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. 2022 Oct 20;11:e76744. doi: 10.7554/eLife.76744

Enriched dietary saturated fatty acids induce trained immunity via ceramide production that enhances severity of endotoxemia and clearance of infection

Amy L Seufert 1, James W Hickman 1, Ste K Traxler 1, Rachael M Peterson 1, Trent A Waugh 1, Sydney J Lashley 2, Natalia Shulzhenko 3, Ruth J Napier 2,4, Brooke A Napier 1,
Editors: Jos W van der Meer5, Jos W van der Meer6
PMCID: PMC9642993  PMID: 36264059

Abstract

Trained immunity is an innate immune memory response that is induced by a primary inflammatory stimulus that sensitizes monocytes and macrophages to a secondary pathogenic challenge, reprogramming the host response to infection and inflammatory disease. Dietary fatty acids can act as inflammatory stimuli, but it is unknown if they can act as the primary stimuli to induce trained immunity. Here we find mice fed a diet enriched exclusively in saturated fatty acids (ketogenic diet; KD) confer a hyper-inflammatory response to systemic lipopolysaccharide (LPS) and increased mortality, independent of diet-induced microbiome and hyperglycemia. We find KD alters the composition of the hematopoietic stem cell compartment and enhances the response of bone marrow macrophages, monocytes, and splenocytes to secondary LPS challenge. Lipidomics identified enhanced free palmitic acid (PA) and PA-associated lipids in KD-fed mice serum. We found pre-treatment with physiologically relevant concentrations of PA induces a hyper-inflammatory response to LPS in macrophages, and this was dependent on the synthesis of ceramide. In vivo, we found systemic PA confers enhanced inflammation and mortality in response to systemic LPS, and this phenotype was not reversible for up to 7 days post-PA-exposure. Conversely, we find PA exposure enhanced clearance of Candida albicans in Rag1-/- mice. Lastly, we show that oleic acid, which depletes intracellular ceramide, reverses PA-induced hyper-inflammation in macrophages and enhanced mortality in response to LPS. These implicate enriched dietary SFAs, and specifically PA, in the induction of long-lived innate immune memory and highlight the plasticity of this innate immune reprogramming by dietary constituents.

Research organism: Mouse

Introduction

Historically, immune memory has been defined as a trait limited to the adaptive immune system; however, it is now well established that innate immune cells have the capacity for metabolic, epigenetic, and functional reprogramming that leads to long-lasting increases in host resistance to infection (Netea et al., 2020; Kleinnijenhuis et al., 2012; Quintin et al., 2012; Saeed et al., 2014). Specifically, trained immunity is an adaptation of innate host defense in vertebrates and invertebrates that results from exposure to a primary inflammatory stimulus and leads to a faster and greater response to a secondary challenge. Unlike adaptive memory responses, trained immunity does not require genome rearrangements, B and T lymphocytes, and receptors that recognize specific antigens (Netea et al., 2020; Kleinnijenhuis et al., 2012; Quintin et al., 2012; Saeed et al., 2014). Furthermore, trained immunity has been documented in organisms that lack canonical adaptive immune responses, such as plants and invertebrates, suggesting this is a primitive immune memory system that is conserved throughout vertebrates and invertebrates (Lanz-Mendoza and Contreras-Garduño, 2022).

The Bacillus Calmette-Guérin (BCG) vaccine and yeast β-glucans are canonical inducers of trained immunity in humans and stimulate long-lasting metabolic and epigenetic reprogramming of myeloid-lineage cells resulting in hyper-responsiveness upon restimulation with heterologous or homologous inflammatory stimuli. This innate immune memory has been shown to be heritable (Katzmarski et al., 2021) and can last up to months in humans and mice (Netea et al., 2016) and, thus, likely evolved to provide non-specific protection from secondary infections. Most recently, it was described that countries with higher rates of BCG vaccine at birth had fewer coronavirus disease 2019 (COVID-19) cases (Covián et al., 2020) making this immunological phenomenon extremely relevant. Importantly, it is easily ascertained that inflammatory hyper-responsiveness could be deleterious in the context of diseases where more inflammation can lead to greater pathology (e.g. acute septic shock, autoimmune disorders, and allergies). Thus, trained immunity can be regarded as a double-edged sword – providing increased resistance to tissue-specific infection but exacerbating diseases exacerbated by systemic inflammation. Consequently, identifying novel inducers of trained immunity will provide clinically relevant insight into harnessing innate immune cells to attain long-term therapeutic benefits in a range of infections and inflammatory diseases.

Typically, the primary inflammatory stimulus that initiates trained immunity is danger- or pathogen-associated molecular patterns (PAMPs); however, recent publications have shown that β-glucan found in mushrooms, baker’s and brewer’s yeast, wheat and oats, and unknown components of bovine milk can induce trained innate immune memory in monocytes in vitro (Meena et al., 2013; van Splunter et al., 2018). Our data reported here contribute to the growing evidence supporting the multifaceted immunoregulatory role of certain dietary constituents.

Currently, Westernized nations are increasingly dependent on diets enriched in saturated fatty acids (SFAs; Swinburn et al., 2011; Popkin, 2006; Christ and Latz, 2019), which have been shown to mimic PAMP effects on inflammatory cells, regulate innate immune cell function, and alter outcomes of inflammatory disease and infection (Lancaster et al., 2018; Lumeng et al., 2007; Meikle and Summers, 2017; Reyes et al., 2021). Specifically, we have shown the Western diet (WD), a diet enriched in sucrose and SFAs, correlates with increased disease severity and mortality in response to systemic LPS, independent of the diet-dependent microbiota, demonstrating the possibility that the dietary components of this diet may be driving the hyper-responsiveness to LPS (Napier et al., 2019). Currently, it is unknown if enriched dietary SFAs alone mediate trained immunity.

Our work presented herein identifies a ketogenic diet (KD) enriched exclusively in SFAs, and not sucrose, confers an increased systemic response to LPS independent of diet-associated microbiome, ketosis, or glycolytic regulation during disease, and alters inflammatory capacity and composition of the hematopoietic compartment. While others have shown that the WD induces trained immunity in atherosclerotic mice (Ldrl−/−), we are the first to show that trained immunity, including its hallmark long-term persistence, can be induced in wild-type (WT) mice with exposure to enriched SFAs alone (Christ et al., 2018). A lipidomic analysis of blood fat composition after KD exposure revealed a significant increase of free palmitic acid (PA; C16:0) and fatty acid complexes containing PA. PA is known to act synergistically with LPS to enhance intracellular ceramide levels and proinflammatory cytokine expression in macrophages; however, it is currently unknown if ceramide, a bioactive sphingolipid (SG), specifically mediates a heightened inflammatory response to LPS following pre-exposure to PA (Schilling et al., 2013; Zhang et al., 2017). Here we find macrophages pre-treated with physiologically relevant concentrations of PA followed by a secondary exposure to LPS lead to enhanced proinflammatory cytokine expression and release, which were reversible with the inhibition of ceramide.

We find that both short- and long-term exposure to PA, the predominant SFA found in high-fat diets, enhance systemic response to microbial ligands in mice even after a 7-day rest period from PA exposure. Thus, our data suggest exposure to PA leads to a long-lasting innate immune memory response in vivo (Netea et al., 2016). Importantly, trained immunity is induced when a primary inflammatory stimulus changes transcription of inflammatory genes, the immune status returns to basal levels, and challenge with a secondary stimulus enhances transcription of inflammatory cytokines at much higher levels than those observed during the primary challenge (Divangahi et al., 2021). While the dynamics of an initial inflammatory event induced by PA in vivo are not defined in this paper, we show that basal levels of Tnf, Il6, Il1b, and Il10 in the blood of mice pre-exposed to PA were comparable to control mice immediately prior to endotoxin challenge, indicating that mice were not in a primed state prior to disease. This suggests that the hyper-inflammation and poor disease outcome we show in PA-exposed mice are not due to priming but a trained immune response.

The dual nature of trained immunity is also a hallmark feature of the phenomenon, in that non-specific innate immune memory can be either beneficial or detrimental depending on the disease context. The majority of research has demonstrated the protective role of trained immunity against a variety of infections, such as with BCG vaccination and B-glucan stimulation (Quintin et al., 2012; Kaufmann et al., 2018). Our work is unique because we focus on the detrimental role that trained immunity has on disease characterized by inflammatory dysregulation; however, we also highlight the beneficial nature of this novel phenotype by showing that when mice lacking adaptive immunity (Rag1−/−) are pre-exposed to systemic PA, they exhibit enhanced clearance of kidney fungal burden compared to control mice.

We further identify a novel role of SFA-dependent intracellular ceramide required for the enhanced systemic response to microbial ligands, and show intervention with OA, a mono-unsaturated fatty acid that depletes PA-dependent ceramide, can reverse these phenotypes in macrophages and in vivo. Our data presented here highlight the dynamic plasticity of dietary intervention on inflammatory disease outcomes. These data are consistent with the current knowledge that SFAs and ceramide are immunomodulatory molecules, and build on these by highlighting a previously unidentified role of PA in driving long-lived trained immunity.

Results

Diets enriched in SFAs increase endotoxemia severity and mortality

To examine the immune effects of chronic exposure to diets enriched in SFAs on lipopolysaccharide (LPS)-induced endotoxemia, we fed age matched (6–8 weeks), female BALB/c mice either with a WD (enriched in SFAs and sucrose), a KD (enriched in SFAs and low-carbohydrate), or standard chow (SC; low in SFAs and sucrose), for 2 weeks (Supplementary file 1). We defined 2 weeks of feeding as chronic exposure, because this is correlated with WD- or KD-dependent microbiome changes and confers metaflammation in WD mice (Napier et al., 2019), sustained altered blood glucose levels in WD mice (Figure 1—figure supplement 1A), and elevated levels of ketones in the urine and blood in KD mice (Figure 1—figure supplement 1B-C). We then induced endotoxemia by a single intraperitoneal (i.p.) injection of LPS. We measured hypothermia as a measure of disease severity and survival to determine outcome (Napier et al., 2019; Napier et al., 2016; Saito et al., 2003). WD- and KD-fed mice showed significant and prolonged hypothermia, starting at 10 hr post-injection (p.i.), compared to the SC-fed mice (Figure 1A). In accordance with these findings, WD- and KD-fed mice displayed 100% mortality by 26 hr p.i. compared to 100% survival of SC-fed mice (Figure 1B). Hypoglycemia is a known driver of endotoxemia, and each of these diets has varying levels of sugars and carbohydrates (Supplementary file 1; Raetzsch et al., 2009; Filkins and Cornell, 1974). However, mice in all diet groups displayed similar levels of LPS-induced hypoglycemia during disease (Figure 1—figure supplement 1D), indicating that potential effects of diet on blood glucose were not a driver of enhanced disease severity.

Figure 1. Diets enriched in saturated fatty acids lead to enhanced endotoxemia severity and altered systemic inflammatory profiles, independent of diet-associated microbiome.

(A–G) Age-matched (6–8 weeks) female BALB/c mice were fed standard chow (SC), Western diet (WD), or ketogenic diet (KD) for 2 weeks and injected intraperitoneal (i.p.) with 6 mg/kg of lipopolysaccharide (LPS). (A) Temperature loss and (B) survival were monitored every 2 hr. At indicated times, 10–20 μL of blood was drawn via the tail vein, RNA was collected, and samples were assessed for expression of (C) Tnf, (D) Il6, (E) Il1b, and (F) Il10 via qRT-PCR. (G) Il10:Tnf ratio was calculated for 5, 10, 15, and 20 hr post-injection (p.i.) with LPS. (H–N) Next, 19–23-week-old female and 14–23-week-old male and female germ-free C57BL/6 mice were fed SC, WD, or KD for 2 weeks and injected i.p. with 50 mg/kg of LPS. (H) Temperature loss and (I) survival were monitored every 5 hr p.i. (J–N) At indicated times, 10–20 μL of blood was drawn via the tail vein, RNA was collected, and samples were assessed for expression of (J) Tnf, (K) Il6, (L) Il1b, and (M) Il10 via qRT-PCR. (N) Il10:Tnf ratio was calculated for 5 and 10 hr p.i. with LPS. For (A–G), all experiments were run three times, and data are representative of one experiment, n=5 per diet group. For (H–N) SC, n=6; WD, n=5; and KD, n=9; and data are representative of one experiment. For (A, C–G, H, and J–N) a Mann Whitney test was used for pairwise comparisons. For (B) and (I) a log-rank Mantel-Cox test was used for survival curve comparison. For all panels, *p<0.05; **p<0.01; ***p<0.001. For (C–E), Φ symbols indicate WD significance, and ∞ symbols indicate KD significance. Error bars shown mean ± SD.

Figure 1—source data 1. Data and statistics for graphs depicted in Figure 1A–N.
elife-76744-fig1-data1.xlsx (957.8KB, xlsx)

Figure 1.

Figure 1—figure supplement 1. Increase in disease severity in ketogenic diet (KD) mice is independent of ketosis.

Figure 1—figure supplement 1.

Age-matched (6–8 weeks) female BALB/c mice were fed standard chow (SC), Western diet (WD), or KD for 2 weeks. At 1 week and 2 weeks, (A) blood was collected via the tail vein to measure blood glucose levels using a glucose testing meter (Keto-Mojo), and (B) urine was collected on ketone indicator strips to measure levels of systemic acetoacetate (AcAc). Age-matched (6–8 weeks) female BALB/c mice were fed SC supplemented with 1,3-butanediol (SC + BD) or with a saccharine vehicle solution as a control (SC + Veh), or KD for 2 weeks. At 1 week and 2 weeks, (C) blood was collected via the tail vein to measure levels of systemic β-hydroxybutyrate (BHB) using a ketone testing meter (Keto-Mojo). At 2 weeks, SC-, WD-, and KD-fed mice were injected intraperitoneal (i.p.) with lipopolysaccharide (LPS; 6 mg/kg) and (D) 25 hr post-injection (p.i.), blood glucose levels were measured as stated in (A). (E) Temperature loss and (F) survival were monitored every 2 hr for mice treated as in (C) followed by i.p. injection with LPS (10 mg/kg). Age-matched (20–21 weeks) female C57BL/6 mice were fed SC, WD, or KD for 2 weeks followed by i.p. injection with LPS (4.5 mg/kg). (G) Temperature loss and (H) survival were monitored every 2 hr. For (A, B, D), all experiments were run three times, and data are representative of one experiment, n=5–8 mice/group. For (C, E, F), all experiments were run three times, and data are representative of one experiment, n=5–8 mice/group. For (G, H), data are representative of one experiment, n=10 mice/group. For (A–C, E, G), a Mann-Whitney U test was used for pairwise comparisons. For (F, H), a log-rank Mantel-Cox test was used for survival curve comparison. For (E), β symbols indicate SC +Veh vs. SC + BD significance, symbols indicate SC + Veh vs. KD significance, and δ symbols indicate SC + BD vs. KD significance. For (G), ϕ symbols indicate SC vs. WD significance, and symbols indicate SC vs. KD significance. For all panels, * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. Error bars show mean ± SD.
Figure 1—figure supplement 1—source data 1. Data for graphs depicted in Figure 1—figure supplement 1A-H.

