Physiology and Metabolism
Research Article
4 August 2022

Chronic Leptin Deficiency Improves Tolerance of Physiological Damage and Host-Pathogen Cooperation during Yersinia pseudotuberculosis Infection

ABSTRACT

To combat infections, hosts employ a combination of antagonistic and cooperative defense strategies. The former refers to pathogen killing mediated by resistance mechanisms, while the latter refers to physiological defense mechanisms that promote host health during infection independent of pathogen killing, leading to an apparent cooperation between the host and the pathogen. Previous work has shown that Leptin, a pleiotropic hormone that plays a central role in regulating appetite and energy metabolism, is indispensable for resistance mechanisms, while a role for Leptin signaling in cooperative host-pathogen interactions remains unknown. Using a mouse model of Yersinia pseudotuberculosis (Yptb) infection, an emerging pathogen that causes fever, diarrhea, and mesenteric lymphadenitis in humans, we found that the physiological effects of chronic Leptin-signaling deficiency conferred protection from Yptb infection due to increased host-pathogen cooperation rather than greater resistance defenses. The protection against Yptb infection was independent of differences in food consumption, lipolysis, or fat mass. Instead, we found that the chronic absence of Leptin signaling protects from a shift to lipid utilization during infection that contributes to Yptb lethality. Furthermore, we found that the survival advantage conferred by Leptin deficiency was associated with increased liver and kidney damage. Our work reveals an additional level of complexity for the role of Leptin in infection defense and demonstrates that in some contexts, in addition to tolerating the pathogen, tolerating organ damage is more beneficial for survival than preventing the damage.

INTRODUCTION

Leptin is an adipose tissue hormone that acts via its receptor (LEP-R) in the brain to regulate energy balance and neuroendocrine function (1). Circulating Leptin levels communicate the state of body energy repletion to the central nervous system in order to suppress food intake and promote energy expenditure (1, 2). When Leptin is present at normal levels, it supports energy utilization on a variety of essential processes, including those that support the immune system. Conversely, Leptin deficiency results in increased appetite and altered energy expenditure—leading to obesity—as well as decreased immune function (13). Indeed, Leptin deficiency has historically been associated with increased susceptibility to a variety of infections (47).
To combat infections, hosts use a combination of evolved antagonistic and cooperative defense strategies (810). The former refers to pathogen killing mediated by resistance mechanisms, while the latter refers to physiological defense mechanisms that foster host health during infection independent of pathogen killing, leading to an apparent cooperation between the host and pathogen (8, 11). The traditional view of Leptin’s role in infection defense is that Leptin is required to mediate resistance mechanisms and pathogen killing. For example, phagocytosis, an intricate immune process through which cells ingest and eliminate pathogens, is severely impaired in the absence of Leptin (7, 12, 13). In a mouse model of Streptococcus pneumoniae infection, Leptin-deficient mice exhibited defective alveolar macrophage phagocytosis. This was associated with reduced bacterial clearance in the lungs and increased lethality. Administration of exogenous Leptin to Leptin-deficient mice during the infection improved phagocytosis, bacterial clearance, and animal survival (4). Leptin also modulates the function of several other innate immune cells, thus influencing innate immunity against pathogens. For instance, Leptin promotes chemotaxis and the release of pathogen-killing reactive oxygen species in neutrophils (14, 15). Similarly, it supports the development and activation of natural killer cells (16). Additionally, Leptin exerts a variety of effects on the adaptive immune system, such as increasing the expression of adhesion molecules by CD4+ T cells and promoting a bias toward TH1-cell responses in memory CD4+ T cells (17).
Acute and chronic Leptin deficiency will influence susceptibility to infections through largely distinct mechanisms. For example, while Leptin signaling is required for immune cell phagocytosis during infection (13), congenital Leptin deficiency causes severe obesity, an established risk factor for infections and poor responses to vaccinations (18). Obesity-related susceptibility to infectious diseases is caused in part by an impairment of immune responses (resistance mechanisms). For instance, studies have found decreased populations of bone marrow-resident B cells, which are responsible for antibody production, in uninfected mice with diet-induced obesity (19). This result is further supported by the observation that influenza-specific antibodies are absent in obese mice at 35 days postinfection (20). Additionally, obesity may also compromise cooperative defenses. Obesity has been shown to impair wound healing (a disease tolerance mechanism) through vascular and nutritional deficiencies as well as aberrant inflammatory responses (21). Chronic Leptin deficiency has a wide range of physiological effects beyond obesity, including endocrine abnormalities and changes in glucose and lipid metabolism (22). It is likely that these physiological changes have a complex effect on host defense. While Leptin has been shown to play a key role in the promotion of resistance mechanisms, and therefore antagonistic defenses, the role of Leptin in cooperative defense strategies remains unexplored.
Cooperative defense mechanisms include disease tolerance mechanisms, which act to prevent/alleviate physiological damage during infection and enable the host to endure such damage should it occur, and anti-virulence mechanisms, which dampen microbial and host-derived virulent signals and behaviors that contribute to disease pathogenesis (811, 23, 24). A general theme that has emerged from recent studies is that physiological defense mechanisms largely involve metabolic processes induced during infection (2529). For example, infection-induced tissue iron sequestration and insulin resistance promoted host-pathogen cooperation in an enteric pathogen model (27). Other studies have found that sickness-induced anorexia can either promote or hinder cooperative defenses during infection (26, 29, 30). In another study, a microbiota-derived Escherichia coli strain promoted disease tolerance during enteric and pulmonary infections by protecting mice from infection-induced wasting (28). Given the metabolic nature of the physiological defense mechanisms identified thus far and the role that Leptin plays in the maintenance of systemic metabolic homeostasis, we reasoned that Leptin may play a major role in regulating physiological defenses and host-pathogen cooperation.
While disease tolerance and anti-virulence defenses are evolved mechanisms to promote physiological defenses and host-pathogen cooperation, a loss of antagonistic defenses can also yield an apparent cooperation and protection from damage during infection. This occurs when the cost of mounting the resistance response is greater than the benefit of killing the pathogen (8). Such costs come in the form of immunopathology that occurs as a consequence to the resistance response. Typically, the loss of such responses will provide protection from tissue/organ/physiological damage and cooperation, leading to a survival advantage despite elevated levels of the pathogen. We have less of an appreciation of the inherent costs to mounting physiological defense responses and whether there are contexts for which enduring tissue/organ/physiological damage is more beneficial than the costs of mounting a disease tolerance or anti-virulence response.
Yersinia pseudotuberculosis (Yptb) is a Gram-negative, extracellular bacterium that is pathogenic to humans and mice (31, 32). Yptb is transmitted via the fecal-oral route. Upon oral infection, Yersinia traverses the M cells of the intestine. Once across, it infects the underlying lymphoid tissues (Peyer’s patches [PP] and mesenteric lymph nodes). Infection typically causes self-limiting gastroenteritis and mesenteric lymphadenitis. In mice, and occasionally in humans, Yptb spreads to the liver and spleen and causes systemic disease leading to sepsis (3133). The ability of Yptb to multiply in lymphoid tissues and spread to systemic organs depends on the presence of pYV, a virulence plasmid that encodes a type III secretion system (T3SS) and several effector proteins called Yersinia outer proteins (Yops). The Yops function to inhibit phagocytosis, downregulate proinflammatory cytokines, and induce apoptosis in target cells, among other functions (3437). Given that Yersinia infection is known to increase transcription of the Leptin receptor gene (Lepr) in mice and that several studies have established a strong link between Yersinia virulence and core metabolism (38, 39), Yptb is an excellent pathogen to elucidate the relationship between leptin, metabolism, and cooperative defenses.
Here, we describe how the effects of chronic Leptin-signaling deficiency regulates physiological defenses and host-pathogen cooperation. In agreement with previous reports (4, 5), we found that Lepob and Leprdb mice that are deficient for Leptin signaling had impaired resistance defenses against Yptb and reduced inflammation. Unexpectedly, however, we found that despite the increased pathogen burdens, Leptin deficiency conferred a survival advantage compared to wild-type (WT) animals. Leptin administration during the acute phase of the infection did not abolish the survival advantage indicating that the physiological effects of chronic Leptin deficiency regulate host-pathogen cooperation. Indeed, our findings show that the resulting changes in lipid metabolism in Leptin-deficient mice protect against Yptb infection. Furthermore, we found that the survival advantage was associated with increased liver and kidney damage and dysfunction. Our work reveals an additional level of complexity for the role of Leptin in infection defense and suggests that in some contexts, in addition to cooperating with the pathogen, tolerating organ damage and dysfunction is more beneficial for survival than preventing the damage.

