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The Role of Interleukin-1 in Wound Biology. Part I: Murine In Silico and In Vitro Experimental Analysis

Hu, Yajing PhD*; Liang, Deyong PhD; Li, Xiangqi MD; Liu, Hong-Hsing MD, PhD*; Zhang, Xun PhD; Zheng, Ming PhD*; Dill, David PhD§; Shi, Xiaoyou MD; Qiao, Yanli MD, MS*; Yeomans, David PhD*; Carvalho, Brendan MD*; Angst, Martin S. MD*; Clark, J. David MD, PhD; Peltz, Gary MD, PHD*

doi: 10.1213/ANE.0b013e3181f5ef5a
Analgesia: Research Reports

BACKGROUND: Wound healing is a multistep, complex process that involves the coordinated action of multiple cell types. Conflicting results have been obtained when conventional methods have been used to study wound biology. Therefore, we analyzed the wound response in a mouse genetic model.

METHODS: We analyzed inflammatory mediators produced within incisional wounds induced in 16 inbred mouse strains. Computational haplotype-based genetic analysis of inter-strain differences in the level of production of 2 chemokines in wounds was performed. An in vitro experimental analysis system was developed to investigate whether interleukin (IL)-1 could affect chemokine production by 2 different types of cells that are present within wounds.

RESULTS: The level of 2 chemokines, keratinocyte-derived chemokine (KC) and macrophage inflammatory protein 1α, exhibited very large (75- and 463-fold, respectively) interstrain differences within wound tissue across this inbred strain panel. Genetic variation within Nalp1, an inflammasome component that regulates IL-1 production, correlated with the interstrain differences in KC and macrophage inhibitory protein 1α production. Consistent with the genetic correlation, IL-1β was shown to stimulate KC production by murine keratinocyte and fibroblast cell lines in vitro.

CONCLUSIONS: Genetic variation within Nalp1 could contribute to interstrain differences in wound chemokine production by altering the amount of IL-1 produced.

Published ahead of print October 1, 2010 Supplemental Digital Content is available in the text.

From the *Department of Anesthesia, Stanford University, Stanford; Veterans Affairs Palo Alto Health Care System, Palo Alto; Department of Genetics & Genomics, Roche Palo Alto, Palo Alto; and §Department of Computer Science, Stanford University, Stanford, California.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.anesthesia-analgesia.org).

Disclosure: The authors report no conflicts of interest.

Address correspondence and reprint requests to Gary Peltz, 800 Welch Rd., Room 213, Palo Alto, CA 94304. Address e-mail to gpeltz@stanford.edu.

Accepted July 27, 2010

Published ahead of print October 1, 2010

Wound healing is a critical component of perioperative patient care. If methods that accelerated wound healing or decreased incisional pain could be discovered, this would lessen postsurgical stress and organ dysfunction, which should improve surgical outcome.1 Similarly, methods that decrease exuberant (hypertrophic) scar formation would reduce the functional and esthetic sequelae that can occur after thermal, traumatic, or surgical skin injury.2 The basic biology underlying the mammalian wound response is well known.3 Shortly after an incision, a fibrin-rich clot is formed to produce hemostasis. Although only a very small number of leukocytes are present in uninjured skin, neutrophils, and subsequently macrophages and mast cells, are rapidly recruited into the wound area.4 The infiltrating phagocytes are thought to protect against infection, clear the wounded area of matrix and debris, and release an array of cytokines that direct tissue repair (reviewed in Ref. 5). The second stage of wound repair (days 2–10) involves new tissue formation, which requires the migration and proliferation of different cell types. The final stage of wound repair, which involves tissue remodeling, begins 2 to 3 weeks after injury and can continue for weeks to months. The cells within the wound area undergo apoptosis that produces a predominantly acellular matrix,3 which leads to fibrosis and scar tissue formation within the wounded area.

We do not have sufficient knowledge about incisional wound biology to develop therapeutics that decrease postsurgical pain, accelerate wound healing, or prevent excessive scarring.2 Global gene expression analyses performed in mice have revealed that the level of expression of >1000 genes were significantly altered within the wound edge 24 hours after wounding.6 Different experimental approaches have been used to study wound biology and have produced conflicting results. For example, macrophages and mast cells produce cytokines and growth factors that are essential for wound healing,7 but knockout mice4,8 without these cells have normal wound healing after experimental incision. Similarly, delays in several wound-healing variables, including wound reepithelialization, were noted in mice with chemokine (Mcp-19) or chemokine receptor (Cxcr210) gene knockouts; however, addition of exogenous macrophage chemotactic protein 1 into incisional wounds did not significantly affect wound-healing variables in normal mice.11