Considering mice fed KD experience a shift toward nutritional ketosis, we wanted to understand if our phenotype was dependent on nutritional ketosis. 1,3-butanediol (BD) is a compound that induces ketosis by enhancing levels of the ketone β-hydroxybutyrate in the blood (Goldberg et al., 2019). Age matched (6–8 weeks), female BALB/c mice were fed for 2 weeks with KD, SC supplemented with saccharine and 1,3-butanediol (SC + BD), or SC-fed with the saccharine vehicle solution (SC + Veh). BD supplementation was sufficient to increase blood ketones (Figure 1—figure supplement 1C). We next injected LPS i.p. and found KD-fed mice showed significantly greater hypothermia, and increased mortality, compared to SC + BD and SC + Veh (Figure 1—figure supplement 1E, F). Though short-lived, when compared to SC + Veh, the SC + BD mice did confer an increase in hypothermia, suggesting that nutritional ketosis may play a minor role in KD-dependent susceptibility to endotoxemia (Figure 1—figure supplement 1E, F). Together these data suggest that diets enriched in SFAs promote enhanced acute endotoxemia severity, and this is independent of diet-dependent hypoglycemic shock or nutritional ketosis.

Diets enriched in SFAs induce a hyper-inflammatory response to LPS and increased immunoparalysis

Endotoxemia mortality results exclusively from a systemic inflammatory response characterized by an acute increase in circulating inflammatory cytokine levels (e.g. TNF, IL-6, and IL-1β) from splenocytes and myeloid-derived innate immune cells (Lewis et al., 2016; Wang et al., 2016; Radzyukevich et al., 2021; Zhang et al., 2012). Additionally, pre-treatment of myeloid-derived cells with dietary SFAs has been shown to enhance inflammatory pathways in response to microbial ligands (Schwartz et al., 2010; Fang et al., 2022). Considering this, we hypothesized that exposure to enriched systemic dietary SFAs in WD- and KD-fed mice would enhance the inflammatory response to systemic LPS during the acute inflammatory response. 5 hr p.i., age matched (6–8 weeks), female BALB/c mice fed all diets showed induction of Tnf, Il6, and Il1b expression in the blood (Figure 1C–E). However, at 5 hr p.i., WD- and KD-fed mice experienced significantly higher expression of Tnf and Il6 in the blood, compared with SC-fed mice, and WD-fed mice also showed significantly higher Il1b expression (Figure 1C–E), indicating that diets enriched in SFAs are associated with a hyper-inflammatory response to LPS.

Importantly, septic patients often present with two immune phases: an initial amplification of inflammation, followed by or concurrent with an induction of immune suppression (immunoparalysis), that can be measured by a systemic increase in the anti-inflammatory cytokine IL-10 (Cheng et al., 2016; Nedeva et al., 2019). Furthermore, in septic patients, a high IL-10:TNF ratio equates with the clinical immunoparalytic phase and correlates with poorer sepsis outcomes (Gogos et al., 2000; van Dissel et al., 1998). Interestingly, we found there was significantly increased Il10 expression in WD- and KD-fed mice, compared to SC-fed mice (Figure 1F), and WD- and KD-fed mice had significantly higher Il10:Tnf ratios at 10–20 hr and 15–20 hr, respectively, compared to SC-fed mice (Figure 1G). These data conclude that mice exposed to diets enriched in SFAs show an initial hyper-inflammatory response to LPS, followed by an increased immunoparalytic phenotype, which correlates with enhanced disease severity, similar to what is seen in the clinic.

Diets enriched in SFAs drive enhanced responses to systemic LPS independent of diet-associated microbiome

We have previously shown that WD-fed mice experience increased endotoxemia severity and mortality, independent of diet-associated microbiome (Napier et al., 2019). In order to confirm the increases in disease severity that correlated with KD were also independent of KD-associated microbiome changes, we used a germ-free (GF) mouse model. 19–23-week-old female and 14–23-week-old male and female GF C57BL/6 mice were fed SC, WD, and KD for 2 weeks followed by injection with 50 mg/kg of LPS, our previously established LD50 in GF C57BL/6 mice (Napier et al., 2019). As we saw in the conventional mice, at 10 hr p.i. WD- and KD-fed GF mice showed enhanced hypothermia and mortality, compared to SC-fed GF mice (Figure 1H, I). These data show that, similar to WD-fed mice, the KD-associated increase in endotoxemia severity and mortality is independent of diet-associated microbiome.

Our previous studies (Figure 1A–G) in conventional mice were carried out in 6–8-week female mice on a BALB/c background. Importantly, genetic background and age differences can have large effects on LPS treatment outcome. The GF mice used in this study (Figure 1H–N) were on a C57BL/6 background, between the ages of 14 and 23 weeks. Thus, we confirmed WD- and KD-fed conventional C57BL/6 mice aged 20–21 weeks old show enhanced disease severity and mortality in an LPS-induced endotoxemia model (4.5 mg/kg), compared to mice fed SC, similar to what is seen in younger BALB/c mice (Figure 1—figure supplement 1G, H).

Additionally, to confirm that the hyper-inflammatory response to systemic LPS was independent of the WD- and KD-dependent microbiome, we measured systemic inflammation during endotoxemia via the expression of Tnf, Il6, and Il1b in the blood at 0–10 hr p.i. We found, WD- and KD-fed GF mice displayed enhanced expression of Tnf and Il1b at 5–10 hr, and significantly enhanced expression of il-6 at 5 hr, compared to SC-fed GF mice (Figure 1J–L). Interestingly, Il10 expression and the Il10:Tnf ratio were not significantly different throughout all diets, suggesting the SFA-dependent enhanced immunoparalytic phenotype is dependent on the diet-associated microbiomes in WD- and KD-fed mice (Figure 1M–N). These data demonstrate that the early hyper-inflammatory response, but not the late immunoparalytic response, to LPS associated with enriched dietary SFAs is independent of the diet-dependent microbiota.

A diet enriched exclusively in SFAs induces trained immunity

Thus far we find feeding diets enriched in SFAs (WD and KD) leads to enhanced expression of inflammatory cytokines in the blood after treatment with systemic LPS, suggesting that the SFAs may be inducing an innate immune memory response that leads to a hyper-inflammatory response to secondary challenge. Specifically, trained immunity is an innate immune memory response characterized by reprogramming of myeloid cells by a primary inflammatory stimulus, that then responds more robustly to secondary inflammatory challenge. Trained immunity has been shown to mediate cell sub-types within the HSC compartment that gives rise to “trained” myeloid progeny for weeks to years (De Zuani and Frič, 2022). A previous study in Ldlr−/− mice has shown 4 weeks of WD feeding significantly enhances multipotent progenitors (MPPs) and granulocyte and monocyte precursors (GMPs) and skews development of GMPs toward a monocyte lineage that is primed to respond with a hyper-inflammatory response to LPS (Christ et al., 2018). Currently, it is unknown if diets enriched in SFAs fed to WT mice can induce changes within the HSC compartment or long-lasting trained immunity.

In order to determine the impact of dietary SFAs on bone marrow reprogramming in vivo, we next evaluated HSCs and progenitor cells via flow cytometry from age-matched (6–8 weeks) female WT BALB/c mice fed SC, WD, and KD for 2 weeks. Using previously published panels for analyzing HSC populations in the bone marrow (Kaufmann et al., 2018; Vazquez et al., 2015; Nowlan et al., 2020), we collected bone marrow and measured relative proportions of long-term HSCs (LT-HSCs; CD201+CD27+CD150+CD48), short-term HSCs (ST-HSCs; CD201+CD27+CD150+CD48+), and MPPs (CD201+CD27+CD150CD48+) (Figure 2A and B). Strikingly, we find that KD-fed mice showed significantly enhanced ST- and LT-HSCs, and MPPs compared to SC-fed mice (Figure 2C). Unlike previously reported in Ldlr−/− mice, there was no significant change in ST-HSCs, LT-HSCs, or MPPs within WD-fed WT mice (Figure 2C). Furthermore, we did not see a significant increase in MPP3s for WD-fed mice, as previously published for Ldlr−/− mice (Christ et al., 2018), or KD-fed mice; however, this may be due to the difference in genetic backgrounds, or length of diet administration (Figure 2—figure supplement 1A). These data are the first to show that the KD, a diet solely enriched in SFAs, alters hematopoiesis by enhancing expansion and differentiation of HSCs, similar to previously described inducers of trained immunity.

Figure 2. Ketogenic diet (KD) feeding alters HSC populations and bone marrow-derived macrophages (BMDMs) from KD-fed mice show a hyper-inflammatory response to lipopolysaccharide (LPS) ex vivo.

Bone marrow was extracted from the femurs and tibias of age-matched (6–8 weeks) female BALB/c mice fed standard chow (SC), Western diet (WD), or KD for 2 weeks. (A) Fluorescence-Activated Cell Sorting (FACS) plots of total HSCs (CD201+CD27+) and (B) LT-HSCs, ST-HSCs, and multipotent progenitors (MPPs) from mice fed SC, WD, or KD for 2 weeks. Quantification of (C) the total numbers of LT- and ST-HSCs, and MPPs in bone marrow from mice fed SC, WD, or KD for 2 weeks. Next, BMDMs were plated at 5×10^6 cells/mL and differentiated for 7 days in media supplemented with macrophage colony-stimulating factor. Cells were split and plated in 24-well plates to adhere for 12 hr and treated with media (Ctrl) or LPS (24 hr; 10 ng/mL). Supernatants were assessed via ELISA for (D) TNF and (E) IL-6 secretion at 24 hr post-LPS treatment. IL-6 Ctrl supernatants were below the limit of detection; ND = no data. For (A-E), all experiments were run three times, and data are representative of one experiment, n=5 per diet group. (C) A Mann Whitney test was used for pairwise comparisons. (D, E) For all plates, all treatments were performed in triplicate, and a student’s t-test was used for statistical significance. *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001. Error bars show the mean ± SD.

Figure 2—source data 1. Data and statistics for graphs depicted in Figure 2A–E.

Figure 2.

Figure 2—figure supplement 1. Ketogenic diet (KD) does not alter multipotent progenitor (MPP) differentiation or basal inflammation in bone marrow-derived macrophages (BMDMs), and monocytes and splenocytes show a hyper-inflammatory response to lipopolysaccharide (LPS) ex vivo.

Figure 2—figure supplement 1.

Age-matched (6–8 weeks) conventional, wild-type, female BALB/c mice were fed standard chow (SC), Western diet (WD), or KD for 2 weeks. Bone marrow was extracted from the femurs and tibias of mice, HSCs were isolated via FACS, and (A) MPPs were quantified. BMDMs were plated at 5×106 cells/mL and differentiated for 7 days in media supplemented with macrophage colony-stimulating factor. Cells were split and plated in 24-well plates to adhere for 12 hr and treated with media (Ctrl) for 24 hr. Supernatants were assessed via ELISA for (B) TNF and IL-6 secretion. Monocytes were isolated from the femurs and tibias of mice and plated at 2×106 cells/mL. RNA was extracted from (C) untreated monocytes (0 hr) or (D) monocytes with LPS (10 ng/mL) for 2 hr. Expression of Tnf and Il6 was analyzed via qRT-PCR. Splenocytes were isolated and plated at 1×106 cells/mL. RNA was isolated from (E) untreated splenocytes (0 hr) or (F) splenocytes treated with LPS (10 ng/mL) for 2 hr. Expression of Tnf and Il6 was analyzed via qRT-PCR. For (A, B), all experiments were run three times, and data are representative of one experiment, n=5 per diet group. For (C-F), all experiments were run twice, and data are representative of one experiment, n=3 per diet group.(A) A Mann Whitney test was used for pairwise comparisons. (B-F) For all plates, all treatments were performed in triplicate, and a student’s t-test was used for statistical significance. For all panels, * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. Error bars show mean ± SD.
Figure 2—figure supplement 1—source data 1. Data for graphs depicted in Figure 2—figure supplement 1.
Figure 2—figure supplement 2. Gating strategy for HSCs, related to Figure 2.

Figure 2—figure supplement 2.

Cells were gated in FSC-A against SSC-A. Doublets were excluded using FSC-A against FSC-H and subsequently SSC-A against SSC-H. Viable cells were gated, and lineage-committed cells were excluded. Within the lineage-negative cells, the CD201+CD27+ population was gated. In a CD150 against CD48 plot, the CD201+CD27+ cells were divided into LT-HSC, ST-HSC, multipotent progenitor (MPP), and the remaining CD150CD48 population. MPPs were characterized as MPP3 and MPP4 by their surface expression of CD34 and Flt3.

Furthermore, it is unknown if enriched dietary SFAs lead to long-lasting functional reprogramming associated with trained immunity that leads to a hyper-inflammatory response. Thus, we fed age-matched (6–8 weeks) female BALB/c mice SC, WD, or KD for 2 weeks, isolated bone marrow, differentiated into BMDMs for 7 days, and analyzed baseline inflammation and response to LPS. We found that untreated BMDMs isolated from mice fed SC and WD showed no significant differences in TNF or IL-6, and those from KD-fed mice showed a modest increase only in IL-6 compared to BMDMs from SC-fed mice (Figure 2—figure supplement 1B). However, when BMDMs were stimulated with LPS for 24 hr ex vivo, BMDMs from WD- and KD-fed mice showed significantly higher secretion of TNF, and only those from KD-fed mice showed significantly enhanced IL-6 secretion (Figure 2D–E). These data show that diets enriched in SFAs are inducing long-lasting inflammatory reprogramming of myeloid cells in vivo, and that reprogramming takes place within the bone marrow.

Importantly, monocytes and splenocytes are necessary for induction of systemic inflammatory cytokines during endotoxemia (Radzyukevich et al., 2021; Zhang et al., 2012). Thus, we wanted to assess if enriched dietary SFA induces in vivo reprogramming of monocytes and splenocytes, leading to an enhanced response to LPS ex vivo. First, we fed age-matched (6–8 weeks) female BALB/c mice SC, WD, or KD for 2 weeks, isolated bone marrow monocytes (BMMs) via magnetic negative selection using bone marrow extracted from femurs and tibias, and determined baseline expression of inflammatory cytokines. We found that prior to ex vivo LPS stimulation, BMMs isolated from mice fed SC, WD, or KD showed no significant difference in Tnf expression, and Il6 expression was significantly decreased in BMMs from KD-fed mice (Figure 2—figure supplement 1C). However, when BMMs were stimulated with LPS for 2 hr ex vivo, those from KD-fed mice showed significantly higher expression of Tnf and Il6, while those from WD-fed mice exhibited no significance in expression compared to SC-fed mice (Figure 2—figure supplement 1D). Similarly, we isolated splenocytes from SC-, WD-, and KD-fed mice and found no difference between homeostatic inflammation of splenocytes between diets, but a significantly enhanced expression of Tnf in the splenocytes of KD-fed mice, and not WD-fed mice, challenged with LPS (2 hr) compared to splenocytes from SC-fed mice (Figure 2—figure supplement 1E, F).

These data show the KD stimulates expansion of HSC populations and skew differentiation of myeloid progenitors that then give rise to macrophages with enhanced inflammatory potency (Figure 2A–E; Figure 2—figure supplement 2). Furthermore, these data suggest that BMDMs, BMMs, and splenocytes from WD- and KD-fed mice are not more inflammatory at homeostasis; however, when challenged with LPS, KD feeding confers a hyper-inflammatory response. Together, our results suggest the KD, a diet that comprised 90.5% SFAs, leads to reprogramming of the HSC compartment and long-lasting trained immunity.