RESULTS

Chronic Leptin deficiency promotes health and survival of Yptb infection.

We began by characterizing the clinical course of disease for Yptb infection in C57BL/6 mice to understand how this infection influences metabolic health of the host. Oral infection with this enteropathogen resulted in 100% mortality by 6 days postinfection, with a median time to death (MTD) of 4 days (Fig. 1A). This mortality was associated with substantial weight loss and infection-induced anorexia. By 72 h postinfection, Yptb-infected mice lost ~10% of their body weight (Fig. 1B). The reduction in weight may partly be explained by the presence of infection-induced anorexia in these mice. Anorexia is a sickness behavior commonly induced by infection. It is characterized by a reduced motivation to consume food and triggers a fasted-like state in the host (40). Over the first 72 h postinfection, Yptb-infected mice progressively lowered their food intake, with day 3 consumption equaling, on average, 25% of their daily food intake under uninfected conditions (Fig. 1C). In sum, our results indicate that oral infection with Yptb in WT mice leads to metabolic pathologies in the host, including anorexia and rapid weight loss followed by death.
FIG 1
FIG 1 Loss of Leptin signaling promotes health and survival during Yptb infection. (A) Survival of WT mice infected with Yptb. n = 4 mice. (B) Weight loss of WT mice following Yptb infection. n = 10 mice, at day 0 and 1, n = 9 at day 2, and n = 8 at day 3 due to death from infection. Asterisks indicate significance at day 3 compared with day 0 and a P value of 0.0007. (C) Food intake of WT mice infected with Yptb. n = 10 mice per group. Significance noted indicates time point compared with 0 to 24 h. *, P = 0.0262; ***, P = 0.0001. Kuskal-Wallis test. (D) ELISA measurements of serum Leptin in WT mice. n = 7 to 10 mice per group. **, P = 0.0016 compared with day 0. One-way ANOVA. (E) Percent weight loss of WT, Lepob, and Leprdb mice after Yptb infection. n = 9 to 10 mice per group. ****, P < 0.0001, two-way ANOVA. (F) Survival of WT, Lepob, and Leprdb mice following Yptb infection. n = 9 to 10 mice per group. Log-rank test. (G) Percent weight loss of weight-matched WT, Lepob, and Leprdb mice following Yptb infection. n = 9 to 10 mice/condition. Two experiments combined. ****, P < 0.0001, two-way ANOVA. (H) Survival of weight-matched WT, Lepob, and Leprdb mice following Yptb infection. Log-rank test. Two experiments combined. Error bars represent +/− SEM.
Leptin is an appetite-suppressant hormone whose levels are known to increase systemically in animal models of lipopolysaccharide (LPS)-induced anorexia (41, 42). To begin to understand the relationship between Leptin and the presence of infection-induced anorexia in our Yptb infection model, we quantified serum Leptin in Yptb-infected mice. Surprisingly, we found that circulating levels of Leptin declined over the course Yptb infection in C57BL/6 mice. The decline was apparent as early as 24 h postinfection and continued to decline through 72 h postinfection (Fig. 1D). These data indicate that in the context of Yptb infection, the infection-induced anorexic response is associated with a decline, rather than an increase, in circulating leptin. The discrepancy between our results and previous work using LPS (41, 42) may be explained by the fact that LPS administration does not fully reflect the complexity of infection with a live pathogen.
We next set out to determine whether the absence of Leptin signaling changes the outcome of Yptb infection. When we infected Leptin-deficient (Lepob) and Leptin receptor-deficient (Leprdb) mice with Yptb, we found that compared with WT infected mice, these mutant mice were protected against the weight loss induced by Yptb infection. While infected WT mice lost greater than 10% of their body weight by 72 h postinfection, infected Lepob and Leprdb mice maintained their body weight at this same time point (Fig. 1E; Fig. S1A). In addition to a protection from infection-induced wasting, we found that mice deficient for Leptin signaling had a significant survival advantage compared with infected WT mice. The MTD for WT mice was 3 days while the MTD for Lepob and Lepdb mice was 6 days (Fig. 1F). Lepob and Leprdb mice develop obesity due to hyperphagia that is sustained by a defective Leptin circuitry (43). Indeed, the weights at the time of infection of Lepob and Leprdb mice were significantly higher than WT mice (Fig. S1B). To determine if the differences in susceptibility were due to differences in body weight at the time of infection, we compared Yptb susceptibility of WT mice that were fed high fat diet (HFD) with Lepob and Leprdb mice. WT mice fed HFD had comparable weights as Lepob and Leprdb mice at the time of infection (Fig. S1C). We found that weight-matched WT mice were highly susceptible to both Yptb-induced wasting and mortality compared with Lepob and Leprdb mice (Fig. 1G and H; Fig. S1D). Altogether, our data demonstrate that Leptin-signaling deficiency protects from wasting and death during Yptb infection and that the differences in susceptibility cannot be explained by differences in body size.
One hypothesis to explain why Leptin-signaling deficiency may be protective during Yptb infection is that Leptin signaling during the acute infection may contribute to disease pathogenesis. As Leptin-signaling-deficient animals also have profound metabolic and physiological abnormalities due to chronic hyperphagia and sustained defective Leptin circuitry, a second hypothesis is that the baseline metabolic and physiological differences between WT and Leptin-signaling-deficient animals are responsible for the differences in Yptb susceptibility. To distinguish between these two hypotheses, we infected Lepob and Leprdb mice with Yptb and asked how acute Leptin administration during the infection influences susceptibility. As expected, Leptin administration had no effect on food consumption or survival in Leprdb mice that lack the Leptin receptor (Fig. S1E and F). In Lepob mice, Leptin administration during the infection was sufficient to reduce food consumption; however, it had no effect on survival (Fig. S1G and H). Taken together, chronic deficiency in Leptin signaling results in a physiological state that protects from Yptb infection.

Increased feeding does not promote survival of Yptb infection.

