Nat Immunol 17:9–17 [DOI] [PubMed] [Google Scholar]
  70. Pacher P, Nagayama T, Mukhopadhyay P, Batkai S, Kass DA (2008) Measurement of cardiac function using pressure-volume conductance catheter technique in mice and rats. Nat Protoc 3:1422–1434 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Pan W, Zhu S, Qu K, Meeth K, Cheng J, He K, Ma H, Liao Y, Wen X, Roden C et al (2017) The DNA methylcytosine dioxygenase Tet2 sustains immunosuppressive function of tumor-infiltrating myeloid cells to promote melanoma progression. Immunity 47:284–297.e285 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Pham AH, McCaffery JM, Chan DC (2012) Mouse lines with photo-activatable mitochondria to study mitochondrial dynamics. Genesis 50:833–843 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Pham CG, Bubici C, Zazzeroni F, Papa S, Jones J, Alvarez K, Jayawardena S, De Smaele E, Cong R, Beaumont C et al (2004) Ferritin heavy chain upregulation by NF-kappaB inhibits TNFalpha-induced apoptosis by suppressing reactive oxygen species. Cell 119:529–542 [DOI] [PubMed] [Google Scholar]
  74. Pirzgalska RM, Seixas E, Seidman JS, Link VM, Sanchez NM, Mahu I, Mendes R, Gres V, Kubasova N, Morris I et al (2017) Sympathetic neuron-associated macrophages contribute to obesity by importing and metabolizing norepinephrine. Nat Med 23:1309–1318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Quiros PM, Goyal A, Jha P, Auwerx J (2017) Analysis of mtDNA/nDNA Ratio in Mice. Curr Protoc Mouse Biol 7:47–54 [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Ramos S, Ademolue TW, Jentho E, Wu Q, Guerra J, Martins R, Pires G, Weis S, Carlos AR, Mahú I et al (2022) A hypometabolic defense strategy against malaria. Cell Metab 34:1183–1200 [DOI] [PubMed]
  77. Ramos S, Carlos AR, Sundaram B, Jeney V, Ribeiro A, Gozzelino R, Bank C, Gjini E, Braza F, Martins R et al (2019) Renal control of disease tolerance to malaria. Proc Natl Acad Sci USA 116:5681–5686 [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Reitman ML (2018) Of mice and men – environmental temperature, body temperature, and treatment of obesity. FEBS Lett 592:2098–2107 [DOI] [PubMed] [Google Scholar]
  79. Romero AR, Mu A, Ayres JS (2022) Adipose triglyceride lipase mediates lipolysis and lipid mobilization in response to iron-mediated negative energy balance. iScience 25:103941 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Rosina M, Ceci V, Turchi R, Chuan L, Borcherding N, Sciarretta F, Sánchez-Díaz M, Tortolici F, Karlinsey K, Chiurchiù V et al (2022) Ejection of damaged mitochondria and their removal by macrophages ensure efficient thermogenesis in brown adipose tissue. Cell Metab 34:533–548.e512 [DOI] [PMC free article] [PubMed] [Google Scholar]
  81. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504 [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Silva HM, Bafica A, Rodrigues-Luiz GF, Chi J, Santos PDA, Reis BS, Hoytema van Konijnenburg DP, Crane A, Arifa RDN, Martin P et al (2019) Vasculature-associated fat macrophages readily adapt to inflammatory and metabolic challenges. J Exp Med 216:786–806 [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Soares MP, Hamza I (2016) Macrophages and iron metabolism. Immunity 44:492–504 [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Stearns SC, Medzhitov R (2015) Evolutionary medicine. Oxford University Press
  85. Stephens M (2016) False discovery rates: a new deal. Biostatistics 18:275–294 [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Swirski FK, Nahrendorf M, Etzrodt M, Wildgruber M, Cortez-Retamozo V, Panizzi P, Figueiredo JL, Kohler RH, Chudnovskiy A, Waterman P et al (2009) Identification of splenic reservoir monocytes and their deployment to inflammatory sites. Science 325:612–616 [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Teh MR, Armitage AE, Drakesmith H (2024) Why cells need iron: a compendium of iron utilisation. Trends Endocrinol Metab 35:1026–1049 [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Trzebanski S, Kim JS, Larossi N, Raanan A, Kancheva D, Bastos J, Haddad M, Solomon A, Sivan E, Aizik D et al (2024) Classical monocyte ontogeny dictates their functions and fates as tissue macrophages. Immunity 57:1710–1712 [DOI] [PubMed] [Google Scholar]
  89. Tsou CL, Peters W, Si Y, Slaymaker S, Aslanian AM, Weisberg SP, Mack M, Charo IF (2007) Critical roles for CCR2 and MCP-3 in monocyte mobilization from bone marrow and recruitment to inflammatory sites. J Clin Invest 117:902–909 [DOI] [PMC free article] [PubMed] [Google Scholar]