PA and PA-associated fatty acids are enriched in the blood of KD-fed mice

It is known that the SFAs consumed in the diet determine the SFA profiles in the blood (Dougherty et al., 1987; Skeaff et al., 2006; Zöllner and Tatò, 1992), and that these SFAs have the potential to be immunomodulatory. Thus, we next wanted to identify target SFAs enriched in the blood of mice fed a diet exclusively enriched in SFAs that may be altering the systemic inflammatory response to LPS. Considering that the KD is enriched in SFAs and not sucrose, and that KD-fed mice showed distinct HSC alterations and LPS-induced hyper-inflammation in BMDMs, BMMs, and splenocytes treated ex vivo, the subsequent studies were performed exclusively on KD-fed mice. We used mass spectrometry lipidomics to create diet-dependent profiles of circulating fatty acids in SC- and KD-fed mice (Choi et al., 2018). Age matched (6–8 weeks), female BALB/c mice were fed SC or KD for 2 weeks, then serum samples were collected and analyzed using qualitative tandem liquid chromatography quadrupole time of flight mass spectrometry. We used principal component analysis (PCA) to visualize how samples within each data set clustered together according to diet, and how those clusters varied relative to one another in abundance levels of free fatty acids (FFA), triacylglycerols (TAG), and phosphatidylcholines (PC). For all three groups of FAs, individual mice grouped with members of the same diet represented by a 95% confidence ellipse with no overlap between SC- and KD-fed groups (Figure 3A–C). These data indicate that 2 weeks of KD feeding are sufficient to alter circulating FFAs, TAGs, and PCs, and that SC- and KD-fed mice display unique lipid blood profiles. Similarly, the relative abundance of SGs in SC- and KD-fed mice displayed unique diet-dependent profiles with no overlapping clusters, and abundance of specific SGs was significantly higher in the serum of KD-fed mice compared to SC-fed mice (Figure 3—figure supplement 1A, B). Though the independent role of each FFA, TAG, PC, and SG species has not been clinically defined, each are classes of lipids that when accumulated is associated with metabolic diseases, which have been shown to enhance susceptibility to sepsis and exacerbate inflammatory disease (Meikle and Summers, 2017; I S Sobczak et al., 2019; Sokolowska and Blachnio-Zabielska, 2019; Papadimitriou-Olivgeris et al., 2016).

Figure 3. Ketogenic diet (KD) alters lipid profiles, and palmitic acid (PA) is mediating a hyper-inflammatory response to secondary challenge with lipopolysaccharide (LPS).

Data points represent single animal samples, and colors represent groups fed standard chow (SC; gray) or KD (orange) diets for 2 weeks. A 95% confidence ellipse was constructed around the mean point of each group for (A) free fatty acids (FFA), (B) triglycerides (TAG), and (C) phosphatidylcholines (PC). (D) Heatmap analysis of FFA in SC and KD mice. Components that are significantly different between the two groups are in bold. Below the heatmap is a comparison of PA 16:0 peak area detected by Liquid Chromatography Quadruple Time of Flight Mass Spectrometry (LC-QToF MS/MS) between SC and KD groups; AUC = area under the curve. Statistical significance is determined by unpaired two-tailed t-test between SC and KD groups with n=3 per group. Primary bone marrow-derived macrophages (BMDMs) were isolated from age-matched (6–8 weeks) C57BL/6 female and male mice. BMDMs were plated at 1×106 cells/mL and treated with either ethanol (ethanol (EtOH); media with 0.83% ethanol), media (Ctrl for LPS), or LPS (10 ng/mL) for 12 hr, or PA (PA stock diluted in 0.83% EtOH; 1 mM PA conjugated to 2% bovine serum albumin [BSA]) for 12 hr, with and without a secondary challenge with LPS. After indicated time points, RNA was isolated, and expression of (E) Tnf, (F) Il6, and (G) Il1b was measured via qRT-PCR. BMDMs were plated at 1×106 cells/mL and treated with either ethanol (EtOH; media with 0.83% ethanol), media (Naïve), or 1 mM PA for 12 hr followed by PBS (control) or LPS (10 ng/mL). Supernatants were assessed via ELISA for (H) TNF, (I) IL-6, and (J) IL-1β secretion. Next, BMDMs were plated at 1×106 cells/mL and treated with either media (Ctrl), LPS (10 ng/mL) for 24 hr, PA (PA stock diluted in 0.83% EtOH; 0.5 mM PA conjugated to 2% BSA) for 12 hr, Fumonisin B1 (FB1; 10 μM; diluted in 0.14% EtOH) or EtOH (0.97% to mimic simultaneous PA/FB1 treatment). Controls for all treatments are shown next to experimental groups treated additionally with LPS (10 ng/mL) for 24 hr. Supernatants were assessed via ELISA for (K) TNF, (L) IL-6, and (M) IL-1β secretion. For all plates, all treatments were performed in triplicate. For all panels, a student’s t-test was used for statistical significance. *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001. Error bars show the mean ± SD.

Figure 3—source code 1.
Figure 3—source data 1. Data and statistics for graphs depicted in Figure 3A–M.

Figure 3.

Figure 3—figure supplement 1. Principal component analysis and heatmap analysis of sphingolipid lipidomic data in mouse serum samples.

Figure 3—figure supplement 1.

(A) Data points represent single animal samples, and colors represent groups fed standard chow (SC; gray) or Ketonic diet (KD; orange) diets for 2 weeks, and a 95% confidence ellipse was constructed around the mean point of each group. Heatmap analysis of (B) sphingolipids (SM), (C) triglycerides (TG), and (D) phosphatidylcholines (PC) in SC and KD groups. Lipid components containing 16:0 palmitic chains are highlighted in purple, and components that are significantly different between the two groups are in bold. Statistical significance determined by unpaired two-tailed t-test between SC and KD groups. * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. n=3 per group.
Figure 3—figure supplement 1—source data 1.
Figure 3—figure supplement 1—source code 1.
Figure 3—figure supplement 2. Physiological levels of palmitic acid (PA) induce a hyper-inflammatory response to secondary challenge with lipopolysaccharide (LPS) in macrophages.

Figure 3—figure supplement 2.

Primary bone marrow-derived macrophages (BMDMs) were isolated from age-matched (6–8 weeks) female and male mice. (A–C) BMDMs were plated at 1×106 cells/mL and treated with ethanol (EtOH; media with 1.69% ethanol), media (Ctrl for LPS), or PA (1 mM; diluted in 1.69% EtOH) for 12 hr. Next, PA-treated cells were treated with LPS (10 ng/mL) for 24 hr, and all other wells were given fresh media. (D–I) BMDMs were plated at 1×106 cells/mL and treated with PA (0.5 mM; diluted in 1.69% EtOH) for 12 or 24 hr. Next, PA-treated cells were treated with LPS (10 ng/mL) for 24 hr, and all other wells were given fresh media. After indicated time points, RNA was isolated and expression of (A, D, G) Tnf, (B, E, H) Il6, and (C, F, I) Il1b was measured via qRT-PCR. For all plates, treatments were performed in triplicate. For all panels, a student’s t-test was used for statistical significance. * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. Error bars show mean ± SD.
Figure 3—figure supplement 2—source data 1. Data for graphs depicted in Figure 3—figure supplement 2A-D.
Figure 3—figure supplement 3. Cytotoxicity as determined by lactate dehydrogenase (LDH) release from bone marrow-derived macrophages (BMDMs) pre-treated with palmitic acid (PA) followed by lipopolysaccharide (LPS) stimulation.

Figure 3—figure supplement 3.

BMDMs from age-matched (6–8 weeks) male and female C57BL/6 mice were plated in 96-well plates at 5×104 cells/well and incubated for 12 hr with PA (0.5 mM or 1 mM). Next, media was removed, and cells were treated with PBS for 10 ng/mL LPS in phenol-red-free Opti-MEM media and incubated for an additional 24 hr. Supernatants were collected, and LDH release was quantified using CytoTox96 non-radioactive cytotoxicity assay. (A, B) Cytotoxicity is shown as percentage of max LDH release. For all plates, all treatments were performed in triplicate, and a student’s t-test was used for statistical significance. * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. Error bars show mean ± SD.
Figure 3—figure supplement 3—source data 1. Data for graphs depicted in Figure 3—figure supplement 3A, B.

Importantly, we identified a significant increase in multiple circulating FFAs within the KD-fed mice, compared to the SC-fed mice, many of which were SFAs (Figure 3D). Interestingly, in KD-fed mice we found a significant increase in free PA (C16:0), an immunomodulatory SFA that is found naturally in animal fats, vegetable oils, and human breast milk (Mancini et al., 2015) and is eightfold enriched in KD (Figure 3D, Supplementary file 1). Additionally, PA-containing TAGs and PCs were significantly elevated in KD-fed mice serum, compared to SC-fed mice (Figure 3—figure supplement 1C, D). These data indicate that KD feeding not only enhances levels of freely circulating PA, but also enhances the frequency PA is incorporated into other lipid species in the blood.

PA enhances macrophage inflammatory response to LPS

Many groups have shown that PA alone induces a modest, but highly reproducible increase in the expression and release of inflammatory cytokines in macrophages and monocytes (Lancaster et al., 2018; Korbecki and Bajdak-Rusinek, 2019). However, it remains unknown if PA can act as a primary inflammatory stimulus to induce a hyper-inflammatory response to a secondary heterologous stimulus in primary cells. Thus, we next wanted to determine if pre-exposure to physiologically relevant concentrations of PA altered the macrophage response to a secondary challenge with LPS. Current literature indicates a wide range of serum PA levels, between 0.3 and 4.1 mM, reflects a high-fat diet in humans (Abdelmagid et al., 2015; Liu et al., 2015; Gallego et al., 2018; Buchanan et al., 2021; Perreault et al., 2014). We aimed to use a physiologically relevant concentration of PA reflecting a human host for our in vitro studies, thus we treated primary bone marrow-derived macrophages (BMDMs) with and without 1 mM of PA containing 2% bovine serum albumin (BSA) for 12 hr, removed the media, subsequently treated with LPS (10 ng/mL) for an additional 24 hr, and measured expression and release of TNF, IL-6, and IL-1β. Importantly, the BSA dissolved in the media used for PA treatment solutions was endotoxin- and FA-free to ensure aberrant TLR signaling would not occur via BSA contamination, and fresh PA was conjugated to BSA-containing media immediately prior to use. We found that BMDMs pre-treated with PA (1 mM) for 12 hr expressed significantly higher levels of Tnf and Il6 in response to secondary treatment with LPS, compared to naïve BMDMs (Figure 3E and F). Il1b expression was significantly lower in cells pre-treated with PA (Figure 3G); however, secretion of TNF, IL-6, and IL-1β was enhanced in BMDMs pre-treated with PA (1 mM) for 12 hr and challenged with LPS (Figure 3H–J). We found a similar enhanced Il6 and Tnf expression in response to LPS in BMDMs treated with PA (1 mM) for twice the length of exposure (24 hr), and Il-1b expression was decreased (Figure 3—figure supplement 2A-C).

Furthermore, we pre-treated BMDMs with a concentration of PA that reflects the lower range of physiologically relevant serum levels and found 0.5 mM of PA induced significantly higher expression of Tnf, Il6, and Il1b after 12-hr challenge with LPS; however, only Tnf and Il6 were significantly enhanced after 24-hr LPS treatment, compared to naive BMDMs treated with LPS (Figure 3—figure supplement 2D-I).

Importantly, PA treatment can induce apoptosis and pyroptosis in various cell types (Borradaile et al., 2006; Li et al., 2018; Ly et al., 2017; Tao et al., 2021); however, we found only an average of 3.4 and 4.4% of cell death after a 12-hr or 24-hr incubation, respectively, with PA (1 mM) and subsequent 24 hr of LPS treatment or control media (Figure 3—figure supplement 3A, B). These data demonstrate PA pre-treatment of macrophages induces a hyper-inflammatory response to LPS independent of cell death, suggesting PA is sensitizing macrophages to secondary inflammatory challenge.

Thus, we conclude that both 12- and 24-hr pre-treatments with 0.5 mM or 1 mM of PA conjugated to 2% BSA are sufficient to induce reprogramming of macrophages and alter the response to stimulation with a heterologous ligand. Additionally, these data demonstrate that even serum concentrations of PA that are at the lower end of the spectrum for humans consuming a high-fat diet pose a risk for inflammatory dysfunction.

Diverting ceramide synthesis inhibits the PA-dependent hyper-inflammatory response to LPS in macrophages

PA treatment of various cell types diverts cellular metabolism toward the synthesis of the toxic metabolic byproducts: diacylglycerols and ceramide (Palomer et al., 2018). PA-induced ceramide synthesis has specifically been demonstrated to enhance inflammation (Schilling et al., 2013; Zhang et al., 2017; Schwartz et al., 2010; Jin et al., 2013). Considering this, we wanted to determine the role of enhanced macrophage ceramide production in driving PA-induced hyper-inflammatory response to LPS. Thus, we treated BMDMs simultaneously with PA (0.5 mM) and a ceramide synthase inhibitor Fumonisin B1 (FB1; 10 μM), for 12 hr, removed the media, subsequently treated with LPS (10 ng/mL) for an additional 24 hr, and measured release of TNF, IL-6, and IL-1β. We found that BMDMs pre-treated simultaneously with PA and FB1 for 12 hr expressed significantly lower levels of TNF, IL-6, and IL-1β secretion in response to LPS, compared to BMDMs pre-treated with only PA (Figure 3K–M). We conclude that ceramide synthesis induced by PA is required for the macrophage hyper-inflammatory response to secondary challenge with LPS.

PA is sufficient to increase endotoxemia severity and systemic hyper-inflammation

Considering the drastic effect of PA on macrophage response to secondary challenge with LPS, we next wanted to understand if exposure to PA alone is sufficient to induce a hyper-inflammatory response during endotoxemia in vivo. We answered this question using age-matched (6–8 weeks) female BALB/c mice fed SC for 2 weeks, by mimicking systemic PA levels found in serum of humans on high-fat diet via a single i.p. injection of ethyl palmitate (750 mM), and then after 12 hr, challenging with LPS i.p. (Eguchi et al., 2012). Similar to previous publications, we find that a 750-mM i.p. injection of ethyl palmitate enhances free PA levels in the serum to 173–425 μM compared to Veh-treated mice with 110–250 μM (Figure 4—figure supplement 1A). Important to note, free PA is only transiently enhanced by systemic application and is quickly (<1 hr) taken up by peripheral tissues; thus, our detected free serum levels are most likely an underestimation of transient systemic PA (Black, 2007; Mansbach and Gorelick, 2007; Karavolos et al., 2008).

Interestingly, after LPS challenge, PA-treated mice experienced increased disease severity as indicated by their significant decline in temperature compared to Veh mice (Figure 4A). Similar to WD- and KD-fed mice, PA-treated mice also exhibited enhanced mortality, compared to Veh mice (Figure 4B). Importantly, mice injected with PA for shorter time periods (0, 3, and 6 hr) and then challenged with LPS did not exhibit increased disease severity or poor survival outcome (Figure 4—figure supplement 1B, C), concluding that a 12-hr pre-treatment with PA is required for an increase in disease severity.

Figure 4. Palmitic acid (PA) acts as a novel mediator of trained immunity by inducing a hyper-inflammatory response lipopolysaccharide (LPS)-induced endotoxemia and enhancing clearance of Candida albicans infection.

Age-matched (6–8 weeks) female BALB/c mice were fed standard chow (SC) for 2 weeks and injected intraperitoneal (i.p.) with ethyl palmitate (PA, 750 mM) or vehicle (Veh) solutions 12 hr before i.p. LPS injections (10 mg/kg). (A) Temperature loss was monitored every 2 hr as a measure of disease severity or (B) survival. At indicated times blood was collected via the tail vein, RNA was extracted, and samples were assessed for expression of (C) Tnf, (D) Il6, and (E) Il1b via qRT-PCR. (F) Blood was collected via the tail vein from Veh and PA pre-treated (12-hr PA) mice immediately prior to LPS injection, and samples were assessed for expression of Tnf, Il6, Il1b, and Il10 via qRT-PCR. Additionally, age-matched (6–8 weeks) female BALB/c mice fed SC, injected i.p. with ethyl palmitate (PA, 750 mM) or Veh solutions every day for 9 days, and then rested for 7 days before i.p. LPS injections (10 mg/kg) (G) Temperature loss and (H) survival were monitored during endotoxemia. (I) Age-matched (8–9 weeks) female Rag1−/− mice were injected i.p. with ethyl palmitate (PA, 750 mM) or Veh solutions 12 hr before intravenous C. albicans infection. Fungal burden of kidneys from Veh and PA pre-treated (12-hr PA) mice 24 hr after C. albicans infection. For (A–F), experiments were run three times, and data are representative of one experiment, n=3 mice/group. For (G, H), experiments were run twice, and data are representative of one experiment, n=5 mice/group. For (I), experiments were run three times, and data are representative of one experiment, n=6 mice/group. For (A), (C–E), (G), and (I), a Mann Whitney test was used for pairwise comparisons. For (B) and (H), a log-rank Mantel-Cox test was used for survival curve comparison. For all panels, *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001. Error bars shown mean ± SD.