Infection-induced anorexia is associated with distinctive changes in the expression of feeding and neuronal activation genes—termed the anorexic program—in the hypothalamus, a region of the brain that plays a central role in the regulation of food intake and energy balance (26). To confirm that the reduced food consumption exhibited by Yptb-infected WT mice was in fact due to anorexia, we determined whether Yptb infection induces the molecular anorexic program in mice. We quantified the mRNA expression of the feeding-associated genes Lepr, Npy, Fos, Socs3, Pomc, and Agrp in the hypothalamus using qRT-PCR. Compared with uninfected controls, we found that the mRNA expression of Agrp, Socs3, Fos, and LepR significantly increased, while the mRNA expression of Npy and Pomc significantly decreased in Yptb-infected mice (Fig. 2A). In accordance with previously published results (26, 44, 45), these hypothalamic transcriptional changes are in line with the presence of anorexia, indicating that Yptb-infected mice not only display anorexic feeding behavior but also possess molecular markers characteristic of anorexia.
FIG 2
FIG 2 Increased feeding does not improve survival of Yptb infection. (A) Quantification of feeding-associated genes Lepr, Npy, Fos, Socs3, Pomc, and Agrp in the hypothalamus of Yptb-infected WT mice using qRT-PCR. n = 6 to 10 mice per group. *, P < 0.05; **, P < 0.01; ***, P < 0.0005; ****, P < 0.0001 versus uninfected in a one-way ANOVA or Kruskal-Wallis test. (B) Average daily food intake of WT, Lepob, and Leprdb when uninfected. n = 29 to 30 mice per group. ****, P < 0.0001 versus uninfected in a Kruskal-Wallis test. Data are three independent experiments combined. (C) Total food consumption per mouse over the first 3 days of infection. Data for WT, Lepob, and Leprdb are shown. n = 18 to 20 mice per group. ****, P < 0.0001 versus uninfected in a one-way ANOVA test. Three independent experiments combined. (D) Survival of infected WT, Lepob, and Leprdb mice under ad libitum and food-restricted conditions. n = 10 mice per group. Log rank analysis. The curves showing presented data with mutant ad libitum conditions are in Fig. S2A. Error bars represent +/−SEM.
We previously demonstrated that infection with the enteropathogen Salmonella enterica serovar Typhimurium induces the anorexic program in the hypothalamus in mice resulting in sickness-induced anorexic behavior and reduced food consumption. We demonstrated that this behavioral response triggered increased pathogen virulence during S. Typhimurium infection (26). Considering that Yptb infection also induces an anorexic signature and resulting anorexic response in mice (Fig. 1C) and that Lepob and Leprdb mice exhibit hyperphagic behavior when uninfected (43) and (Fig. 2B), we hypothesized Lepob and Leprdb consumed more food than WT mice during a Yptb infection. Consistent with our hypothesis, we found that Lepob and Leprdb mice consumed twice the amount of food (~20 g versus ~10 g) as WT mice over the first 3 days of the infection (Fig. 2C). Taken together, these results indicate that the characteristic hyperphagia of Lepob and Leprdb mice is extended to infected conditions.
While administration of Leptin to Lepob mice was sufficient to reduce food consumption during a Yptb infection (Fig. S1G), it was not sufficient to alter susceptibility of infection (Fig. S1H). To confirm that the hyperphagic behavior of Leptin-signaling-deficient mice during Yptb infection was not responsible for the protection against the infection, we performed pairwise feeding experiments where we infected WT, Lepob, and Leprdb mice with Yptb and restricted the diet of Lepob, and Leprdb each day postinfection so that they were allowed to consume comparable amounts of food as WT mice each day postinfection. While food-restricted Lepob and Leprdb mice displayed increased survival of infection compared with ad libitum WT mice, we did not observe any differences in survival between ad libitum and food-restricted Lepob and Leprdb mice (Fig. 2D; Fig. S2A). In sum, our data suggest that while Lepob and Leprdb mice are hyperphagic during infection, their increased feeding does not account for the survival advantage of these mice when infected with Yptb.
To further corroborate that increased feeding does not lead to increased survival in the context of Yptb infection, we employed two alternate models. The cytokine IL-1β is a key mediator of feeding under homeostatic conditions (Fig. S2B) and infection-induced anorexia (46). We infected WT and Il1β−/− knockout (KO) mice with Yptb and measured food consumption during infection. Infected Il1β−/− KO mice exhibited a significantly higher food intake compared with infected WT mice (Fig. S2C). These results indicate that IL-1β contributes to the anorexic response induced by Yptb infection. Next, we compared survival of infection between WT and Il1β−/− KO mice. We found that there is no survival difference between infected WT and Il1β−/− KO mice (Fig. S2D). Thus, our second model (Il1β−/− KO mice) confirmed that increased feeding does not promote survival during Yptb infection. As a third and last approach, we hypothesized that if increased feeding serves to protect mice against Yptb infection, then food-restricting WT mice during infection will lower their survival. To test this hypothesis, we compared survival of infection between ad libitum and food-restricted WT mice. Our data showed no difference in survival between these two groups of mice (Fig. S2E). In sum, using three distinct approaches, we demonstrated that food consumption does not change the final outcome of Yptb infection and that the protection mediated by Leptin-signaling deficiency is not due to the hyperphagic behavior of these mice during a Yptb infection. This is consistent with our Leptin administration experiments demonstrating that the underlying physiological state rather than differences in Leptin signaling during the acute infection cause the differences in susceptibility of Yptb infection.

Microbial community richness maintained in Lepob and Leprdb mice post-Yptb infection.

The microbiome plays a key role in host health and its responses to infectious diseases (47). We hypothesized that differences in the microbiome between WT and Leptin-signaling-deficient animals may contribute to differences in susceptibility to Yptb infection. We processed cecum samples for amplicon 16S rRNA gene sequencing in an effort to assess the microbiota profile of uninfected and infected WT, Lepob, and Leprdp mice at 72 h postinfection. We observed a significant decrease in microbial community richness, as measured by Faith’s Phylogenetic Diversity, in infected WT mice compared with uninfected WT mice (Fig. 3A; Fig. S3A and B). Furthermore, this decrease in microbial richness was associated with a significant difference in microbial community composition as measured by weighted UniFrac distances (Fig. 3B; Fig. S3C). At the phylum level, infected WT mice exhibited a reduction in Firmicutes and an expansion of Bacteroidetes (Fig. 3C; Fig. S3D). In contrast, there was no significant differences in both microbial community richness (Fig. 3A; Fig. S3A and B), nor the composition of the microbiota, between uninfected and infected Lepob mice; this observation extends to uninfected and infected Leprdp mice with regard to microbial community richness (Fig. 3A; Fig. S3A and B). Importantly, there is no significant difference in weighted UniFrac distances between infected Lepob and infected Leprdp mice, indicating that the microbial composition of these two groups is similar (Fig. 3B; Fig. S3C). Finally, a comparison of WT mice with Lepob and Leprdb mice revealed that community richness was comparable under uninfected conditions, but during infection, WT mice exhibited reduced community richness compared with both mutant strains (Fig. 3A; Fig. S3A and B). At the phylum level, while WT mice exhibited a reduction in Firmicutes and expansion of Bacteroidetes, both Lepob and Leprdb mice exhibited an expansion of Firmicutes and a reduction of Bacteroidetes during infection (Fig. 3C; Fig. S3D). To test the functional importance of the differences in microbiome, we first performed cecal transplant experiments. We colonized germfree C57BL/6 mice with the cecal content of WT, Lepob or Leprdb mice. After 2 weeks of colonization, we infected mice with Yptb. We found no difference in death kinetics in mice that received the different cecal transplants (Fig. 3D). Finally, we performed cohousing experiments, where WT mice were cohoused with Lepob and Leprdb mice to facilitate horizontal transfer of the microbiotas. We then infected mice with Yptb and found that despite cohousing, mice deficient for Leptin signaling were still protected from a Yptb infection compared with WT mice (Fig. 3E). Our results, therefore, suggest that the observed health and survival phenotype between the Leptin deficient mice is largely independent of the microbiota.
FIG 3
FIG 3 Microbial community richness maintained in Lepob and Leprdb mice post-Yptb infection. (A to C) The cecums from uninfected and infected WT, Lepob, and Leprdb at 72 h postinfection were harvested and 16S rRNA sequencing was performed. (A) Comparison of alpha diversity as measured by Faith’s Phylogenetic Diversity scores for uninfected and infected WT, Leprob, and Lepdb mice. Kruskal-Wallis. **, P = 0.009; *, P = 0.016. Data plotted showing the comparison of infected versus uninfected of the same genotype in Fig. S3A. A complete list of P-values for pairwise comparisons are provided in Fig. S3B. (B) Principal coordinate analysis plot of weighted UniFrac distances for uninfected and infected WT, Lepob and Leprdb mice. Data points are projected onto the sample space and colored by genotype and shaped by infection status. A list of P-values for pairwise PERMANOVA comparisons are provided in Fig. S3C. (C) Biodiversity plots of cecal 16S rRNA analysis. n = 5 mice/group for (A to C). (D) Germ-free WT mice were colonized with the cecal content of uninfected WT, Lepob, or Leprdb mice and then infected with Yptb. Survival was determined. n = 6 to 8 mice/group. (E) WT mice were cohoused with Lepob and Leprdb mice to facilitate horizontal exchange of microbiotas, after which mice were infected with Yptb. Survival was determined. n = 15 to 20 mice per group. Error bars indicate +/− SEM. Log rank analysis for survival curves.

Lipid utilization contributes to mortality of Yptb infected wild-type mice.