  90. van Furth R, Cohn ZA (1968) The origin and kinetics of mononuclear phagocytes. J Exp Med 128:415–435 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. van Furth R, Diesselhoff-den Dulk MM (1984) Dual origin of mouse spleen macrophages. J Exp Med 160:1273–1283 [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Veglia F, Sanseviero E, Gabrilovich DI (2021) Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity. Nat Rev Immunol 21:485–498 [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Veiga-Fernandes H, Mucida D (2016) Neuro-immune interactions at barrier surfaces. Cell 165:801–811 [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Wagner M, Koester H, Deffge C, Weinert S, Lauf J, Francke A, Lee J, Braun-Dullaeus RC, Herold J (2014) Isolation and intravenous injection of murine bone marrow derived monocytes. JoVE 94:52347 [DOI] [PMC free article] [PubMed]
  95. Wang X, Wu Q, Zhong M, Chen Y, Wang Y, Li X, Zhao W, Ge C, Wang X, Yu Y et al (2024) Adipocyte-derived ferroptotic signaling mitigates obesity. Cell Metab 37:673–691 [DOI] [PubMed]
  96. Wculek SK, Heras-Murillo I, Mastrangelo A, Mananes D, Galan M, Miguel V, Curtabbi A, Barbas C, Chandel NS, Enriquez JA et al (2023) Oxidative phosphorylation selectively orchestrates tissue macrophage homeostasis. Immunity 56:516–530.e519 [DOI] [PubMed] [Google Scholar]
  97. Weinberg SE, Singer BD, Steinert EM, Martinez CA, Mehta MM, Martinez-Reyes I, Gao P, Helmin KA, Abdala-Valencia H, Sena LA et al (2019) Mitochondrial complex III is essential for suppressive function of regulatory T cells. Nature 565:495–499 [DOI] [PMC free article] [PubMed] [Google Scholar]
  98. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag New York
  99. Winn NC, Volk KM, Hasty AH (2020) Regulation of tissue iron homeostasis: the macrophage “ferrostat”. JCI Insight 5:e132964 [DOI] [PMC free article] [PubMed]
  100. Winterbourn CC (1995) Toxicity of iron and hydrogen peroxide: the Fenton reaction. Toxicol Lett 82-83:969–974 [DOI] [PubMed] [Google Scholar]
  101. Wolf Y, Boura-Halfon S, Cortese N, Haimon Z, Sar Shalom H, Kuperman Y, Kalchenko V, Brandis A, David E, Segal-Hayoun Y et al (2017) Brown-adipose-tissue macrophages control tissue innervation and homeostatic energy expenditure. Nat Immunol 18:665–674 [DOI] [PMC free article] [PubMed] [Google Scholar]
  102. Wu Q, Carlos AR, Braza F, Bergman ML, Kitoko JZ, Bastos-Amador P, Cuadrado E, Martins R, Oliveira BS, Martins VC et al (2024) Ferritin heavy chain supports stability and function of the regulatory T cell lineage. EMBO J 43:1445–1483 [DOI] [PMC free article] [PubMed] [Google Scholar]
  103. Wu Q, Sacomboio E, Valente de Souza L, Martins R, Kitoko J, Cardoso S, Ademolue TW, Paixao T, Lehtimaki J, Figueiredo A et al (2023) Renal control of life-threatening malarial anemia. Cell Rep 42:112057 [DOI] [PubMed] [Google Scholar]
  104. Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL (2012) Primer-BLAST: a tool to design target-specific primers for polymerase chain reaction. BMC Bioinforma 13:134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  105. Ye Q, Trivedi M, Zhang Y, Bohlke M, Alsulimani H, Chang J, Maher T, Deth R, Kim J (2019) Brain iron loading impairs DNA methylation and alters GABAergic function in mice. FASEB J 33:2460–2471 [DOI] [PMC free article] [PubMed] [Google Scholar]
  106. Yona S, Kim KW, Wolf Y, Mildner A, Varol D, Breker M, Strauss-Ayali D, Viukov S, Guilliams M, Misharin A et al (2013) Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity 38:79–91 [DOI] [PMC free article] [PubMed] [Google Scholar]
  107. Yook JS, You M, Kim Y, Zhou M, Liu Z, Kim YC, Lee J, Chung S (2021) The thermogenic characteristics of adipocytes are dependent on the regulation of iron homeostasis. J Biol Chem 296:100452 [DOI] [PMC free article] [PubMed] [Google Scholar]
  108. Zeng W, Pirzgalska RM, Pereira MM, Kubasova N, Barateiro A, Seixas E, Lu YH, Kozlova A, Voss H, Martins GG et al (2015) Sympathetic neuro-adipose connections mediate leptin-driven lipolysis. Cell 163:84–94 [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Zhou X, Franklin RA, Adler M, Jacox JB, Bailis W, Shyer JA, Flavell RA, Mayo A, Alon U, Medzhitov R (2018) Circuit design features of a stable two-cell system. Cell 172:744–757.e17 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix (5.5MB, pdf)
Peer Review File (1.6MB, pdf)
Source data Fig. 1 (74.8KB, zip)
Source data Fig. 2 (2.3MB, zip)
Source data Fig. 3 (178.8KB, zip)
Source data Fig. 4 (53.8MB, zip)
Source data Fig. 5 (13.6MB, zip)
Source data Fig. 6 (41.9MB, zip)
Source data Fig. 7 (17.9KB, zip)
Source data Fig. 8 (3.9MB, zip)
Expanded View Figures (7.1MB, pdf)

Data Availability Statement

Data from RNA sequencing studies are available at GEO database GSE292630 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE292630; Figs. 7A–D,  EV6E,F, Appendix Fig. S4A–C, EV7A–D).

The source data of this paper are collected in the following database record: biostudies:S-SCDT-10_1038-S44318-025-00622-x.


Articles from The EMBO Journal are provided here courtesy of Nature Publishing Group

RESOURCES