Figure 4—source data 1. Data and statistics for graphs depicted in Figure 4A–I.
elife-76744-fig4-data1.xlsx (684.8KB, xlsx)

Figure 4.

Figure 4—figure supplement 1. Palmitic acid (PA) intraperitoneal (i.p.) injections enhance serum PA concentrations, and PA-induced trained immunity is time-dependent.

Figure 4—figure supplement 1.

Conventional wild-type, age-matched (6–8 weeks), female BALB/c mice were fed standard chow (SC) for 2 weeks and injected i.p. with ethyl palmitate (PA 750 mM in 1.6% lecithin and 3.3% glycerol in endotoxin-free limulus amebocyte lysate [LAL] reagent water) or a vehicle solution (Veh, 1.6% lecithin and 3.3% glycerol in endotoxin-free LAL reagent water). (A) Serum was collected via cardiac punctures from mice 2 hr and 5 hr post-injection (p.i.). Serum samples were analyzed for absolute PA concentrations using qualitative tandem liquid chromatography quadrupole time of flight mass spectrometry. At 0, 3, and 6 hr after PA injection, endotoxemia was induced via a single i.p. injection of lipopolysaccharide (LPS; 10 mg/kg). (B) Temperature loss and (C) survival were monitored every 2 hr. (D) Blood was collected via the tail vein to measure blood glucose levels at 0 and 20 hr p.i. with LPS using a glucose testing meter (Keto-Mojo). For (D), a Mann Whitney test was used for pairwise comparisons. Data is representative of one experiment, n=3–4 mice/group. * p<0.05; ** p<0.01; *** p<0.001; **** p<0.0001. Error bars show mean ± SD.
Figure 4—figure supplement 1—source data 1. Data for graphs depicted in Figure 4—figure supplement 1A-D.

Next, we measured systemic inflammatory status during disease and found similar to KD-fed mice, the 12-hr PA-pre-treated mice showed significantly enhanced expression of Tnf (5 hr and 10 hr) and Il6 (5 hr) post-LPS challenge, compared to Veh control (Figure 4C and D). Expression of Il-1b trended upward but was not significantly upregulated in 12-hr PA-pre-treated mice, compared to Veh-treated mice (Figure 4E). Importantly, as a control we looked at LPS-induced hypoglycemia in PA-treated mice, and 12-hr pre-treatment with PA did not alter LPS-induced hypoglycemia (Figure 4—figure supplement 1D), indicating that diet-dependent hypoglycemic shock was not a driver of endotoxemia severity in PA-treated mice. Thus, exposure to PA to mimic systemic levels found in humans eating high-fat diets is sufficient to drive enhanced inflammation and disease severity in mice stimulated with endotoxin, and this effect is dependent on length of PA exposure.

PA induces long-lived hyper-responsiveness to LPS and enhanced clearance of fungal infection

Our data show that pre-treatment with systemic PA alone enhances endotoxemia severity in vivo and inflammatory responses of macrophages to a secondary and heterologous stimulus in vitro. This form of regulation resembles trained immunity; however, it remains unclear if PA is inducing trained immunity in vivo. We first evaluated the basal level expression of Tnf, Il6, and Il1b in mice treated with 750 mM of PA or Veh i.p. for 12 hr, before stimulation with LPS. Interestingly, we did not see significant differences in Tnf, Il6, or Il1b expression at 12 hr of exposure with PA (Figure 4F), which suggests that circulating immune cells of these mice is not in a primed state at these time points prior to LPS injection. These data suggest PA induces trained immunity, and not priming; however, the time point of initial inflammation induced by PA remains unknown.

As mentioned previously, canonical inducers of trained immunity (e.g. BCG or β-glucan) induce long-lived enhanced innate immune responses to secondary inflammatory stimuli (Kaufmann et al., 2018, Netea et al., 2020). Thus, we hypothesized that exposure to a PA bolus would enhance disease severity and mortality in mice, and that this phenotype would persist even after mice were rested from PA injections for 1 week. We injected age matched (6–8 weeks), female BALB/c mice fed SC with a vehicle solution (Veh→SC) or PA (750 mM; PA→SC) i.p. once a day for 9 days and then rested the mice for 1 week. When challenged with systemic LPS, PA→SC showed an increase in disease severity and mortality compared to Veh→SC mice (Figure 4G and H), indicating that PA alone can induce long-lived trained immunity that increases susceptibility to inflammatory disease. Importantly, the difference between Veh→SC and PA→SC survival was not significant (Figure 4H), suggesting PA is not the sole driver of the enhanced mortality we see in KD.

Lastly, the most commonly studied models for inducing trained immunity are immunization with BCG or stimulation with β-glucan, and they have been shown to protect mice from systemic Candida albicans infection via lymphocyte-independent immunological reprogramming that leads to decreased kidney fungal burden (Kleinnijenhuis et al., 2012). Therefore, we next tested if PA treatment induces lymphocyte-independent clearance of C. albicans infection. For these experiments, Rag1 knockout (Rag1−/−) mice were treated with a vehicle or PA solution for 12 hr and subsequently infected intravenously (i.v.) with 2×106 C. albicans. In accordance with canonical trained immunity models, mice treated with PA for 12 hr showed a significant decrease in kidney fungal burden compared to Veh mice, 24 hr post-infection (Figure 4I). These are the first data to suggest PA enhances innate immune clearance of C. albicans in vivo.

OA reverses enhanced disease severity in WD- and KD-fed mice

We have reported here that diversion of ceramide synthesis reverses the PA-dependent hyper-inflammatory response to LPS in macrophages in vitro (Figure 3K–M). Interestingly, OA (C18:1) is a mono-unsaturated fatty acid naturally found in animal fats and vegetable oils, and in the presence of PA, diverts lipid metabolism away from ceramide production (Palomer et al., 2018; Listenberger et al., 2003). Considering OA and PA are the most prevalent fatty acids found in the human diet and in human serum (Palomer et al., 2018), we wanted to test if OA diversion of ceramide synthesis could reverse the PA-dependent hyper-inflammatory response to LPS in macrophages. Thus, we treated BMDMs with OA (0.2 mM), PA (0.5 mM), or OA and PA together for 12 hr and then with LPS. We found that macrophages simultaneously pre-treated with PA and OA produced significantly lower levels of TNF, IL-6, and IL-1β following subsequent LPS exposure, compared to BMDMs pre-treated with only PA prior to LPS stimulation (Figure 5A–C). These data reveal OA-dependent depletion of intracellular ceramides neutralizes the PA-dependent hyper-inflammatory response to LPS in macrophages.

Figure 5. Oleic acid (OA) reverses palmitic acid (PA)-dependent hyper-inflammation in response to lipopolysaccharide (LPS) in vitro, and PA-dependent enhanced endotoxemia disease severity in vivo.

Figure 5.

Primary bone marrow-derived macrophages (BMDMs) were isolated from age-matched (6–8 weeks) C57BL/6 female and male mice. BMDMs were plated at 1×106 cells/mL and treated with either media (Ctrl), LPS (10 ng/mL) for 24 hr, PA (PA stock diluted in 0.83% EtOH; 0.5 mM PA conjugated to 2% bovine serum albumin) for 12 hr, or OA (200 μM; diluted in endotoxin-free water). Controls for all treatments are shown next to experimental groups treated additionally with LPS (10 ng/mL) for 24 hr. Supernatants were assessed via ELISA for (A) TNF, (B) IL-6, and (C) IL-1β secretion. Age-matched (6–8 weeks) female BALB/c mice were fed standard chow (SC) or ketonic diet (KD) for 2 weeks and injected intraperitoneal with 7 mg/kg LPS. (D) Temperature loss and (E) survival were monitored every 2 hr. For (A–C), experiments were run three times and data are representative of (A) two experiments and (B, C) one experiment. For all plates, all treatments were performed in triplicate, and a student’s t-test was used for statistical significance. For (D), a Mann Whitney test was used for pairwise comparisons. For (E), a log-rank Mantel-Cox test was used for survival curve comparison. For (D, E), experiments were run three times, and data are representative of one experiment, n=5 mice/group. β symbols indicate KD + Veh vs KD + OA significance, and ∞ symbols indicate KD + Veh vs. SC + Veh. For all panels, *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001. Error bars shown mean ± SD.

Figure 5—source data 1. Data and statistics for graphs depicted in Figure 5A–E.

Considering this, we next wanted to know if i.p. injections of OA in KD-fed mice would mitigate enriched dietary SFA-associated disease severity and mortality. Thus, we fed age-matched (6–8 weeks) female BALB/c mice SC or KD for 2 weeks and injected them i.p. with 300 mM OA or Veh once per day for the final 3 days of feeding. We then injected LPS i.p. and measured hypothermia and survival. Veh-injected KD-fed mice showed significant and prolonged hypothermia starting at 8 hr p.i. compared to SC-fed mice (Figure 5D). In accordance with these findings, KD-fed mice displayed significantly enhanced mortality by 24 hr p.i. compared to 100% survival of SC-fed mice (Figure 5E). Strikingly, for KD-fed mice injected with 300 mM OA prior to LPS treatment, there was minimal temperature loss comparable to SC-fed mice, and 100% survival (Figure 5D and E). Together, these data show systemic OA can abrogate KD-dependent hypothermia and survival defect in response to LPS in mice-fed diets enriched solely in SFA and highlight the fascinating plasticity of dietary fatty acid reprogramming of innate immune cell populations and disease dynamics.

Discussion

In this study, we showed that mice-fed diets enriched in SFA exhibit hyper-inflammation during endotoxemia and poorer outcomes, compared with mice fed a standard low-SFA diet, independent of the diet-associated microbiome, ketosis, and the impact of each diet on LPS-induced hypoglycemia (Figure 1; Figure 1—figure supplement 1). Strikingly, we found that before LPS treatment, healthy mice fed a diet solely enriched in SFAs (KD) displayed significant expansion of HSCs, including MPPs, and harbored BMDMs, BM monocytes, and splenocytes that were not inherently more inflamed, but when challenged with LPS exhibited increased production of inflammatory cytokines (Figure 2; Figure 2—figure supplement 1, Figure 2—figure supplement 2). Since (Netea et al., 2020) we did not confer the hyper-inflammatory phenotype in BMDMs, BMMs, and splenocytes with WD, but only from KD-fed mice, and (Kleinnijenhuis et al., 2012) the KD is only enriched in SFAs and contains no sucrose, allowing us to ask questions specifically about SFAs, we chose to focus on the KD for the remainder of the study.

Considering the immunogenic properties of some dietary SFAs enriched in the KD, and that excess dietary SFAs are found circulating throughout the blood and peripheral tissues, we used lipidomics to identify dietary SFAs that may be directly reprogramming innate immune cells to respond more intensely to secondary inflammatory stimuli. Our study identified enriched PA (C16:0; PA) and PA-associated fatty acids in the blood of KD-fed mice (Figure 3; Figure 3—figure supplement 1). And, when we treated macrophages with physiologically relevant concentrations of PA, we found that PA alone induces a hyper-inflammatory response to secondary challenge with LPS (Figure 3; Figure 3—figure supplement 2). This enhanced production of inflammatory cytokines in response to secondary heterologous stimuli has been shown in previous models of innate immune memory, specifically trained immunity (Saeed et al., 2014; Christ et al., 2018; Bekkering et al., 2014). Furthermore, our data suggests PA induces trained immunity by showing that circulating inflammatory levels in PA-injected mice were not upregulated or in a primed state prior to LPS stimulation in vivo (Figure 4F), and PA-associated enhanced endotoxemia severity and mortality are still shown in mice rested for 7 days post-PA exposure (Figure 4G–H). Importantly, we have not fully defined the initial inflammatory response to PA in our model, thus our data only suggests trained immunity is induced by PA exposure. However, we do find that PA exacerbates the acute phase of endotoxin challenge and correlates with increased mortality but also enhances resistance to infection independent of mature lymphocytes (Figure 4). Together, our data concludes PA exposure can lead to hallmark phenotypes associated with canonical trained immunity models in vitro and in vivo.

Interestingly, the in vivo blood expression of cytokines for KD-fed mice following endotoxin challenge is mild in comparison to the cytokine secretion we show for BM monocytes, splenocytes, and BMDMs isolated from KD-fed mice treated with LPS ex vivo (Figure 1; Figure 2; Supplementary file 2). The media used for culturing and treating BM monocytes and splenocytes ex vivo with LPS contained a high-glucose concentration (4.5 g/L; 25 mM). However, high-glucose media does not alter TNF, IL-6, or IL-1β secretion, or mitochondrial metabolic activity, in WT BMDMs treated with LPS following 7 days of differentiation in high-glucose media (Ayala et al., 2019). Additionally, in these studies, metabolic adaptation likely takes place within 48 hr for BMDMs cultured in high-glucose media (Ayala et al., 2019); thus, we suggest it is unlikely that high glucose contributed to the significant augmentation of LPS-induced TNF and IL-6 secretion for BMDMs from KD-fed mice compared to controls, following 7 days of differentiation in high-glucose media prior to LPS challenge. However, further studies on the metabolic flexibility of the SC- and KD-BMDMs will be required to answer this question directly.

Additionally, we have previously shown that WD-induced weight gain does not correlate with enhanced endotoxemia severity and mortality in conventional mice (Napier et al., 2019). This is important to address because of the “obesity paradox” that describes the diversity in sepsis severity and mortality exhibited within the obese patient population, with some studies showing that obesity may even be protective in certain disease contexts (Ng and Eikermann, 2017). Humans on an animal-based KD that contains 76% fat with 30% SFA content, and 10% carbohydrates, experience ketosis within 1–2 weeks characterized by a three- to fourfold elevation in blood BHB levels and exhibit greater energy expenditure and weight loss compared to humans on a low-fat, plant-based diet that contains 10% fat and 75% carbohydrates (Hall et al., 2021). Likewise, KD-fed mice do not gain weight but show enhanced energy expenditure after 5 weeks of diet administration, and a trend toward weight loss during 9 weeks of diet exposure, compared to mice fed an SC diet (Kennedy et al., 2007). Thus, neither weight gain nor the obesity paradox is the confounding feature for the data we present here showing that both KD and dietary PA mediate innate immune memory in vivo during endotoxemia.

Furthermore, the metabolism of dietary SFAs is a key element of immune system function, and metabolic intermediates enhanced by SFAs and PA alone, such as ceramide, serve as signaling lipids in diseases of inflammation (Galadari et al., 2013). Mechanistically, we show that inhibiting ceramide synthesis or diverting metabolism away from ceramide synthesis using OA protects macrophages from PA-induced trained immunity, suggesting that dietary intervention may help regulate inflammatory dysregulation during disease (Figure 5). And, to complement our in vitro mechanistic findings we show that three single i.p. injections of OA prior to endotoxin stimulation protects KD-fed mice from enhanced disease severity and mortality (Figure 5).