Infections cause dramatic rearrangements to the physiology of host energy stores, including wasting of adipose tissue. In an MRI time course analysis, we found that Yptb infection in WT mice caused a rapid and robust adipose tissue wasting phenotype beginning 24 h postinfection (Fig. S4A to D). By 72 h postinfection, Yptb infected WT mice lost 33.5% of total body fat and direct measurements of inguinal and gonadal white adipose tissue weights (IWAT and GWAT) revealed a >50% reduction in mass (Fig. S4A to D). Lepob and Leprdb mice exhibit a higher rate of net lipolysis under homeostatic conditions compared to WT mice (48). We hypothesized that this increased lipolysis may confer a survival advantage when animals are challenged with Yptb. To test whether lipolysis was necessary to protect against Yptb infection, we employed tissue specific knock out mice, Pnpla2 fabp4 cre, in which Pnpla2, the gene encoding adipose triglyceride lipase (ATGL), which mediates the first and rate-limiting step of lipolysis is knocked out in adipocytes (49). We reasoned that if increased lipolysis provided a survival advantage to Lepob and Leprdb mice during Yptb infection, then lipolysis-impaired mice, such as ATGL-deficient mice, would be more susceptible to the infection. Mice deficient for ATGL function in adipocytes did not exhibit adipose tissue wasting when infected with Yptb, demonstrating that adipose tissue wasting during Yptb infection is dependent on ATGL function (Fig. S4E and F). Our survival analysis showed comparable death kinetics for Yptb-infected cre– and cre+ mice, indicating that adipose tissue lipolysis is not necessary to alter the outcome of a Yptb infection (Fig. S4G).
From our clinical pathology analysis, we found that during Yptb infection, Lepob and Leprdb mice maintained their circulating triglyceride levels. In contrast, WT mice exhibited a decline in their circulating triglyceride levels when infected with Yptb (Fig. 4A; Fig. S5A). It was previously shown in a model of systemic bacterial inflammation (25) that administration of lipids was sufficient to protect from lethality. To determine if the hypotriglyceridemic state of WT mice contributed to lethality, we injected Yptb infected WT mice with Intralipid over the course of the infection. We found that lipid administration had no effect on the death kinetics of Yptb-infected WT mice, suggesting that the hypotriglyceridemia does not contribute to Yptb-induced lethality in WT mice (Fig. S5B).
FIG 4
FIG 4 Lipid utilization increases susceptibility to Yptb infection. (A) WT, Lepob, and Leprdb mice were infected with Yptb and serum levels of triglycerides + gycerol were measured from 48 to 72 h postinfection and compared with uninfected control mice. n = 8 to 25 mice per condition, three experiments combined. Kruskal-Wallis test, ****, P < 0.0001. The same data are also shown in Fig. S5A to show pairwise comparisons for uninfected versus infected for each genotype. (B and C) WT, Lepob, and Leprdb mice were infected with Yptb and a lipid tolerance test was performed at 72 h postinfection. (B) serum triglyceride levels over the course of the LTT assay and (C) area under the curve analysis for (B). n = 5 mice per condition. Two-way ANOVA or one-way ANOVA,*, P < 0.05; **, P < 0.01; ****, P < 0.0001. Uninfected condition for each genotype is shown in Fig. S5M and N. The LTT curves for the infected conditions for each genotype shown in (B-C) are also shown in Fig. S5O to T with the corresponding LTT curve for the uninfected genotype condition. (D to I) Uninfected and Yptb infected WT, Lepob, and Leprdb mice were placed in CLAMs to measure the RER. (D) WT uninfected and infected mice; (E) area under the curve analysis for (D); (F) Lebob uninfected and infected mice; (G) area under the curve analysis for (F); (H) Lebrdb uninfected and infected mice; (I) area under the curve analysis for (H), three to five mice per condition. The CLAMS data from this figure are also shown in Fig. S6 to show a comparison of uninfected conditions and infected conditions for each genotype. (J) WT mice were infected with Yptb and treated with lovastatin or vehicle and survival was monitored. n = 10 mice per group, two experiments combined. Log rank analysis for survival. Error bars +/− SEM.
Triglyceride levels are controlled by both exogenous sources (diet) and endogenous sources. As WT mice become anorexic during the infection (Fig. 2C), the decline in circulating triglycerides in part can be explained by reduced food consumption. To determine whether differences in endogenous sources also contribute to the differences in triglyceride levels, we first determined if there were changes in hepatic output of triglycerides. Injection of mice with Pluronic detergent inhibits lipoprotein lipase activity, and thus any change in circulating triglyceride levels indicate differences in hepatic secretion (50). Under both uninfected and infected conditions, WT mice showed comparable levels of circulating triglycerides after Pluronic treatment as Lepob and Leprdb mice (Fig. S5C to L), suggesting that differences in hepatic triglyceride output do not explain differences between WT and mutant mice during infection. We next considered whether there were changes in peripheral tissue consumption of triglycerides during infection in WT mice. We performed lipid tolerance tests by injecting mice with Intralipid and measuring the clearance of triglycerides from the blood at postlipid injection time points. Interestingly, we found that Lepob and Leprdb mice became lipid intolerant compared with WT mice during Yptb infection (Fig. 4B and C; Fig. S5M to T). Thus, during Yptb infection, mice deficient for Leptin signaling reduce peripheral tissue consumption of lipids.
The differences in peripheral tissue consumption of lipids suggests that WT and Leptin-signaling-deficient mice may have differences for lipid substrate utilization during Yptb infection. To test this, we housed mice in the Comprehensive Laboratory Animal Monitoring System (CLAMS) and measured the respiratory exchange ratio (RER) to assess their energy substrate preference during infection. An RER closer to 1 indicates primarily carbohydrate usage, while values closer to 0.7 indicate a preference for lipid substrates. Values at ~0.8 indicate a usage of both. Consistent with our hypothesis, we found that the RER of Yptb-infected WT mice shifted toward ~0.7 indicating that they rely of lipids during the infection (Fig. 4D and E; Fig. S6A to D). In contrast, Lepob and Leprdb mice maintained an RER at ~0.8 during infection (Fig. 4F to I; Fig. S6A to D). To determine if lipid utilization contributes to Yptb lethality in WT mice, we treated mice with lovastatin, which lowers circulating triglycerides (51), reducing the levels available for utilization. We found that mice treated with lovastatin were significantly protected from a Yptb infection (Fig. 4J). Thus, our data suggest that the absence of Leptin signaling protects from a shift to lipid utilization during infection and that lipid utilization contributes to Yptb lethality in WT mice.

Leptin deficiency impairs gut and gut-associated lymphoid tissues resistance mechanisms.

Resistance defenses contribute to host health and survival of infection by mediating microbial killing mechanisms to control pathogen burdens. Previous work has shown that Leptin is required for resistance mechanisms against infection. Indeed, for some infections, Leptin deficiency is associated with an impaired immune response and pathogen clearance, as well as decreased survival (47). We evaluated the contribution of Leptin signaling to host resistance defenses against Yptb by measuring pathogen burdens and extraintestinal dissemination over the course of the infection. We infected WT, Lepob, and Leprdb mice with Yptb and measured CFU in various target organs at 24 h, 48 h, and 72 h postinfection. CFU measurements in the small intestine (SI), cecum, and colon revealed substantially higher bacterial burdens in Lepob and Leprdb mice compared with WT mice by 48 h postinfection (Fig. 5A to C). These data suggest that resistance defenses in the intestinal tract are transiently compromised during Yptb infection in mice deficient for Leptin signaling.
FIG 5
FIG 5 Loss of Leptin impairs gut resistance mechanisms. (A to C) Yptb CFU/gram found in the (A) small intestine, (B) cecum, (C) colon at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. Kruskal-Wallis test, *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001. (D) Mesenteric lymph node (MLN) dissemination index at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. Two-way ANOVA, *, P = 0.0144 and **, P = 0.0011. (E) Yptb CFU/gram found in the MLNs at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. (F) Peyer’s patches (PPs) dissemination index at 24, 48 and 72 h postinfection in WT, Lepob, and Leprdb mice. Two-way ANOVA, **, P = 0.0081 and ***, P = 0.0007. (G) Yptb CFU/gram found in the PPs at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. (H) Liver dissemination index at 24, 48 and 72 h postinfection in WT, Lepob, and Leprdb mice. (I) Yptb CFU/gram found in the liver at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. (J) Spleen dissemination index at 24, 48 and 72 h postinfection in WT, Lepob, and Leprdb mice. (K) Yptb CFU/gram found in the spleen at 24, 48, and 72 h postinfection in WT, Lepob, and Leprdb mice. n = 12 to 15 mice per group per time point. Three independent experiments combined. The number of mice with CFU below the limit of detection are indicated at the bottom of each bar as “X ND” where “X” indicates the number of mice below the limit of detection. Geometric mean +/– SD shown for CFU plots.
Pathogenic Yersinia have a pronounced tropism for lymphatic tissues, such as Peyer’s patches (PPs) and mesenteric lymph nodes (MLNs). We found that a higher proportion of mice deficient for Leptin signaling showed dissemination to the MLNs and PPs; however, in WT mice that showed dissemination, the Yptb burdens in the PPs and MLNs were comparable with what we found in Lepob and Leprdb mice (Fig. 5D to G). These data indicate that Lepob and Leprdb mice have impaired resistance defenses in the gut-associated lymphoid tissues (GALT). Finally, in contrast to our gut and GALT results, we found no differences in pathogen dissemination to or pathogen burdens in the liver and spleen of Lepob, Leprdb, or WT mice (Fig. 5H to K), suggesting that systemic resistance defenses are not compromised in Lepob and Leprdb mice during Yptb infection. Interestingly, we found that by 24 h postinfection, WT mice exhibited colonization in the livers and spleens without dissemination events to the MLNs and PPs. This finding is consistent with work from other groups showing that Yptb hepatosplenic dissemination is connected with successful colonization of the intestine and does not result from spreading to gut lymph nodes prior to dissemination to the liver and spleen (52). In summary, our data are in agreement with previous findings demonstrating that Leptin is required for resistance defenses (46). However, we find that, in the case of Yptb infection, Leptin-signaling-deficient mice only have a gut and GALT specific resistance defects, as we did not observe differences in burdens at systemic sites in Leptin-deficient and WT animals. Furthermore, our data demonstrate that the survival advantage conferred by Leptin deficiency is not due to a heightened resistance response to the infection.

Loss of Leptin signaling increases hepatic damage and dysfunction, but dampens inflammation.

We found that the health and survival advantage in Lepob and Leprdb mice was associated with increased pathogen burdens in the gut and GALT tissues, and comparable burdens in the liver and spleen as found in WT mice infected with Yptb. Our data indicate that the absence of Leptin signaling facilitates cooperation between the host and Yptb. While resistance mechanisms are important for host defense by killing the pathogen, if the costs of mounting such responses are too great, hosts that are able to cooperate with the pathogen will have a health and survival advantage compared with those that are more resistant (8). A significant cost of resistance responses is immunopathology. Compromised resistance defenses are often associated with reduced inflammatory responses, which can contribute to a survival advantage by limiting immunopathology, despite elevated pathogen burdens. We hypothesized that the reduced resistance in the gut and GALT of Lepob and Leprdb would be associated with a reduced inflammatory response. We examined the levels of three proinflammatory cytokines that can contribute to immunopathology: TNF-α, IL-1β, and IL-6, and found that mice deficient for Leptin signaling had dampened inflammatory responses in the MLNs compared with WT infected mice (Fig. 6A to C), but no differences in the levels of these proinflammatory cytokines in any other gut tissues analyzed (Fig. S7). While we did not find differences in the pathogen burdens of Lepob and Leprdb mice compared with WT mice, we also measured the levels of proinflammatory cytokines in these tissues because Leptin has proinflammatory properties. Consistent with this, we found significantly lower levels of TNF-α and IL-6 in the liver and no differences in the levels of the cytokines measured in the spleen in WT and Leptin deficient mice (Fig. 6D to F; Fig. S7). These data indicate that the health and survival advantage conferred by deficiency in Leptin signaling is associated with a dampened inflammatory response in the GALT and the liver.
FIG 6
FIG 6 Leptin deficiency dampens inflammation during infection. WT, Lepob, and Leprdb mice were infected with Yptb and proinflammatory cytokines in the (A to C) MLNs and (D to F) liver and measured by ELISA during the first 72 h postinfection. (A) TNF-α levels in the MLNs. (B) IL-1β levels in the MLN and (C) IL-6 levels in the MLNs. (D) TNF-α levels in the liver. (E) IL-1β levels in the liver and (F) IL-6 levels in the liver. n = 10 to 15 mice per group per time point. Three experiments combined. *, P < 0.05; **, P < 0.005; ***, P < 0.005; ****, P < 0.0001 in a two-way ANOVA, Error bars +/− SEM.
We hypothesized that the dampened inflammatory response and survival advantage observed in Yptb-infected mice deficient for Leptin signaling would be associated with reduced tissue/organ/physiological damage. To test our hypothesis, we took a clinical pathology approach. Yersinia infection has been reported to cause both liver and kidney damage (5357). Therefore, we measured the amount of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and blood urea nitrogen (BUN) in the serum of both uninfected and infected mice. AST, ALT, and ALP are markers of liver damage, while BUN is a maker of kidney function. Our data revealed that the circulating levels of both AST and ALT were significantly elevated in WT Yptb-infected mice compared with uninfected WT mice, while ALP levels were unchanged (Fig. 7A to C; Fig. S8A to C). In contrast, BUN levels were reduced between uninfected and infected WT mice (Fig. 7D; Fig. S8D). We found that Lepob and Leprdb had elevated levels of AST, ALT, and ALP, but no difference in BUN levels during infection, suggesting that the absence of Leptin signaling leads to increased liver damage during Yptb infection (Fig. 7A to D; Fig. S8A to D). Compared with WT mice, Leptin-signaling-deficient animals had elevated levels of ALT, AST, and ALP in both uninfected and infected states (Fig. 7A to C). Under uninfected conditions, Leptin-deficient animals had lower levels of BUN compared with WT mice; however, during infection, BUN levels were increased in Lepob and Leprdb mice compared with infected WT mice (Fig. 7D). Furthermore, we found that the BUN:creatinine ratio increased in Lepob and Lepdb infected with Yptb (Fig. 7E; Fig. S8D to E), suggesting that liver and kidney function may be compromised in Leptin-signaling-deficient mice compared with WT mice. Thus, in contrast to our hypothesis, the absence of Leptin signaling renders mice more susceptible to liver and kidney damage and dysfunction despite a dampened inflammatory response and increased survival of infection.
FIG 7
FIG 7 Loss of Leptin signaling promotes disease tolerance during Yptb infection. WT, Lepob, and Leprdb mice were infected with Yptb and serum levels of (A) ALT, (B) AST, (C) ALP, (D) BUN, (E) BUN:Creatinine ratio were measured. n = 8 to 24 mice per condition. Three experiments combined. One-way ANOVA or Kruskal-Wallis test. *, P < 0.05; **, P < 0.01; ***, P < 0.001; ****, P < 0.0001, Error bars +/− SEM or geometric mean +/− SD for log scale. Values presented in this figure are also shown in Fig. S8 to show pairwise comparisons of uninfected and infected for each genotype.