Our findings align with the growing body of evidence indicating that trained immunity is a double-edged sword, where the phenomenon can be beneficial for resistance to infection but detrimental in the context of diseases exacerbated by systemic inflammation (DiNardo et al., 2021). Specifically, we show that PA-induced memory is beneficial in that it promotes clearance of C. albicans infection in the kidneys of Rag1−/− mice (Figure 4I). In stark contrast, PA-induced memory is detrimental in the context of endotoxemia, a disease driven by organ damage due to acute hyper-inflammation (Beutler et al., 1985; Mohler et al., 1993; Cunningham et al., 2002; Chen et al., 2012; Zhong et al., 2016; Figure 4G and H). Furthermore, it is known that trained immunity is a key feature of BCG vaccination, which has been shown to enhance resistance to infections, and is a possible mechanism that drives increased resistance to severe COVID-19 in the BCG-vaccinated population (Netea et al., 2016; Escobar et al., 2020). Thus, future research in understanding the plasticity of the SFA- and PA-regulated immune memory responses, enhanced pathogen clearance, and the mechanisms that drive this phenomenon, will be of interest to the larger medical community.

Mechanistically, it is appreciated that PA is not acting as a ligand for the pattern recognition receptor TLR4; however, the presence of TLR4 (independent of TLR4 signaling capability) is required for PA-dependent inflammation (Lancaster et al., 2018). Our data and others contribute to the growing evidence that PA is inducing cell intrinsic stress through alterations in metabolism. The crosstalk between glycolytic and oxidative metabolism, and epigenetics, is crucial for trained immunity in human monocytes, and metabolic intermediates of the TCA cycle directly modify histone methylation patterns associated with proinflammatory cytokines upregulated in trained immunity (Saeed et al., 2014; Arts et al., 2016; Ryan and O’Neill, 2020). While ceramides are known to modify histone acetylation and DNA methylation patterns (Silva et al., 2022), the interplay between ceramide metabolism and epigenetics within innate immune cells has not been explored. Though we have shown that PA-dependent ceramide production leads to innate immune memory, the impact of these alterations on the epigenome remains unknown. Therefore, the influence of ceramide metabolism on epigenetics will be important to consider in future trained immunity studies where PA serves as the primary stimulus.

Interestingly, we find here that immunoparalysis, which is associated with a prolonged septic response and is enhanced in patients with poorer outcomes, is greater in mice-fed diets enriched in SFAs (Figure 1; Gogos et al., 2000; van Dissel et al., 1998). However, we found that this SFA-dependent enhanced immunoparalysis is abrogated in GF mice, suggesting, for the first time, that the microbial species within the SFA-fed mice may be regulating the late immunoparalytic phase of endotoxin shock. Considering the clinical correlation of immunoparalysis and increased sepsis mortality, it will be imperative to explore the identity of the SFA-dependent microbiome and the host/microbe mechanisms that drive sepsis-associated immunoparalysis.

Importantly, previous seminal studies concluded that mice treated with antibodies to the TNF receptor and challenged with systemic LPS increased survival from 0% to nearly 100%, suggesting that acute inflammation driven by TNF is responsible for endotoxemia-related mortality (Beutler et al., 1985; Mohler et al., 1993). Furthermore, it has been shown that TNF is required for acute renal failure (Cunningham et al., 2002), lung injury (Chen et al., 2012), and liver damage (Zhong et al., 2016) during LPS challenge. These data show that acute inflammation, specifically the bioactivity of TNF, drives endotoxemia mortality and organ damage in conventional mice. It has also been shown that acute inflammation, specifically TNF production, is a driver of endotoxemia in GF mice (Souza et al., 2004). Thus, although our conventional mice show increased immunoparalysis, we suggest that early acute systemic inflammation is the driver of disease severity and mortality in both our conventional and GF endotoxemia mouse models; however, the data we present here is not sufficient to make this conclusion.

In conclusion, this unappreciated role of dietary SFAs, specifically PA, may provide insight into the long-lasting immune reprogramming associated with a high-SFA fed population, and lends insight into the complexity of nutritional immunoregulation. Considering the results in this study, we suggest the potential for SFAs such as PA to directly impact innate immune metabolism and epigenetics associated with inflammatory pathways. Thus, our findings are paramount not only for potential dietary interventions, but also treatment of inflammatory diseases exacerbated by metabolic dysfunction in humans.

Materials and methods

Cell lines and reagents

RAW 264.7 macrophages (from ATCC), CASP-1KO BMDMs, BMDMs, and BMMs were maintained in Dulbecco's Modified Eagle Medium (DMEM; Gibco) containing L-glutamine, sodium pyruvate, and high glucose supplemented with 10% heat-inactivated fetal bovine serum (FBS; GE Healthcare, SH3039603). BMDMs were also supplemented with 10% macrophage colony-stimulating factor (M-CSF; M-CSF-conditioned media was collected from National Institutes of Health (NIH) 3T3 cells expressing M-CSF, generously provided by Denise Monack at Stanford University).

Generation of BMDMs, BMMs, and splenocytes

BMDMs and BMMs were harvested from the femurs and tibias of age-matched (6–8 weeks) CO2-euthanized female BALB/c mice or male and female C57BL/6 J mice. BMDM media was supplemented with 10% M-CSF for differentiation, cells were seeded at 5×106 in petri dishes and cultured for 6 days, collected with cold PBS, and frozen in 90% FBS and 10% dimethyl sulfoxide (DMSO) in liquid nitrogen for later use. BMMs were isolated from BMDM fraction using EasySep Mouse Monocyte Isolation Kit (STEMCELL). Spleens were harvested from age-matched (6–8 weeks) CO2-euthanized female BALB/c mice, tissue was disrupted using the end of a syringe plunger on a 70-μm cell strainer and rinsed with FACS buffer (PBS + 2 mM EDTA). Cells were subjected to red blood cell lysis with RBC lysing buffer (Sigma) followed by neutralization in FACS buffer.

Treatments

After thawing and culturing for 5 days, BMDMs were pelleted and resuspended in DMEM containing 5% FBS, 2% endotoxin- and fatty acid-free BSA (Proliant Biologicals) and 10% M-CSF. Cells were seeded at 2.5×105 cells/well in 24-well tissue culture plates, treated with EtOH (1.69%, or 0.83%) 10 ng/mL LPS (Ultrapure LPS, Escherichia coli 0111:B4, Invivogen), 500 μM or 1 mM PA (Sigma-Aldrich, PHR1120), 10 uM FB1 (Sigma-Aldrich, F1147), or 200 μM OA (Sigma-Aldrich, O7501) and incubated at 37°C and 5% CO₂ for 12 or 24 hr. Next, cells were treated with an additional 10 ng/mL LPS and incubated an additional 12 or 24 hr. RAW 264.7 macrophages were thawed and cultured for 3–5 days, pelleted and resuspended in DMEM containing 5% FBS and 2% endotoxin- and fatty acid-free BSA, and treated identical to BMDM treatments. BMMs were seeded immediately after harvesting at 4×10^5 cells/well in 96-well V-bottom plates in DMEM containing 10% FBS and treated with LPS for 2 or 24 hr. Splenocytes were seeded immediately after harvesting at 1×105 cells/well in 96-well V-bottom plates in RPMI media with L-glutamine (Cytiva) containing 10% FBS and treated with LPS for 2 or 24 hr. BMDMs for ex vivo treatments were isolated as described above, plated at 2.5×105 cells/well in 24-well plates, and stimulated with 10 ng/mL LPS after 12 hr of adherence. For all treatments, supernatant was removed for ELISA analysis, and cells were lysed with TRIzol (ThermoFisher), flash-frozen in liquid nitrogen, and stored at –80°C until qRT-PCR analysis. For all plates, all treatments were performed in triplicate.

Flow cytometry

Modified panel using combined methods from Kaufmann et al., Nowlan et al., and Vasquez et al. Red blood cells were lysed in BM cells using RBC lysis buffer (Biolegend). BM cells (3×106 cells) were stained with viability stain Live/Dead Fixable Aqua (ThermoFisher) at the concentration of 1:200 for 30 min at 4°C. Next, cells were washed with FACS buffer (PBS supplemented with 0.5% BSA; Proliant Biologicals, fatty acid free), and incubated with anti-CD16/32 (clone 93, BioLegend) at a concentration of 1:100 in FACS buffer for 10 min at 4°C. The following antibodies were then used for staining HSCs, and MPPs: anti-Ter-110, anti-CD11b (clone M1/70), anti-CD5 (clone 53–7.3), anti-CD4 (clone RM4-5), anti-CD8a (clone 53–6.7), anti-CD45R (clone RA3-6B2), and anti-Ly6G/C (clone RB6-8C5), all biotin-conjugated (all BD Bioscience), were added at a concentration of 1:100 for 30 min at 4°C and washed with FACS buffer. Streptavidin-APC-Cy7 (eBioscience), anti-CD150-eFluor450 (clone Q38-480, eBioscience), anti-CD48-PerCPeFluor710 (BD Bioscience), anti-Flt3-PE (clone A2F10.1, BD Bioscience), anti-CD34-PEDazzle 594 (clone HM34, BioLegend), anti-CD27-PE-Cy7 (eBioscience), and anti-CD201-APC (eBioscience) were added all at a concentration of 1:100 for 20 min at 4°C. All cells were then washed with FACS buffer before and after incubation in 1% paraformaldehyde for 30 min at 4°C. Cells were acquired on BD flow cytometer (FACSymphony A1 Cell Analyzer) with FACSDiva Software. Analyses were performed using FlowJo software v.10.1. The DownSample version 3.3.1 plugin was used to standardize events for each sample after populations were gated.

Lactate dehydrogenase assays

BMDMs were cultured as stated above with culture media, PA, or ethanol in 96-well tissue-culture plates at a concentration of 5×104 cells/well and incubated for 12 hr. Cells were treated with PBS or 10 ng/mL LPS in a phenol-red-free Optimem media (ThermoFisher) and incubated an additional 12 or 24 hr. Supernatants were collected at the specified time points with LDH release quantified with a CytoTox96 Non-Radioactive Cytotoxicity Assay (Promega). Cytotoxicity was measured per well as a percentage of max LDH release, with background media-only LDH release subtracted. For all plates, all treatments were performed in triplicate.

Measurement of cell viability

Cell viability was determined by 0.4% Trypan Blue dye exclusion test executed by a TC20 Automated Cell Counter (Bio-Rad).

Blood RNA extraction and real-time qPCR

Mice were treated with PBS or LPS, and at specified time points 10–20 μL of blood was collected from the tail vein, transferred into 50 μL of RNALater (ThermoFisher Scientific), and frozen at –80°C. RNA extractions were performed using RNeasy Mini Kit (Qiagen), and cDNA was synthesized from RNA samples using SuperScript III First-Strand synthesis system (Invitrogen). Gene-specific primers were used to amplify transcripts using SsoAdvanced Universal SYBR Green Supermix (Bio-Rad). A complete list of all primers used, including the names and sequences, is supplied as Supplementary file 2.

Enzyme-linked immunosorbent assay

TNF, IL-6, and IL-1β concentrations in mice serum were measured and analyzed using TNF, IL-6, and IL-1β Mouse ELISA kits (ThermoFisher Scientific), according to the manufacturer’s instructions. Absorbances were measured at a wavelength of 450 nm using a microplate reader (BioTek Synergy HTX). Values below the limit of detection (LOD) of the ELISA were imputed with LOD divided by 2 (LOD/2) values.

LPS-induced endotoxemia model

Age-matched (6–8 weeks) female BALB/c mice were anesthetized with isoflurane and injected subcutaneously with ID transponders (Bio Medic Data Systems). 2 weeks post diet change, and 1 week post ID transponder injection, mice were stimulated with a single injection of 6–10 mg/kg LPS reconstituted in endotoxin-free LAL reagent water (Invivogen) and diluted in PBS for a total volume of 200 μL. Control mice received corresponding volumes of PBS. Progression of disease was monitored every 2 hr after LPS injection for clinical signs of endotoxin shock based on weight, coat and eyes appearance, level of consciousness, and locomotor activity. Age-matched (20–21 weeks) female C57BL/6 mice were treated as described above, except for their LPS dose (4.5 mg/kg). Temperature was recorded using a DAS-8007 thermo-transponder wand (Bio Medic Data Systems). For PA injections, a solution of 750 mM ethyl palmitate (Millipore Sigma), 1.6% lecithin (Sigma-Aldrich), and 3.3% glycerol was made in endotoxin-free LAL reagent water (Lonza). The lecithin-glycerol-water solution was used as a vehicle, and mice were injected with 200 μL of the vehicle as a control or ethyl palmitate solution to increase serum PA levels. For OA injections, a solution of 300 mM OA (Sigma-Aldrich) was made using the same solution and vehicle described above. Mice were injected i.p. with 200 μL of the vehicle as a control, or OA solution, between 7 and 9 pm for 3 days prior to LPS exposure.

Mouse diets, glucose, and ketones

Six-week-old female mice were fed soft, irradiated chow (PicoLab Mouse Diet 20, product 5058) and allowed to acclimate to research facility undisturbed for 1 week. Chow was replaced by WD (Envigo, TD.88137), KD (Envigo, TD.180423), or SC (Envigo, TD.08485), and mice were fed ad libitum for 2 weeks before induction of endotoxemia. For KD, food was changed daily. For WD, food was changed every 72 hr. Ketones and blood glucose were measured weekly and immediately prior to LPS injections with blood collected from the tail vein using Blood Ketone and Glucose Testing Meter (Keto-Mojo), or with urine collected on ketone indicator strips (One Earth Health, Ketone Test Strips).

Statistics analysis

Mann Whitney, Mantel-Cox, and student’s t-tests were carried out with GraphPad Prism 9.0 software.

Ethical approval of animal studies

All animal studies were performed in accordance with NIH guidelines, the Animal Welfare Act, and US federal law. All animal experiments were approved by the Oregon Health and Sciences University (OHSU) Department of Comparative Medicine or Oregon State University (OSU) Animal Program Office and were overseen by the Institutional Care and Use Committee (IACUC) under Protocol IDs #IP00002661 and IP00001903 at OHSU and #5091 at OSU. Conventional animals were housed in a centralized research animal facility certified by OHSU. Conventional 6–10-week-aged female BALB/c mice (Jackson Laboratory 000651) were used for the endotoxemia model, and isolation of BMDMs, BMMs, and splenocytes. GF male and female C57BL/6 mice (Oregon State University; bred in house) between 14- and 23-week-old were used for the GF endotoxemia model. BALB/c Rag1−/− mice between 8 and 24 weeks were infected i.v. with 2×106 CFUs of C. albicans SC5314 (ATCC #MYA-2876), and kidney fungal burden was assessed 24 hr post-infection. Kidneys were harvested 24 hr post-infection, and homogenized organs were plated in serial dilutions on Yeast Peptone Dextrose plates to assess fungal burden.

Lipidomics PCA analysis

Mice on specialized diets were sacrificed at the indicated time points after PBS or LPS treatment with 300–600 µL of blood collected via cardiac puncture into heparinized tubes. Blood samples were centrifuged for 15 min at 2500 rpm at 4°C, and serum was transferred to a new tube before storage at –80°C. Serum samples were analyzed via LC-MS/MS. Lipidomic data sets were scaled using the scale function, and PCAs were performed using the prcomp function from the stats package in R Version 3.6.2. Visualization of PCAs and biplots was performed with the fviz_pca_ind and fviz_pca_biplot functions from the factoextra package and with the ggplot2 package (Mundt and Weisweiler, 2017; Wickham, 2016). For each diet group, 95% confidence ellipses were plotted around the group mean using the coord.ellipse function from the FactoMineR package (Lê, 2008). Heatmaps were created using the pheatmap package (Kolde, 2018).