DISCUSSION

The objective of this study was to investigate the role of Leptin in host-pathogen cooperation (8, 11). By taking a holistic approach, we revealed greater complexities for the role of Leptin in infection defenses than previously appreciated. We found that for a single infection type: (i) the contributions of Leptin signaling to host resistance defense are organ dependent; (ii) the contributions of Leptin signaling to the proinflammatory response are organ dependent and show both correlation and no correlation with pathogen burdens depending on the organ; and (iii) Leptin signaling protects from organ damage and dysfunction. It is also noteworthy that our study highlights the significant effects that chronic as opposed to acute Leptin-signaling deficiency has on host defense. Leptin administration did not reverse our survival phenotype, indicating that the physiological effects of chronic Leptin deficiency contribute to the survival advantage of Lepob and Lepdb mice. This is not surprising considering how chronic Leptin deficiency causes a range of physiological effects that cannot be immediately and or fully rescued by reactivation of Leptin signaling (58). However, we cannot discard the possibility that a different dosing regimen could have had a different effect. While Leptin has been long appreciated for its role in promoting pathogen clearance (46), the current study expands our understanding of Leptin in host defense to include a role in the regulation of physiological defenses and host-pathogen cooperation in addition to antagonistic defenses.
We found that during Yptb infection, Lepob and Lepdb mice had a compromised resistance response to infection in the gut and GALT, with a dampened inflammatory response, and increased hepatic damage and dysfunction. Despite this, we found that the deficiencies in Leptin signaling conferred a survival advantage for Yptb infection. A loss of resistance and dampened inflammation can confer a survival advantage to an infected host if the cost of mounting such responses is too costly for host health (8). Typically, these costs come in the form of immunopathology, and a loss of these responses promote survival by protecting the host from tissue/organ/physiological damage. Our finding that the survival advantage conferred by a loss of Leptin signaling was associated with increased hepatic damage and dysfunction was unexpected. There are several nonexclusive models to mechanistically explain our results. First, while we did not observe differences in pathogen burdens in the liver, we did find Leptin deficient mice to have greater burdens of Yptb in the gut and GALT. The increased hepatic damage can be an indirect consequence of the decreased resistance defenses in these tissues. Second, we found reduced levels of proinflammatory cytokines in the liver that may be necessary for protection from hepatic damage. A third model is that hepatic steatosis, which is characteristic of Lepob and Lepdb mice and known to raise ALT, AST, and ALP levels, makes these mice more susceptible to infection-induced hepatic damage (59, 60). Finally, it is also plausible that tolerating hepatic damage and dysfunction may require mice to increase peripheral consumption of triglycerides. This would explain why WT mice, which shift toward lipid utilization during the infection, show less liver damage. In all of these cases, the fact that we found animals that had survival advantage to have increased hepatic damage and dysfunction indicates that there are costs to protection from this damage and dysfunction and in the context of this infection, allowing the damage to occur is less costly than protecting the host from it. While we have a good understanding of the costs associated with resistance and inflammatory responses, we do not have a good understanding of the costs for mounting tissue protective responses. It is tempting to speculate that our results may have revealed a damage allocation model in which the body allocates damage to parts of the body that are able to withstand damage in order to protect other parts that may be less able to withstand damage. Allocation is a common theme in infection biology in the context of resource allocation (61) and perhaps damage allocation will emerge as an important theme in infection biology with future studies.
The health and survival advantage in Leptin-signaling-deficient animals suggests that they are able to endure the consequences of hepatic damage and dysfunction that occurs during Yptb infection. We suggest that this is likely due to a disease tolerance that operates to allow the host to remain healthy by enduring the damage that has occurred. We do not have a good understanding of how disease tolerance mechanisms work to facilitate health and function despite damage and dysfunction, but one likely possibility is that physiological compensation is occurring (8). This involves the adaptation of other systems in the body to the new “state” to facilitate functioning and sustain health despite the damage. Future studies aimed at understanding how Lepob and Lepdb mice succumb to a Yptb infection and how this compares with Yptb infected WT animals will be important for understanding how deficiencies in Leptin signaling influence disease course and outcome.
In our study, we revealed mechanistic insights for a number of metabolic aspects of Yptb infection. We found that similar to other enteric infections (26), Yptb induces infection-induced anorexia and this is dependent on IL-1β. In a mouse model of S. Typhimurium infection, myeloid cells of the lamina propria released IL-1β that signaled to the vagus nerve to induce the anorexic response (26). Future work is needed to determine the cellular source of IL-1β that is necessary for driving the anorexic response during a Yptb infection and whether it is sensed peripherally or centrally to trigger the response. In the case of S. Typhimurium, the anorexic response led to a more severe infection course. In contrast, using dietary and genetic approaches, we found that abolishing the anorexic response had no effect on the outcome of a Yptb infection in mice. This is consistent with previous studies demonstrating that the effects of the anorexic response on infection outcome are infection specific (29, 30). We also found that Yptb induces wasting of WAT over the course of the infection and we demonstrated that ATGL in the WAT is necessary to mediate lipolysis and WAT wasting during Yptb infection. Similar to the anorexic response, we found that inhibition of this lipolytic response had no influence on the outcome of infection. Whether adipose tissue wasting serves a role in defense against bacterial infections is not understood. Furthermore, we found that this infection lowers circulating triglyceride levels. This decrease stands in contrast to the increase that follows infection with several other pathogens (62). While other studies have found that maintaining triglyceride levels during infection protects organs and promotes survival (25), we found that decreasing peripheral tissue consumption of lipids protects mice from Yptb lethality while increasing organ damage. As discussed earlier, increasing peripheral lipid utilization during infection may act to protect against organ damage, which could explain why several infections induce an increase in circulating triglycerides. Finally, a previous study showed that administering lovastatin to mice infected with Yptb’s closely related species Yersinia pestis, the causative agent of bubonic plague, significantly increased survival of infection (63). Although the study did not provide a mechanistic explanation for the conferred protection, it is tempting to speculate that decreasing peripheral lipid consumption could be a strategy to combat infection with multiple Yersinia species.
It is interesting to note that given the significant number of preceding studies to evaluate the role of Leptin in infection defense, these studies, unlike ours, did not find that Leptin deficiency promotes survival of pathogenic infection and host-pathogen cooperation. On the contrary, most found that the absence of Leptin severely decreases survival (47). We speculate that there are at least two main reasons for this occurrence. First, the evolutionary solutions that have arisen from different host-pathogen coadaptations will have unique ways in which each pathogen interacts with its host. Another layer of intricacy adding to whether decreasing Leptin is beneficial or detrimental to the outcome of specific infections comes from Leptin’s dual role in inflammation. While Leptin is generally viewed as a proinflammatory factor, acting to enhance the production of various inflammatory cytokines (64), Leptin has also been reported to reduce inflammation in some infection models. For example, during S. aureus infection, which reduces circulating Leptin in the host, administration of exogenous Leptin lowers the levels of IL-6 and reduces pathology (65). This is in contrast to our own results, where Leptin deficiency reduces inflammation. Beyond inflammation, the effect of Leptin on organ damage is also complex. While we found that Leptin deficiency sustains physiological function in the face of increased organ damage during infection, thereby promoting disease tolerance, a different study showed that administration of Leptin reduces remote organ injury in rats exposed to thermal burn trauma (66). This suggests that whether Leptin deficiency improves physiological function is also highly context dependent. In sum, reduction of serum Leptin may serve as an important clinical tool to manage inflammation and sustain physiological function during some infections, but more work is needed to identify the specific infections that would benefit from this approach.
On a final note, current literature maintains that a rich and diverse microbiota facilitates the health of a host, especially in response to infectious diseases (47). Our finding that Lepob and Leprdp mice maintained their richness in microbiota diversity following infection with Yptb warrants further investigation into possible microbiome-based mechanisms driving the protection from wasting and death compared to WT genotypes.

MATERIALS AND METHODS

Mice.

Six- to 8-week-old male mice were used for all experiments. C57BL/6 (000664) and Lepob (000632) and Leprdb (000697) mice on the C57BL/6 background were purchased from Jackson Laboratories. Il-1β−/− and Pnpla2 fabp4 cre mice were bred in-house. Il-1β−/− mice were previously described (67). B6N.129S-Pnpla2tm1Eek/J (024278) and B6.Cg-Tg(Fabp4-Cre)1Rev/J (005069) for breeding were obtained from Jackson Laboratory. All mutations were confirmed via PCR. For cohousing experiments, C57BL/6, Lepob and Leprdb mice were imported from Jackson labs and cohoused on arrival. Two weeks later, mice were infected with Yptb as described below. Experiments were performed in our AAALAC-certified vivarium, with approval from The Salk Institute Animal Care and Use Committee.
Germ-free mice were bred and housed in the Salk Institute’s gnotobiotic facility. Germ-free mice were kept on a 12:12 h light:dark cycle under sterile conditions in flexible film isolators inflated with high-efficiency particulate air (HEPA)-filtered air. Germ-free mice were fed NEWCO LabDiet 5K67 ad libitum, and they were housed using SaniChip bedding. All water, food, and bedding were autoclaved and transferred into isolators using an autoclave transfer cylinder. Cages were changed weekly. Isolators were monitored for microbial contamination via different methods as previously described (68).

Bacteria.

Yersinia pseudotuberculosis (IP2666) was a gift from Igor Brodsky and James Bliska.

Culturing Yersinia pseudotuberculosis for mouse infections.