Acknowledgements

We would like to thank Ajesh Saini, a student in the Napier Lab, for his contributions in carrying out the ELISA data within this manuscript. This study was supported by National Institute of General Medical Sciences (NIGMS) grant 5R35GM133804-02 to B.A.N.

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Brooke A Napier, Email: brnapier@pdx.edu.

Jos W van der Meer, Radboud University Medical Centre, Netherlands.

Jos W van der Meer, Radboud University Medical Centre, Netherlands.

Funding Information

This paper was supported by the following grants:

  • NIGMS/NIH R35GM133804 to Brooke A Napier.

  • National Institute of General Medical Sciences to Brooke A Napier.

  • US Department of Veterans Affairs VA CDA2 BLRD 1K2BX004523 to Ruth J Napier.

Additional information

Competing interests

No competing interests declared.

No competing interests declared.

Author contributions

Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing.

Data curation, Software, Formal analysis, Validation, Investigation, Methodology, Writing - review and editing.

Conceptualization, Data curation, Formal analysis, Investigation, Methodology.

Data curation, Formal analysis, Investigation.

Investigation, Methodology.

Data curation, Investigation.

Resources, Project administration.

Conceptualization, Resources, Data curation, Investigation, Project administration.

Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing.

Ethics

This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#IP00002661 & IP00001903) of Oregon Health & Sciences University and Oregon State University (#5091). All animal experiments were approved by the Oregon Health and Sciences University (OHSU) Department of Comparative Medicine or Oregon State University (OSU) Animal Program Office and were overseen by the Institutional Care and Use Committee (IACUC).

Additional files

Supplementary file 1. Diet compositions (values represent percentage of total kcal).
elife-76744-supp1.docx (18.5KB, docx)
Supplementary file 2. List of primers used in this study.
elife-76744-supp2.docx (13.5KB, docx)
Transparent reporting form

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting file.

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Editor's evaluation

Jos W van der Meer 1

This fundamental paper in mice convincingly demonstrates that a Western-type diet and the more extreme ketogenic diet for 2 weeks enhance monocyte-driven immune responsiveness. This leads to a deadly hyper-inflammatory state in the mice in response to an endotoxin challenge in vivo and enhances the clearance of pathogens. The paper is of interest to immunologists, infectious disease specialists, and nutritionists.

Decision letter

Editor: Jos W van der Meer1
Reviewed by: Maziar Divangahi2

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]

Thank you for submitting the paper "Dietary palmitic acid induces innate immune memory via ceramide production that enhances severity of acute septic shock and clearance of infection" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Maziar Divangahi (Reviewer #2).

Comments to the Authors:

We are sorry to say that, after consultation with the reviewers, we have decided that this work will not be considered further for publication by eLife.

Specifically, the shortcomings of the paper, which are detailed in the reviews below, are such that the work required for an acceptable revision cannot be delivered within the 8 weeks that we allow.

Reviewer #1 (Recommendations for the authors):

1. Presumably Figure 1 panels J-N are data stemming from both male and female mice. Although this is great for sexual diversity and representation in scientific studies. This decision is weakened by 2 issues (1) the sample sizes are very small, and therefore don't allow the authors to investigate sex specific difference in the mice's response to diet and LPS. (2) In humans males and females show hugely different responses to endotoxemia challenge [PMID: 17452928]. According to a fairly recent PLoS ONE publication [PMID: 27631979] these sex differential responses are also present in mice, where male mice have a greater inflammatory response and have more severe outcomes. Since readers aren't given any insight into the sex distribution of the mice in each group it is impossible to decide if the data are skewed/biased. In order to improve the robustness of the authors findings, these studies should be repeated with mice sharing a single sex, or be performed with greater numbers (n=>12) with equal distribution of sexes in each dietary group.

2. Figure 4 D – F shows the OA for 12h followed by LPS for 24h induces the greatest levels of cytokines. In fact, what's worrying with these data is that the effect of "PA-12h◊LPS-24h" vs "LPS-24h" is not recapitulated from the previous results shown in Figure 4 panels A – C; at least the authors don't display the results of statistical tests for panels D – F, however comparing the cytokine levels it's clear that the PA treatment didn't generate the same cytokine levels. How do the authors explain these results? Also why isn't the highly cytokine inducing potential of OA not described in the Results section? In fact what is shown in Panels D – F is that PA treatment reverses the inflammation induced by OA, rather than the other way around that the authors claim to be the case. These experiments should be repeated, showing a significant change from "LPS-24h" to "PA-12h-->LPS-24h" as in panels Figure 4 A – C. The authors should also address the effect of OA on LPS responsiveness.

I would like to politely highlight a concern of mine, the authors appear to have purposefully chosen their color scheming to throw the eye off from noticing the effect of "OA-12h-->LPS-24h". Notice how in panels A – C "PA-12h-->LPS24h" is colored in blue, while in panels D – F "PA-12h◊LPS-24h" is colored in grey and "OA-12h-->LPS-24h" is colored in blue. Skimming of the figures, one could easily mistake that both blue columns represent "PA-12h-->LPS-24h", completely overlooking that OA is inducing high levels of cytokines and that the authors failed to reproduce their own results. The authors should use the same color coding for both sets of figures.

3. Dietary intervention studies are difficult, and often difficult decisions have to be made when designing your studies. One of these difficult decisions is how to design the macronutrient contributions to the total caloric intake of the mice. A choice could be made to, for example, to fix the percentage or mg of protein to the caloric total. In this way it is possible control for the effect that altering protein availability will have on LPS challenge. For example protein intake effects the survivaly of critically ill patients – some with sepsis [PMID: 29709380]. Can the authors justify their decision for the nutrient composition used in their study?

4. In basic/functional science it's important to make reductionist groupings for the sake of clear comparisons (also for financial reasons). However, what may give you the clearest separation in your analysis may impact the translatability of the data to the broader, medical context. Here the authors have decided to compare standard chow diets (SC) with the ketogenic diet (KD), as opposed to the potentially more interesting (from the epidemiological perspective at least) Western-diet (WD). It is unsurprising that eliminating most carbohydrates from ones diet will result in gross changes in systemic metabolism and circulating lipid profiles. However how common are septic events in people practicing the ketogenic diet? For a lay audience this may convey the message that ketogenic diet – per se – is a major contributor to septic death. Naturally the authors tie these results to dietary palmitic acid, where supplementation alone is able to confer these negative effects. However I think the manuscript would benefit from a small sentence in the results prior to Figure 2 outlining why they chose to focus on KD rather than WD.

5. The description of the methods are rather poor, but also there appear to be many inconsistencies in the methods themselves. In the legend of Figure 1 the authors use "conventional mice" aged 4-6 weeks for the data shown in panel A – F, while through panel G – N the switch to C57BL/6 mice that are 19-23 weeks old female or 14-23 weeks for male mice; using a unreported mixture of the sexes. Additionally, the younger mice receive 6 mg/kg of LPS, while the older mice receive 50 mg/kg of LPS. Later on in Figure 5, switching back to the younger 4-6 week mice (all female), the authors switch again to 10 mg/kg of LPS. The RAG -/- mice are represent a third age group used in the study (8-9 weeks old). I see this as a major, and limiting aspect of the presented work. If it's within the power of the authors, I would advocate for repeating the mice studies in the paper with a single, standardized protocol. Using mice from the same background, sex, age, and to receive the same injection of LPS.

Reviewer #2 (Recommendations for the authors):

In this manuscript entitled "Dietary palmitic acid induces innate immune memory via ceramide production that enhances severity of acute septic shock and clearance of infection" Seufert and colleagues have investigated how saturated fatty acids increase susceptibility of the host in a murine model of LPS-mediated septic shock. They have shown that pretreatment of macrophages with palmitic acid (PA) reprograms macrophages towards hyper-inflammatory phenotype, which was dependent on ceremide. Importantly, depletion of macrophages intracellular ceremide with oleic acid reverse their hyper-inflammatory phenotype. Interestingly, while PA was harmful in the LPS-acute septic shock model, it was beneficial in clearance of C. albicans in Rag deficient mice lacking both B and T cells. While this is an exciting study, the presented data don't fully support the central hypothesis and the link with trained immunity is currently weak.

1. Training: As the authors described in the result section the difference between priming and training: "priming occurs when the first stimulus enhances transcription of inflammatory genes and doesn't return to basal levels before the secondary stimulation. In contrast, trained immunity occurs when the first stimulus changes transcription of inflammatory genes, the immune status then returns to basal levels, and challenges with homologous or heterologous stimulus enhances transcription of inflammatory cytokines at much higher levels than those observed during the primary challenge". However, the presented in vitro data are priming (Figure 3 and 4) and not training, as the interval between the first (PA) and secondary (LPS) stimulus was extremely short. Indeed, PA often increased the expression or production of inflammatory cytokines, in which was augmented following LPS stimulation. Epigenomic/transcriptomic approaches can more precisely distinguish between priming and training. I would suggest the authors to move the definition of priming vs training from the result section to the introduction.

2. Microbiome: In Figure 1H-N, by using GF-mice, the authors indicated that SFA-driven enhanced responses to systemic LPS was independent of microbiome. However, the mortality was increased by 50% in SC-GF (Figure 1I) mice compared to SC-WT (Figure 1B) mice. Thus we could argue that the increased mortality in control groups was dependent on microbiome while it was masked in super susceptible WD/KD groups. This needs to be carefully addressed.

3. Cellular sources: In Figure 1, the authors assess the expression of several pro-inflammatory genes as well as an anti-inflammatory gene in blood, which composed of 90% lymphocytes and only 5-10% myeloid cells. Thus it is not clear to this reviewer that how the increased expression of these genes are linked to trained innate immunity. Similarly, in Figure 2, the authors showed that the expression of TNF was increased in splenocytes (>80% lymphocytes) of KD mice after ex-vivo stimulation with LPS. So, without knowing the cellular sources of these cytokines, it is challenging to directly link the expression of inflammatory genes to innate cells. Furthermore, the authors need to provide the level of circulating cytokine by simply using ELISA. Considering the overlapping error bars in evaluating of many gene expressions statistical analysis needs to be double checked.

4. Hematopoietic stem cells: In Figure 2, the authors showed that monocytes isolated from BM of KD-mice expressed higher levels of TNF and IL6 following ex-vivo LPS stimulation. These data indicate that the potential impact of SFAs is on HSCs and progenitor cells. I would highly recommend the authors to consdier two experiments to provide more direct link between SFAs and trained immunity. First, to assess the impact of SFAs or PA on HSCs and myeloid progenitor cells by FACS as it has been done in the BCG model (Kaufmann et al., 2018). Second, to generate BMDM from SFAs and SC mice and then stimulate them with LPS or infect them with C. albicans, ex-vivo. As the generation of BMDM will take 5-7 days, any initial imprinting by SFAs can be transmitted from the progenitor cells to macrophages. Thus if there is an alteration in HSCs and progenitor cells, this can provide mor evidence of central training and its long-term effects on immunity to sterilized immunity (LPS) or infections (e.g. C. albicans). This will also provide more support for Figure 5H-I.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Enriched dietary saturated fatty acids induce trained immunity via ceramide production that enhances severity of acute septic shock and clearance of infection" for further consideration by eLife. Your revised article has been evaluated by Jos van der Meer (Senior Editor) and a Reviewing Editor.

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

The authors have wonderfully addressed the comments, and have resubmitted a very strong and thorough study on the role of dietary fatty acids on the induction of in vivo trained immunity. The manuscript is nearly ready for publication, especially considering the novelty and strength of their findings, not to mention the relevance to the field of trained immunity as well as metainflammation. There are however a few final comments on the present manuscript.

The first thing is the so-called 'obesity paradox'. People overweight or with obesity are generally protected from deadly/lethal septicemia when compared to normal or underweight individuals. Two weeks of high-fat feeding may not be sufficient to induce obesity, however, it would be interesting to know if the mice have gained weight. It would be of interest to briefly discuss the clinical conundrum of the 'obesity paradox', especially given the highly lethal phenotype of WD and KD-fed mice in for example Figure 1B.

With sepsis, the general course of the disease is indeed hyper-inflammation leading to organ failure and death, or immune paralysis and increased risk of mortality via secondary infection. Given that your data suggest that the mice indeed enter into the immune-paralyzed state, do you have any data to show whether the mice died from organ failure or secondary infections? Regardless of the phenotype, WD or KD-fed mice are more susceptible to lethal responses to LPS. Germ-free mice similarly show lethality making the effect clearer to being the result of organ failure/damage. Though, the cytokines, especially IL-10 make this distinction even murkier. The germ-free clearly look as though they are dying from hyper-inflammation, while the BALB/c mice are seemingly dying in the immune-paralyzed state; given they aren't germ-free and are susceptible to secondary infection with commensals. How would the authors rationalize this?

Sepsis is a medical term that describes an infection of the blood. In your model, LPS is used to induce systemic inflammation. Although many of the symptoms and effects overlap profoundly with those seen in sepsis, we advise against using the term sepsis to describe your model since no infection is established. Endotoxin challenge, or endotoxin stimulation, is more appropriate/accurate semantics.

Page 17 lines 461 – 463 reading: "Our findings align with the growing body of evidence indicating that trained immunity is a double-edged sword, where the phenomenon can be beneficial for resistance to infection, but detrimental in the context of inflammatory disease." This reads a bit off given that, in fact, your model uses a bacterial-derived stimulus to induce a lethal inflammatory response in WD and KD-'trained' mice. You could hardly call this a beneficial effect of trained immunity.

A technical hurdle for figure 3 is that the mice are on a ketogenic diet, cells are harvested, and then brought into culture with glucose-enriched media. We wonder then how the sudden overabundance of glucose might contribute to the elevated cytokine responsiveness seen in the data presented in these figure panels, as opposed to the ketogenic diet per se giving rise to increased immune responsiveness. It is worth saying that the in-vivo cytokine responses are much milder than what's seen ex vivo.

eLife. 2022 Oct 20;11:e76744. doi: 10.7554/eLife.76744.sa2

Author response


[Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]

Reviewer #1 (Recommendations for the authors):

1. Presumably Figure 1 panels J-N are data stemming from both male and female mice. Although this is great for sexual diversity and representation in scientific studies. This decision is weakened by 2 issues (1) the sample sizes are very small, and therefore don't allow the authors to investigate sex specific difference in the mice's response to diet and LPS. (2) In humans males and females show hugely different responses to endotoxemia challenge [PMID: 17452928]. According to a fairly recent PLoS ONE publication [PMID: 27631979] these sex differential responses are also present in mice, where male mice have a greater inflammatory response and have more severe outcomes. Since readers aren't given any insight into the sex distribution of the mice in each group it is impossible to decide if the data are skewed/biased. In order to improve the robustness of the authors findings, these studies should be repeated with mice sharing a single sex, or be performed with greater numbers (n=>12) with equal distribution of sexes in each dietary group.

The Reviewer brings up an important point, all studies with endotoxemia in wild-type conventional mice were carried out in 6–8-week female BALB/c mice, as mentioned in the Methods section under “Ethical approval of animal studies” and “endotoxin-induced model of sepsis” sections. This is extremely important to mention more clearly in the results text, because the Reviewer 1 is correct, sexual dimorphism and age differences can have very large effects on LPS treatment outcome. This was not stated clearly enough in the results and now the age, sex, and background of mice have been explicitly stated in each Results and Figure Legend section for each experiment.

2. Figure 4 D – F shows the OA for 12h followed by LPS for 24h induces the greatest levels of cytokines. In fact, what's worrying with these data is that the effect of "PA-12h◊LPS-24h" vs "LPS-24h" is not recapitulated from the previous results shown in Figure 4 panels A – C; at least the authors don't display the results of statistical tests for panels D – F, however comparing the cytokine levels it's clear that the PA treatment didn't generate the same cytokine levels. How do the authors explain these results? Also why isn't the highly cytokine inducing potential of OA not described in the Results section? In fact what is shown in Panels D – F is that PA treatment reverses the inflammation induced by OA, rather than the other way around that the authors claim to be the case. These experiments should be repeated, showing a significant change from "LPS-24h" to "PA-12h-->LPS-24h" as in panels Figure 4 A – C. The authors should also address the effect of OA on LPS responsiveness.

I would like to politely highlight a concern of mine, the authors appear to have purposefully chosen their color scheming to throw the eye off from noticing the effect of "OA-12h-->LPS-24h". Notice how in panels A – C "PA-12h-->LPS24h" is colored in blue, while in panels D – F "PA-12h◊LPS-24h" is colored in grey and "OA-12h-->LPS-24h" is colored in blue. Skimming of the figures, one could easily mistake that both blue columns represent "PA-12h-->LPS-24h", completely overlooking that OA is inducing high levels of cytokines and that the authors failed to reproduce their own results. The authors should use the same color coding for both sets of figures.

The reviewer brings up an important point, Eguchi et al. did use infusions. From their data (Figure 1A), we calculated that after 600mM of i.v. injection (total = 267uL within 14h; 0.2L/min) there was ~420uM absolute PA within the blood. They were using C57BL/6 mice that were 23g on average. Using these results, we extrapolated that one single 200uL injection of a 750mM PA solution within 6–8-week female BALB/c mice (~15-18g) would equate to ~500-1mM of PA within the blood. Considering obese healthy and unhealthy humans vary widely in total PA concentrations in the blood (0.3-4.1 mM) (1, 2), we moved forward with these calculations. Considering this, we thank the reviewer for this advice, and we agree that we have not definitively shown we are increasing systemic levels of PA. Thus, we ran a lipidomic analysis of serum from SC-fed mice with Veh or PA for 12 h. We show that a 750 mM i.p. injection of ethyl palmitate enhances free PA levels in the serum to 173-425 μM at 2 h post-injection, which is within the reported range for humans on high-fat diets (0.34.1mM). We have added this new data to Figure S7A of the main manuscript.

Importantly, the concentration in the PA-treated mice is greater than that of the Veh-treated mice, however we believe the value shown is an underestimate of maximum serum PA levels enhanced by i.p. injection, because free PA is known to be packaged into chylomicrons within enterocytes and travel through the circulation with a half-life of less than an hour (3, 4). Thus, serum concentrations of free PA are only transiently enhanced by i.p. injection, and is quickly taken up by adipose tissue, skeletal muscle, heart, and liver tissue. These complex lipid transport processes make it difficult to determine maximum concentrations of free PA in the serum.

While all of the details concerning PA circulation following an i.p. injection are unknown, we suggest that this method of “force-feeding” is similar to dietary intake in that uptake of PA into the circulation occurs within the peritoneal space prior to traveling to the blood via the thoracic duct and right lymphatic duct (5).

3. Dietary intervention studies are difficult, and often difficult decisions have to be made when designing your studies. One of these difficult decisions is how to design the macronutrient contributions to the total caloric intake of the mice. A choice could be made to, for example, to fix the percentage or mg of protein to the caloric total. In this way it is possible control for the effect that altering protein availability will have on LPS challenge. For example protein intake effects the survivaly of critically ill patients – some with sepsis [PMID: 29709380]. Can the authors justify their decision for the nutrient composition used in their study?

The reviewer brings up an important and nuanced topic in the immunometabolism field. Our diets are created by Envigo, and each diet (SC, WD, and KD) contain the same vitamin mixes, carbohydrate, and fat sources.

We originally conducted experiments in SC and WD to understand the role of high SFA and sucrose on reprogramming innate immune populations (7). However, in this study we wanted identify if enriched SFA alone could recapitulate these results. The mice were tolerant to the Envigo KD, so we continued our studies. We specifically state this within the Results section, but considering this important point, we have added these diet details within the Supplemental Table 1.

It is important to note, the KD has depleted protein (9.1% compared to 17% and19% in SC and WD, respectively). Our studies have not ruled out that low protein is involved in the response to systemic LPS; however, we have recapitulated these results in short-term PA-treated mice (fed SC; Figure 4A-F) and long-term PA-treated mice (fed SC; Figure 4G-H) suggesting that regardless of the effect of low protein on this model, enriched SFA is sufficient to drive hyper-sensitivity to systemic LPS.

4. In basic/functional science it's important to make reductionist groupings for the sake of clear comparisons (also for financial reasons). However, what may give you the clearest separation in your analysis may impact the translatability of the data to the broader, medical context. Here the authors have decided to compare standard chow diets (SC) with the ketogenic diet (KD), as opposed to the potentially more interesting (from the epidemiological perspective at least) Western-diet (WD). It is unsurprising that eliminating most carbohydrates from ones diet will result in gross changes in systemic metabolism and circulating lipid profiles. However how common are septic events in people practicing the ketogenic diet? For a lay audience this may convey the message that ketogenic diet – per se – is a major contributor to septic death. Naturally the authors tie these results to dietary palmitic acid, where supplementation alone is able to confer these negative effects. However I think the manuscript would benefit from a small sentence in the results prior to Figure 2 outlining why they chose to focus on KD rather than WD.

We respect the opinion of the reviewer, and suggest the KD was a jumping off point for identifying enriched saturated fatty acids and understanding the more interesting mechanistic data provided by Figures 2-5. We chose the KD diet because it was only enriched in SFA and not glucose, like the WD. We agree with the reviewer that a sentence in the Results prior to Figure 3 outlining why we chose the KD rather than the WD is needed. Thus, we have addressed the reviewers concern and have explained why we chose to focus on the KD diet exclusively in the beginning of the Results section, “Palmitic acid (PA) and PA-associated fatty acids are enriched in the blood of KD-fed mice.” We state, “Considering that the KD is enriched in SFAs and not sucrose, and that KD-fed mice showed distinct HSC alterations and LPS-induced hyper-inflammation in BMDMs, BMMs, and splenocytes treated ex vivo (Figure 2; S2), the subsequent studies were performed exclusively on KD-fed mice.”

5. The description of the methods are rather poor, but also there appear to be many inconsistencies in the methods themselves. In the legend of Figure 1 the authors use "conventional mice" aged 4-6 weeks for the data shown in panel A – F, while through panel G – N the switch to C57BL/6 mice that are 19-23 weeks old female or 14-23 weeks for male mice; using a unreported mixture of the sexes. Additionally, the younger mice receive 6 mg/kg of LPS, while the older mice receive 50 mg/kg of LPS. Later on in Figure 5, switching back to the younger 4-6 week mice (all female), the authors switch again to 10 mg/kg of LPS. The RAG -/- mice are represent a third age group used in the study (8-9 weeks old). I see this as a major, and limiting aspect of the presented work. If it's within the power of the authors, I would advocate for repeating the mice studies in the paper with a single, standardized protocol. Using mice from the same background, sex, age, and to receive the same injection of LPS.

We appreciate this review and suggest that:

1) For the LPS models, mice were all female and aged matched between 6-8 weeks. We are aware of sex differences in the endotoxemia model, which is why we specifically use female mice in our studies (6, 7). This is mentioned twice in the methods under the sections “Endotoxin-induced model of sepsis” and “Ethical approval of animal studies”. We have added these specifics of our model to all Results and Figure Legend sections for clarification.

2) For Germ-free models, it is notoriously difficult to breed C57BL/6 germ-free mice. It was inherently difficult to obtain enough mice within the same sex and age to carry out these experiments, however since we have published in this model before with mixed sex and age we were aware that our WD phenotype is robust enough in these backgrounds (7). Further, we believe that seeing our robust phenotype independent of age or sex within germ-free mice provides more evidence of the strength of this phenotype. It is important to note that we induce endotoxemia within Germ-free mice with 50mg/kg, instead of 6mg/kg which is used in conventional mice, because this is our reported LD50 for mixed sex Germ-free C57BL/6, as we have published previously in detail (7). This difference is due to the presence of the microbiota (8, 9) and also germ-free mice have an immature immune system that correlates with a hypo-responsiveness to microbial products (10-12). We agree with the reviewer that the ages of the C57BL/6 germ-free mice are significantly older than our conventional 6-8 week mice, thus we confirmed that WD- and KD-fed conventional C57BL/6 female mice aged 20 – 21 weeks old still show enhanced disease severity and mortality in an LPS-induced endotoxemia model, compared to mice.

3) In our preliminary results, we stratified survival during C. albicans infection between male and female C57BL/6 and found no notable difference in survival at 40h post IP infection with Candida albicans (Author response image 1A-B). However, the data presented in the manuscript on CFU is female kidney burden and we do not have data on fungal burden within male mice. This is an important piece of data that we would like to collect for understanding sex differences in the PA-dependent enhanced resistance to systemic C. albicans. We are currently addressing this question within the lab as well as elucidating the cell type and mechanism of PA-dependent enhanced fungal resistance.

Author response image 1. PA treatmentenhances survival in both female and male RAG-/- mice.

Author response image 1.

Age-matched (8-9 wk) RAG-/- mice were injected i.v. with ethyl palmitate (PA, 750mM) or vehicle (Veh) solutions 12 h before C.albicans infection. Survival was monitored for 40h post-infection fed SC (Figure S1G-H).

Reviewer #2 (Recommendations for the authors):

In this manuscript entitled "Dietary palmitic acid induces innate immune memory via ceramide production that enhances severity of acute septic shock and clearance of infection" Seufert and colleagues have investigated how saturated fatty acids increase susceptibility of the host in a murine model of LPS-mediated septic shock. They have shown that pretreatment of macrophages with palmitic acid (PA) reprograms macrophages towards hyper-inflammatory phenotype, which was dependent on ceremide. Importantly, depletion of macrophages intracellular ceremide with oleic acid reverse their hyper-inflammatory phenotype. Interestingly, while PA was harmful in the LPS-acute septic shock model, it was beneficial in clearance of C. albicans in Rag deficient mice lacking both B and T cells. While this is an exciting study, the presented data don't fully support the central hypothesis and the link with trained immunity is currently weak.

1. Training: As the authors described in the result section the difference between priming and training: "priming occurs when the first stimulus enhances transcription of inflammatory genes and doesn't return to basal levels before the secondary stimulation. In contrast, trained immunity occurs when the first stimulus changes transcription of inflammatory genes, the immune status then returns to basal levels, and challenges with homologous or heterologous stimulus enhances transcription of inflammatory cytokines at much higher levels than those observed during the primary challenge". However, the presented in vitro data are priming (Figure 3 and 4) and not training, as the interval between the first (PA) and secondary (LPS) stimulus was extremely short. Indeed, PA often increased the expression or production of inflammatory cytokines, in which was augmented following LPS stimulation. Epigenomic/transcriptomic approaches can more precisely distinguish between priming and training. I would suggest the authors to move the definition of priming vs training from the result section to the introduction.

We thank the reviewer for their thoughtful comments on this topic. We agree, and thus, we have added to Introduction of the manuscript, we describe the difference between priming and trained immunity with the following, “Importantly, trained immunity is induced when a primary inflammatory stimulus changes transcription of inflammatory genes, the immune status returns to basal levels, and challenge with a homologous or heterologous stimulus enhances transcription of inflammatory cytokines at much higher levels than those observed during the primary challenge (14). While the dynamics of basal inflammation are not defined in this paper, we show that basal levels of tnf, il-6, il-1β and il-10 in the blood of mice pre-exposed to PA were comparable to control mice immediately prior to LPS-induced sepsis, indicating that mice were not in a primed state prior to disease. This suggests that the hyper-inflammation and poor disease outcome we show in PA-exposed mice is due to trained immunity, and not priming.”

Importantly, the additional ex vivo experiments this Reviewer suggests in point #4 has addressed this trained immunity phenotype further.

2. Microbiome: In Figure 1H-N, by using GF-mice, the authors indicated that SFA-driven enhanced responses to systemic LPS was independent of microbiome. However, the mortality was increased by 50% in SC-GF (Figure 1I) mice compared to SC-WT (Figure 1B) mice. Thus we could argue that the increased mortality in control groups was dependent on microbiome while it was masked in super susceptible WD/KD groups. This needs to be carefully addressed.

This reviewer brings up a very important point. We have addressed these issues thoroughly and specifically in our previous publication: Napier, et al. Western diet regulates immune status and the response to LPS-driven sepsis independent of diet-associated microbiome. PNAS. 2019 (Figure 4A-D). However, we were not clear enough in our text and will change: “Diets enriched in SFAs drive enhanced responses to systemic LPS independent of microbiome” to à “Diets enriched in SFAs drive enhanced responses to systemic LPS independent of diet-associated microbiome”, where appropriate.

3. Cellular sources: In Figure 1, the authors assess the expression of several pro-inflammatory genes as well as an anti-inflammatory gene in blood, which composed of 90% lymphocytes and only 5-10% myeloid cells. Thus it is not clear to this reviewer that how the increased expression of these genes are linked to trained innate immunity. Similarly, in Figure 2, the authors showed that the expression of TNF was increased in splenocytes (>80% lymphocytes) of KD mice after ex-vivo stimulation with LPS. So, without knowing the cellular sources of these cytokines, it is challenging to directly link the expression of inflammatory genes to innate cells. Furthermore, the authors need to provide the level of circulating cytokine by simply using ELISA. Considering the overlapping error bars in evaluating of many gene expressions statistical analysis needs to be double checked.

We agree with the reviewer, typically only 4 and 10% of leukocytes in the blood, in mice and humans respectively, are considered myeloid cells. Additionally, within the first 24 hours after systemic LPS exposure in humans (in vivo) the % of classical monocytes (expressing inflammatory cytokines TNF and IL-1b; CD14hiCD16-) increases in the blood, and to a lesser degree nonclassical monocytes (expressing TNF, IL-1b, IL-6, and IL-8; CD14dimCD16hi) increase in the blood (15). These systemic pools of monocytes are then recruited to peripheral tissues whereby they differentiate into tissue resident macrophages and DCs [Reviewed here Ginhoux, 2014, Nature Reviews Immunology].

In mice, after exposure to systemic LPS, inflammatory bone marrow monocytes (CD11b+Ly6Chi – mouse Ly6Chi monocytes are equivalent to human CD14hi monocytes), lung monocytes, and splenic monocytes [Reviewed here: Teh et al., Frontiers in Immunology, 2019] are recruited to peripheral tissues through the blood. These blood monocyte populations are typically transient, and decrease after inflammation resolves.

Further, we have specifically seen that 10h post-LPS inject, inflammatory monocytes (CD11b+CD115+) are increased within the blood in SC mice (7). Other labs have shown, inflammatory (CD11b+CD115+Ly6hi) monocytes are recruited to peripheral tissues, like the liver, 24h post-LPS treatment [Reviewed here Ginhoux, 2014, Nature Reviews Immunology]. This suggests there is a transitory period that inflammatory monocytes producing cytokines are traveling within the blood, and may be responsible for this acute increase in cytokine expression 5-20h after LPS induction (Figure 1).

This topic is of immense interest to our lab, and we are currently working to identify the leukocytes responsible for increased expression of inflammatory cytokines within the blood during endotoxemia between diets.

To address the last comments, we assessed cytokine secretion within the mice during LPS through 10uL tail vein bleeding – allowing us to track the progression of disease and expression of cytokines throughout disease within each mouse. This volume of blood does not allow for ELISA analysis and would require sacrificing mice. Lastly, we have provided all statistical analysis of our cytokine expression data within the reference source data.