Yersinia pseudotuberculosis was grown overnight at 26°C on a 2xYT agar plate with 4 mg/mL of irgasan (Sigma). 2xYT ingredients for 1 L include: 16 g Bacto Tryptone, 10 g Bacto Yeast Extract, 5 g NaCl, 15 g Agar, pH to 7.0. A single colony from 2xYT/irgasan agar plate was inoculated into 6 mL of sterile 2xYT media with a 4 mg/mL of irgasan. The culture was shaken overnight at 26°C (250 RPM). The next evening, a second overnight culture was started by subculturing the 6 mL culture in 50 mL of sterile 2xYT/irgasan. Then, 500 mL of the 6-mL culture was put into 50 mL of sterile 2xYT/irgasan media. This was shaken overnight at 26°C. The following morning an OD was taken to quantify the concentration of bacteria. Bacteria were pelleted by centrifugation and resuspended in sterile PBS to required infection concentrations. For every infection, the inoculum was serially diluted and plated in order to confirm the inoculum.

Mouse infection models.

For every experiment, mice were fasted 12 to 16 h overnight the day before infection. Mice were infected with 5 × 109 CFU/mL in a 100-mL gavage. Postinfection mouse weights, food weights, and survival were assayed. Both single housed and group housed mice were used for experiments.

Food restriction.

Single housed Lepob and Lepdb mice were given a restricted diet during infection that matched the feeding amounts of Yptb-infected WT mice each day postinfection. WT mice and control Lepob and Lepdb mice were fed ad libitum.

Cecal content transplant of germ-free mice.

The cecums of WT, Lepob, and Lepdb mice were dissected separately, and their contents were squeezed into sterile 1.7-mL tubes. Next, 1 mL of a sterile 50% glycerol in PBS solution was added to each tube, and the contents were mixed to generate homogeneous samples. Cecal content stocks were then snap-frozen in liquid nitrogen and stored at −80°C until further use.
For cecal transfer experiments, cecal content stocks were thawed on ice prior to gavage. Germ-free WT mice were transferred out of the germ-free isolator and put onto an ISOcage P system (positive pressure, cat.# ISO30PFEUS) in order to maintain microbial status. Once in the ISOcages, germ-free mice were colonized with the cecal contents of WT, Lepob, and Lepdb mice. After 2 weeks of colonization, mice were infected with Yptb.

Weight matched experiments.

C57BL/6 were imported from Jackson Laboratory at 3 weeks of age and put on a high fat diet (Adjusted Calories Diet [60/Fat], Rx: 2711666, cat.# TD.06414). Mice were weighed one time each week until they reached 31 to 34 g body weight (~5 weeks of high fat diet). Weight matched Lepob and Leprdb fed normal chow were then imported from Jackson Laboratory. Mice were infected as described above and all genotypes were given normal chow (NEWCO LabDiet 5053 pelleted, cat.# 3005740-220) during the infection.

MRI.

An EchoMRI machine was used for all MRIs. MRIs were performed on uninfected and infected mice at day 0, 1, 2 and 3 postinfection to quantify total body fat (g) and lean mass (g).

Quantification of Yersinia pseudotuberculosis in mouse tissues.

Spleen, mesenteric lymph nodes, cecum, colon, liver, small intestine, and Peyer’s patches were harvested from infected mice and bead beaten in PBS with 1% Triton X-100 with a BeadMill 24 benchtop bead-based homogenizer (Fisher Scientific). Tissues were serially diluted and plated on Yersinia selective agar. Agar plates were incubated at 26°C and colonies were quantified. For calculation of the dissemination index for the liver, spleen, Peyer’s patches, and MLNs, at each time point postinfection mice that showed at least one CFU in the examined tissue were assigned a score of 1. Mice that did not have detectable CFU were assigned a score of 0. The fraction of mice that were assigned a score of 1 was then determined. This was determined for each extraintestinal tissue examined.

ELISAs.

ELISAs were performed to quantify the levels of IL-1β, IL-6, and TNF-α in spleen, MLNs, cecum, colon, liver, small intestine, and Peyer’s patches homogenates. The small intestine, liver, and Peyer’s patches were homogenized in 500 μL of 1% Triton X-100 in PBS. All other organs were homogenized in 1 mL of 1% Triton X-100 in PBS. ELISA antibodies were purchased from eBioscience: TNF-α antibodies cat. # 14-7341-85 (primary) and 13–7326-85 (secondary), IL-1β antibodies cat. # 14-7012-85 (primary) and 13–7112-85 (secondary), and IL-6 antibodies cat. # 14-7061-85 (primary) and 13–7062-85 (secondary). Briefly, ELISA plates were incubated with the primary antibody at 37°C for 1 h, washed, and then blocked for 1 h at 37°C in a PBS solution containing 1% Triton and 1% BSA. After washing, samples were loaded and incubated at 37°C for 1 h. Following another wash, the secondary antibody was added to the plate, and the plate was incubated for 30 min at 37°C. After washing, Streptavidin HRP (BD, cat. # 554066) was added, and the plate was incubated for 15 min at 37°C. Following the final wash, an OPD (Sigma, cat. # P3804)-based developing solution was applied to the plate and the reaction was stopped after 15 min using a 3M HCl solution. The optical density at 490 nm was determined using a SpectraMax (Molecular Devices) plate reader and analyzed using SoftMax Pro software 5.4.
For the Leptin ELISA, the Mouse/Rat Leptin Quantikine ELISA Kit (R&D Systems, cat.# SMOB00B) was used on harvested serum.

Clinical pathology.

At the time of dissection, mice were euthanized by CO2 and blood was collected through cardiac puncture. Blood samples were placed in microtainer tubes (BD, cat.# 365967) and centrifuged for 20 min at 6,000 RPM. Serum was snap-frozen using liquid nitrogen and stored at −80°C for downstream analysis.
Harvested serum was used to measure the levels of AST, ALT, BUN, creatinine, and ALP. Clinical pathology analyses were performed by IDEXX Laboratories.

qRT-PCR.

Hypothalami were harvested and then frozen at −80°C for subsequent RNA extraction, using the PARIS Kit (Invitrogen). cDNA was generated using SuperScript IV Reverse Transcriptase (Invitrogen). qRT-PCR was performed using a QuantStudio 5 Real-Time PCR instrument (Applied Biosystems). Primer sequences include: Rps17 forward 5′-CGCCATTATCCCCAGCAAG-3′ and reverse 5′-TGTCGGGATCCACCTCAATG-3′, Lepr forward 5′-TCATCCTACGTCTGAGCCCA-3′ and reverse 5′-GGAGTCAGGAAGGACACA CG-3′, Fos forward 5′-TTTATCCCCACGGTGACAGC-3′ and reverse 5′-ACACGGTCTT CACCATTCCC-3′, Socs3 forward 5′-TTGAGCGTCAAGACCCAGTC-3′ and reverse 5′-CGTGGGTGGCAAAGAAAAGG-3′, Npy forward 5′-CGTGTGTTTGGGCATTCTGG-3′ and reverse 5′-AGCGGAGTAGTATCTGGCCA-3′, Agrp forward 5′-GCAGACCGAGCAGA AGAAGT-3′ and reverse 5′-TTGAAGAAGCGGCAGTAGCA-3′, and Pomc forward 5′-GTACCCCAACGTTGCTGAGA-3′ and reverse 5′-GGCTCTTCTCGGAGGTCATG-3′.

Amplicon 16S rRNA gene profiling analyses.