4. Hematopoietic stem cells: In Figure 2, the authors showed that monocytes isolated from BM of KD-mice expressed higher levels of TNF and IL6 following ex-vivo LPS stimulation. These data indicate that the potential impact of SFAs is on HSCs and progenitor cells. I would highly recommend the authors to consdier two experiments to provide more direct link between SFAs and trained immunity. First, to assess the impact of SFAs or PA on HSCs and myeloid progenitor cells by FACS as it has been done in the BCG model (Kaufmann et al., 2018). Second, to generate BMDM from SFAs and SC mice and then stimulate them with LPS or infect them with C. albicans, ex-vivo. As the generation of BMDM will take 5-7 days, any initial imprinting by SFAs can be transmitted from the progenitor cells to macrophages. Thus if there is an alteration in HSCs and progenitor cells, this can provide mor evidence of central training and its long-term effects on immunity to sterilized immunity (LPS) or infections (e.g. C. albicans). This will also provide more support for Figure 5H-I.

We want to thank the reviewer for these suggestions, and we believe that these suggested experiments have bolstered our results significantly. As the reviewer suggested, we have used a modified version of the Kaufmann et al. 2018 FACs panel (Figure 1) to identify the proportions of long-term HSCs, short-term HSCs, and multipotent progenitors after 2 weeks of diet exposure (SC, WD, and KD). Further, we quantified MPP3s, though we had too low MPP4s to conclude results. We suggest the identity of MPP4s may be different in BALB/c mice (used here) compared to C57BL/6 mice (used by Kaufmann et al). Figure 2 now shows the analysis of LT-HSCs, ST-HSCs, and MPPs sub-types from the bone marrow of SC-, WD-, and KD-fed mice.

Supplemental Figure 2A shows quantified MPP3 data and Figure S3 shows our gating schemes.

Additionally, we isolated BMDMs from mice fed SC, WD, and KD for 2 weeks, expand and differentiate these cells 7 days and then stimulated with LPS to analyze cytokine release. We now have found BMDMs from KD-fed mice treated ex vivo with LPS after 7 days of macrophage differentiation shows enhanced cytokine production compared to SC- and WD-fed mice (Figure 2D-E), highlighting the intriguing biology behind KD-dependent trained immunity. We have since concluded KD is inducing a trained immunity response and have added this to the title and within the analysis.

References for revision:

1. M. Perreault et al., A distinct fatty acid profile underlies the reduced inflammatory state of metabolically healthy obese individuals. PLoS One 9, e88539 (2014).

2. S. A. Abdelmagid et al., Comprehensive Profiling of Plasma Fatty Acid Concentrations in Young Healthy Canadian Adults. PLoS One, (2015).

3. D. D. Black, Development and Physiological Regulation of Intestinal Lipid Absorption. I. Development of intestinal lipid absorption: cellular events in chylomicron assembly and secretion. Am J Physiol Gastrointest Liver Physiol 293, (2007).

4. C. M. Mansbach II, F. Gorelick, Development and physiological regulation of intestinal lipid absorption. II. Dietary lipid absorption, complex lipid synthesis, and the intracellular packaging and secretion of chylomicrons. Am J Physiol Gastrointest Liver Physiol 293, (2007).

5. M. H. Karavolos et al., Adrenaline modulates the global transcriptional profile of Salmonella revealing a role in the antimicrobial peptide and oxidative stress resistance responses. BMC Genomics 9, 458 (2008).

6. B. A. Napier et al., Complement pathway amplifies caspase-11-dependent cell death and endotoxininduced sepsis severity. J Exp Med, (2016).

7. B. A. Napier et al., Western diet regulates immune status and the response to LPS-driven sepsis independent of diet-associated microbiome. Proc Natl Acad Sci U S A 116, 3688-3694 (2019).

8. F. B. SCHWEINBURG, H. A. FRANK, J. FINE, Bacterial factor in experimental hemorrhagic shock; evidence for development of a bacterial factor which accounts for irreversibility to transfusion and for the loss of the normal capacity to destroy bacteria. Am J Physiol 179, 532-540 (1954).

9. S. JACOB et al., Bacterial action in development of irreversibility to transfusion in hemorrhagic shock in the dog. Am J Physiol 179, 523-531 (1954).

10. C. T. Fagundes, D. G. Souza, J. R. Nicoli, M. M. Teixeira, Control of host inflammatory responsiveness by indigenous microbiota reveals an adaptive component of the innate immune system. Microbes Infect 13, 1121-1132 (2011).

11. C. T. Fagundes, F. A. Amaral, A. L. Teixeira, D. G. Souza, M. M. Teixeira, Adapting to environmental stresses: the role of the microbiota in controlling innate immunity and behavioral responses. Immunol Rev 245, 250-264 (2012).

12. D. G. Souza et al., The essential role of the intestinal microbiota in facilitating acute inflammatory responses. J Immunol 173, 4137-4146 (2004).

13. S. L. Foster, D. C. Hargreaves, R. Medzhitov, Gene-specific control of inflammation by TLR-induced chromatin modifications. Nature 447, 972-978 (2007).

14. M. Divangahi et al., Trained immunity, tolerance, priming and differentiation: distinct immunological processes. Nat Immunol 22, 2-6 (2021).

15. Y. V. Radzyukevich, N. I. Kosyakova, I. R. Prokhorenko, Participation of Monocyte Subpopulations in Progression of Experimental Endotoxemia (EE) and Systemic Inflammation. Journal of Immunology Research 2021, 1-9 (2021).

[Editors’ note: what follows is the authors’ response to the second round of review.]

The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined below:

The authors have wonderfully addressed the comments, and have resubmitted a very strong and thorough study on the role of dietary fatty acids on the induction of in vivo trained immunity. The manuscript is nearly ready for publication, especially considering the novelty and strength of their findings, not to mention the relevance to the field of trained immunity as well as metainflammation. There are however a few final comments on the present manuscript.

The first thing is the so-called 'obesity paradox'. People overweight or with obesity are generally protected from deadly/lethal septicemia when compared to normal or underweight individuals. Two weeks of high-fat feeding may not be sufficient to induce obesity, however, it would be interesting to know if the mice have gained weight. It would be of interest to briefly discuss the clinical conundrum of the 'obesity paradox', especially given the highly lethal phenotype of WD and KD-fed mice in for example Figure 1B.

The reviewer brings up an important point. We have previously addressed this paradox question in our model of endotoxemia and diet-induced weight gain in Napier, et al. 2019, PNAS. However, it’s important for the reader to understand the context and application of our studies, thus we have added a paragraph to the Discussion that explores this idea in the context of our findings (Lines 452-463).

With sepsis, the general course of the disease is indeed hyper-inflammation leading to organ failure and death, or immune paralysis and increased risk of mortality via secondary infection. Given that your data suggest that the mice indeed enter into the immune-paralyzed state, do you have any data to show whether the mice died from organ failure or secondary infections? Regardless of the phenotype, WD or KD-fed mice are more susceptible to lethal responses to LPS. Germ-free mice similarly show lethality making the effect clearer to being the result of organ failure/damage. Though, the cytokines, especially IL-10 make this distinction even murkier. The germ-free clearly look as though they are dying from hyper-inflammation, while the BALB/c mice are seemingly dying in the immune-paralyzed state; given they aren't germ-free and are susceptible to secondary infection with commensals. How would the authors rationalize this?

We agree with the reviewer, it is important to discuss the implications of immunoparalysis driving mortality in the endotoxemia model in the context of our findings. Previous seminal studies concluded that mice treated with antibodies to the TNF receptor and challenged with systemic LPS increased survival from 0% to nearly 100%, suggesting that acute inflammation driven by TNF is responsible for endotoxemia-related survival (1, 2). Further, it has been shown that TNF is required for acute renal failure (3), lung injury (4), and liver damage (5) during LPS challenge. In agreeance with conventional mouse data, it has also been shown that acute inflammation, specifically TNF production, is a driver of endotoxemia in germ-free (GF) mice (6). These data suggest that acute inflammation, specifically the bioactivity of TNF, drives endotoxemia mortality and organ damage in conventional and GF mice. Thus, although our conventional mice show signs of immunoparalysis, we believe that the acute (515h) enhanced Tnf in the blood of both conventional and GF mice is responsible for endotoxemia mortality and subsequent organ failure, as seen in previous publications. Considering this, we agree that this is important to mention in the context of our results, thus we have added a section in the Discussion that mentions these previously published data (Lines 501-510).

Sepsis is a medical term that describes an infection of the blood. In your model, LPS is used to induce systemic inflammation. Although many of the symptoms and effects overlap profoundly with those seen in sepsis, we advise against using the term sepsis to describe your model since no infection is established. Endotoxin challenge, or endotoxin stimulation, is more appropriate/accurate semantics.

We agree with the reviewer and though we define our disease model as “LPS-induced acute septic shock”, it is important that the readers understand that we are using the traditional “endotoxemia” model. We have changed all references to this disease model to “endotoxemia”.

Page 17 lines 461 – 463 reading: "Our findings align with the growing body of evidence indicating that trained immunity is a double-edged sword, where the phenomenon can be beneficial for resistance to infection, but detrimental in the context of inflammatory disease." This reads a bit off given that, in fact, your model uses a bacterial-derived stimulus to induce a lethal inflammatory response in WD and KD-'trained' mice. You could hardly call this a beneficial effect of trained immunity.

We agree with the reviewer that this statement as-is is confusing, thus we have changed the wording: “Our findings align with the growing body of evidence indicating that trained immunity is a double-edged sword, where the phenomenon can be beneficial for resistance to infection, but detrimental in the context of diseases exacerbated by systemic inflammation” (Lines 71-73; 472-476), and include a detailed explanation of our statement in the Discussion (Lines 472-476).

A technical hurdle for figure 3 is that the mice are on a ketogenic diet, cells are harvested, and then brought into culture with glucose-enriched media. We wonder then how the sudden overabundance of glucose might contribute to the elevated cytokine responsiveness seen in the data presented in these figure panels, as opposed to the ketogenic diet per se giving rise to increased immune responsiveness. It is worth saying that the in-vivo cytokine responses are much milder than what's seen ex vivo.

The reviewer brings up an interesting and important point. It has been shown that TNF, IL-6, or IL-1b secretion is enhanced in WT BMDMs treated for a short period (48 h) with high-glucose media (7). However, high-glucose media does not alter TNF, IL-6, or IL-1b secretion, or mitochondrial activity, in WT BMDMs treated with LPS following 7 d of differentiation in high glucose media (7). Thus, since metabolic adaptation takes place within a few days for BMDMs cultured in high glucose media and does not alter inflammatory cytokine secretion following LPS challenge after 7d in high glucose media, we suggest it is unlikely that high glucose media after 7 d contributed to the significant augmentation of LPS-induced TNF and IL-6 secretion for BMDMs from KD-fed mice compared to controls (7). Further, the speed of metabolic shifts (or metabolic flexibility) from glycolysis to ketosis (and reversed) are often similar in lean adults (regardless of fat-intake), suggesting that both SC- and KD-fed mice will have similar metabolic flexibility in response to 7 d of high-glucose (8, 9). We have not analyzed the exact metabolic flexibility of the mitochondria within SC- or KD-derived BMDMs, but this is an intense area of interest for our lab and we are currently researching this topic.

Lastly, while LPS-challenged macrophages preferentially utilize glucose as their main energy source in order to upregulate expression and release of pro-inflammatory cytokines, there are several variables that may contribute to the mismatch between cytokine mRNA expression in the blood and expression or secretion of cytokines by differentiated immune cells in response to LPS (10). Specifically, monocytes (the major producer of systemic cytokines during LPS challenge) are only approximately 4% of the leukocytes in the blood in mice. Thus, we are seeing a diluted response, whereas in vitro we would be directly assessing monocyte (only) responses.

We agree this is an important point to mention within the manuscript and have since added a section in the Discussion covering this topic (Lines 441-451).

References

1. B. Beutler, I. W. Milsark, A. C. Cerami, Passive immunization against cachectin/tumor necrosis factor protects mice from lethal effect of endotoxin. Science 229, 869-871 (1985).

2. K. M. Mohler et al., Soluble tumor necrosis factor (TNF) receptors are effective therapeutic agents in lethal endotoxemia and function simultaneously as both TNF carriers and TNF antagonists. J Immunol 151, 1548-1561 (1993).

3. P. N. Cunningham et al., Acute renal failure in endotoxemia is caused by TNF acting directly on TNF receptor-1 in kidney. J Immunol 168, 5817-5823 (2002).

4. Y. Chen et al., Aerosol synthesis of cargo-filled graphene nanosacks. Nano Lett 12, 1996-2002 (2012).

5. W. Zhong et al., Curcumin alleviates lipopolysaccharide induced sepsis and liver failure by suppression of oxidative stress-related inflammation via PI3K/AKT and NF-κB related signaling. Biomed Pharmacother 83, 302-313 (2016).

6. D. G. Souza et al., The essential role of the intestinal microbiota in facilitating acute inflammatory responses. J Immunol 173, 4137-4146 (2004).

7. T. S. Ayala et al., High glucose environments interfere with bone marrow-derived macrophage inflammatory mediator release, the TLR4 pathway and glucose metabolism. Scientific Reports, (2019).

8. D. E. Kelley, B. Goodpaster, R. R. Wing, J. A. Simoneau, Skeletal muscle fatty acid metabolism in association with insulin resistance, obesity, and weight loss. Am J Physiol 277, E1130-1141 (1999).

9. R. L. Smith, M. R. Soeters, R. C. I. Wüst, R. H. Houtkooper, Metabolic Flexibility as an Adaptation to Energy Resources and Requirements in Health and Disease. Endocr Rev 39, 489-517 (2018).

10. A. J. Freemerman, L. Makowski, Metabolic reprogramming of macrophages

Glucose transporter 1 (GLUT1)-mediated glucose metabolism drives a proinflammatory phenotype. The Journal of Biological Chemistry 289, 7884-7896 (2014).

Associated Data

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    Supplementary Materials

    Figure 1—source data 1. Data and statistics for graphs depicted in Figure 1A–N.
    elife-76744-fig1-data1.xlsx (957.8KB, xlsx)
    Figure 1—figure supplement 1—source data 1. Data for graphs depicted in Figure 1—figure supplement 1A-H.
    Figure 2—source data 1. Data and statistics for graphs depicted in Figure 2A–E.
    Figure 2—figure supplement 1—source data 1. Data for graphs depicted in Figure 2—figure supplement 1.
    Figure 3—source code 1.
    Figure 3—source data 1. Data and statistics for graphs depicted in Figure 3A–M.
    Figure 3—figure supplement 1—source data 1.
    Figure 3—figure supplement 1—source code 1.
    Figure 3—figure supplement 2—source data 1. Data for graphs depicted in Figure 3—figure supplement 2A-D.
    Figure 3—figure supplement 3—source data 1. Data for graphs depicted in Figure 3—figure supplement 3A, B.
    Figure 4—source data 1. Data and statistics for graphs depicted in Figure 4A–I.
    elife-76744-fig4-data1.xlsx (684.8KB, xlsx)
    Figure 4—figure supplement 1—source data 1. Data for graphs depicted in Figure 4—figure supplement 1A-D.
    Figure 5—source data 1. Data and statistics for graphs depicted in Figure 5A–E.
    Supplementary file 1. Diet compositions (values represent percentage of total kcal).
    elife-76744-supp1.docx (18.5KB, docx)
    Supplementary file 2. List of primers used in this study.
    elife-76744-supp2.docx (13.5KB, docx)
    Transparent reporting form

    Data Availability Statement

    All data generated or analyzed during this study are included in the manuscript and supporting file.


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