Cecal material from uninfected and infected WT, Lepob, and Leprdb mice were processed at The Microbiome Core (University of California San Diego, CA, USA) for amplicon 16S rRNA gene sequencing. Samples were preprocessed with a round of mechanical lysis and genomic DNA was extracted following the Earth Microbiome Project protocol. The V4 hypervariable region of the bacterial 16S rRNA gene was amplified using small subunit 515 forward Golay-barcoded, and SSU806 reverse primers, and sequenced using the Illumina MiSeq platform (V2, 300 cycles; Illumina Inc., San Diego, CA, USA).
Sequence data were processed within the QIITA framework for quality control (split libraries v. q2.1.9.1), demultiplexing, trimming sequence reads to a length of 150 nucleotides, and picking suboperational taxonomic units using Deblur (v1.1.0) to resolve exact sequence variants. The output BIOM file was further processed using QIIME2 (v2021.4) for downstream statistical analyses. Alpha rarefaction curves were generated to determine whether each sample was sequenced to saturation; the feature table was subsequently rarefied to 8,000 reads per sample. Taxonomy was assigned using the sklearn classifier and Greengenes 13.8 99% OTUs from 515F/806R region of sequences classifier available from https://docs.qiime2.org/2018.4/data-resources/. A phylogenetic tree was constructed using fragment insertion (QIIME fragment-insertion sepp) to guide phylogenetically aware statistical analyses. Results from the q2-diversity core-metrics-phylogenetic plugin was exported and visualized using ggplot2 within the R platform. Permutation-based statistical testing (PERMANOVA) on weighted UniFrac distances was used to determine the similarity in microbial community composition between each sample.

Lipid tolerance test.

Mice were fasted in fresh cages 16 h prior to the lipid tolerance test with ad libitum access to water. Mice were intraperitoneally injected with Intralipid (Sigma 20% emulsion) at a dose of 10 μL/g body weight. Blood was collected via the lateral tail vein at either 0, 15, 30, 45, 60, 90, 120, 180, and 240 min postinjection or 0, 20, 40, 60, 90, 120, 180, and 240 min postinjection, depending on the number of mice being treated. Blood was spun at 6,000 rpm for 20 min and serum was collected for triglyceride measurements. Total triglycerides were measured using Fujifilm L-Type Triglyceride M kit, following the manufacturer’s protocol.

Pluronic test.

Mice were fasted in fresh cages 16 h prior to the lipid tolerance test with ad libitum access to water. To make pluronic solution, 5 g of pluronic (Sigma Pluronic F-127) were dissolved in 50 mL of water and the solution was filter sterilized with a 0.22 μm filter. Mice were intraperitoneally injected with the pluronic solution at a dose of 10 μL/g of bodyweight. Blood was collected at either 20, 40, 60, 90, 120, 180, and 240 min postinjection, or 0, 60, 120, 180, and 240 min postinjection, depending on mouse condition. Blood was spun at 6,000 rpm for 20 min and serum was collected for triglyceride measurements. Triglycerides were measured using Fujifilm L-Type Triglyceride M kit, following the manufacturer’s protocol. Serum needed to be diluted to be within standard range for the following time points, 40 min was diluted 1/2, 60 min was diluted 1/5, and serum from 90, 120, 180, and 240 min postinjection was diluted 1/10.

Triglyceride assay.

As described in the Wako Fujifilm L-Type Triglyceride M kit protocol, 4 μL of serum from the lipid tolerance test or diluted serum from the pluronic test were added to a 96-well plate. Standards were generated by using Wako multicalibrator lipids in the following series (mg/dL): 96, 192, 288, and 384. To each well, 90 μL of R1 was added and the plate was incubated at 37°C for 5 min. The plate was read at 600 nm and 700 nm. After reading, 30 μL of R2 was added to each well and the plate was incubated at 37°C for 5 min. The plate was read again at 600 nm and 700 nm and analyzed following the manufacturer’s instructions. Readings were taken using a 96-well VERSAmax microplate reader and SoftMax Pro software. In Fig. 4A and Fig. S5A, triglyceride measurements were done by IDEXX Laboratories. The protocol utilized by IDEXX Laboratories does not involve an initial glycerol extraction step prior to quantification of quantification of triglycerides and therefore the values reported represent both glycerol and triglycerides as noted in the figure. Our in-house triglyceride measurements involves an initial glycerol extraction step prior to quantification of triglycerides and therefore the values reported represents triglyceride levels.

In vivo metabolic phenotyping.

For quantification of respiratory exchange ratio (RER) measurements, mice were placed in metabolic cages within a comprehensive lab animal monitoring system (CLAMS) (Columbus Instruments) 24 h prior to metabolic parameter data collection for habituation purposes. Uninfected mouse RER was recorded over the subsequent 24-h period (12 p.m. to 12 p.m.). Mice were then infected with Y. pseudotuberculosis and remained in the CLAMs until the third day postinfection. The RER of the final 24 h and 12-h period was analyzed (12 p.m. to 12 p.m. and 12 a.m. to 12 p.m.) and reported as described in the manuscript.

Lovastatin treatment.

For survival experiments, mice were gavaged with either 20 mg/Kg or 100 mg/Kg of lovastatin (Lupin Pharmaceuticals Inc., cat. # NDC 68180-468-07). Lovastatin was dissolved in Intralipid (Sigma-Aldrich, cat. # I141), and mice received daily gavages that began 7 days prior to infection and ended on day 7 postinfection. Mouse survival was checked daily, and the experiment was repeated twice.

Leptin treatment.

Mice received intraperitoneal Leptin injections (R&D Systems, cat #498-OB) of 0.12 mg/Kg or PBS vehicle. Mice received the first dose the evening prior to infection. The next morning, mice were infected with Yptb and dosed with Leptin throughout the day. Mice were dosed a total of 3 times per day, each dose was separated by 4 h: 0 h (~8 a.m.), 4 h (~12 p.m.), and 8 h (~4 p.m.). Mice were injected 3 times a day, every day until the experiment ended.

Quantification and statistical analysis.

All statistical tests were conducted using Prism version 9.0. Sample sizes, statistical tests used, and P values are indicated in each figure legend. Data shown are either a single representative experiment or data combined from independent experiments, and this is indicated in each figure legend.

Data availability.

Sequence data have been deposited to the European Nucleotide Archive under the accession number PRJEB52090.

ACKNOWLEDGMENTS

We thank all members of the Ayres lab for their continued support. This work was supported by a postdoctoral fellowship from the NOMIS Foundation and the Pioneer Fund Postdoctoral Scholar Award (K.T.), a Canadian Institutes of Health Research Fellowship (J.L.M.), and NIH R01 AI114929, NIH DP1 AI144249, and the NOMIS Foundation (J.S.A.).
J.S.A. holds an adjunct professor position at UC San Diego and is a member of the Rainin Foundation Scientific Advisory Board. The other authors declare no conflict of interest.
Conceptualization: J.S.A.; investigation: K.K.S., J.S.A., S.S., K.T., A.M., J.L.M., S.E.R., Y.M.L., and A.I.; formal analysis: J.S.A., K.T., J.L.M., A.M., S.E.R., and A.I.; supervision: J.S.A. writing – original draft: K.T. and J.S.A.; review and editing: K.T. and J.S.A.

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Information & Contributors

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Published In

cover image Infection and Immunity
Infection and Immunity
Volume 90Number 915 September 2022
eLocator: e00242-22
Editor: Igor E. Brodsky, University of Pennsylvania
PubMed: 35924898

History

Received: 17 June 2022
Returned for modification: 21 June 2022
Accepted: 19 July 2022
Published online: 4 August 2022

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Keywords

  1. disease tolerance
  2. host-pathogen cooperation
  3. Leptin
  4. lipid utilization
  5. physiological damage
  6. Yersinia pseudotuberculosis

Contributors

Authors

Karina K. Sanchez
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Andre Mu
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Present address: Andre Mu, Host-Microbiota Interactions Laboratory, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
Samuel E. Redford
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Division of Biological Sciences, University of California, San Diego, La Jolla, California, USA
Justin L. McCarville
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Arianna Insenga
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Sarah Stengel
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Yujung Michelle Lee
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA
Present address: Yujung Michelle Lee, Department of Immunology Discovery, Genentech, 1 DNA Way, South San Francisco, California, USA.
Molecular and Systems Physiology Lab, Gene Expression Lab, Nomis Center for Immunobiology and Microbial Pathogenesis, Salk Institute for Biological Studies, La Jolla, California, USA

Editor

Igor E. Brodsky
Editor
University of Pennsylvania

Notes

Karina K. Sanchez and Katia Troha contributed equally to this work. Author order was determined based on differences in contributions as noted in the acknowledgements section.
J.S.A. holds an adjunct professor position at UC San Diego and is a member of the Rainin Foundation Scientific Advisory Board. The other authors declare no conflict of interest.

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