We have previously found that genetic analysis in mice could provide insight into the complicated biology underlying other biomedical responses, including drug metabolism,1215 narcotic drug addiction,1618 or analgesic19 and inflammatory pain responses.20,21 The computational genetic approach has been especially useful when conventional hypothesis-driven approaches have provided little insight or have produced conflicting data. The secreted factors that regulate the recruitment and activation of wound-infiltrating inflammatory cells have a significant role in wound biology. We previously characterized the time course for the production of 8 secreted factors in wounds after murine hindpaw incision.22 The amount of all 8 mediators in wounds that were measured was maximal at either 2 or 24 hours after incision, and all mediators were significantly increased at 24 (but not at 2) hours after incision. Although a single timepoint cannot capture all of the differences in a dynamic and complex system, our previous data indicated that the 24-hour timepoint was optimal for analysis. Therefore, a genetic analysis was initiated by measuring the amount of 16 different cytokines (or chemokines) produced within wound tissue obtained 24 hours after a full-thickness surgical incision in 16 inbred mouse strains.

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METHODS

Cytokine Measurements and Incisional Wounding

Animal experiments were performed according to protocols approved by the Roche Palo Alto Institutional Animal Care and Use Committee. Male mice, 24 weeks old, of 16 inbred mouse strains (MRL/MpJ, LG/J, NZW/LaC, 129S1/SvImJ, SM/J, NZB/B1nJ, LP/J, DBA/2, C57BL/6, A/J, C3H/HeJ, BALB/c, B10.D2-H2dH2-T18c Hc0/oSnJ, BALB/cByJ, AKR/J, A/HeJ) were used in this study. To perform the genetic analysis, multiple inflammatory mediators produced within incisional wounds in 16 inbred mouse strains were measured. A 1-cm incision was made on the back of 10 different mice of each strain to a depth of full skin. Skin tissue surrounding the wound (1 cm × 2 mm, and 1-mm depth) was collected 24 hours later. Sixteen cytokines within the wound tissues were measured using a BioRad Bio-Plex mouse cytokine assay kit (Richmond, CA) according to the manufacturer's instruction (Table 1). The amount of each cytokine was quantitatively determined by comparison to a standard curve. This assay can detect each analyte at a concentration of <10 pg/mL, and the coefficient variation for each assay was <5%. Each data point represents the average of 10 different samples obtained from mice of each strain.

Table 1

Table 1

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Clustering Analysis

A hierarchical clustering method23 was applied to cluster the 16 cytokines into different groups in an unsupervised manner. The dissimilarity measure between a pair of analytes was defined as the Euclidean distance between their log-transformed abundance levels across the 16 mouse strains analyzed, and the complete linkage option was used during the hierarchical clustering.

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Haplotype-Based Computational Genetic Mapping

For genetic mapping, the average macrophage inflammatory protein 1α (MIP-1α) and keratinocyte-derived chemokine (KC) levels for each of the 16 inbred strains was used as the input phenotypic data. Haplotype-based computational genetic analysis of these data was then performed as previously described.24,25 In brief, the 250,837 single nucleotide polymorphisms (SNPs) within a previously described database (http://mousesnp.roche.com) covering 3346 genes were organized into haplotype blocks, which typically consisted of 2 to 4 haplotypes per block.26,27 Haplotype-based computational analysis identifies haplotype blocks in which the haplotypic strain grouping within a block correlates with the distribution of phenotypic data among the inbred strains analyzed. The correlation between the phenotypic data and the haplotypic block is evaluated by calculating the sum of squares of difference between the phenotypic measurement and the group mean. This criterion function is used in McQueen's K-mean clustering algorithm,28 which measures the quality of clustering for any partition of the data. The score is then normalized by the variance of all phenotypic data to become scale invariant, and by a factor that depends on the number of strains and groups to enable valid comparison between blocks that partition the strains into different number of groups. Based on this analysis, the mapping program calculates a P value that assesses the likelihood that genetic variation within each block could underlie the observed distribution of phenotypes among the inbred strains.24,27 The haplotype blocks are ranked based on the calculated P values for the correlations. The genomic regions within haplotype blocks that strongly correlate with the phenotypic data are then analyzed. A complete list of the genes identified by computational genetic analysis of the KC data is available in online supplemental Table 1 (see Supplemental Digital Content 1, http://links.lww.com/AA/A185). The genetic effect size is calculated according to the conventional method: effect size = (SSB − [k − 1] × MSE)/(SStotal + MSE), where SSB is the between-group sum of squares of the analysis of variance model, SStotal is the total sum of squares, k is the number of groups, and MSE is within-group sum of squares divided by (n − k), where n is the total number of objects in the model.27

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Immunohistochemistry of Mouse Skin Wound Tissue

Mouse skin incisional wound tissues were harvested 24 hours after incision of the mouse hindpaw and processed according to published procedures.29 MIP-1α (eBioscience, San Diego, CA), KC (Santa Cruz Biotechnology, Santa Cruz, CA), macrophage (Abcam, Cambridge, MA), and neutrophil-specific (AbD Serotec, Raleigh, NC) antibodies (recognizing ag 4/7) were used as primary antibodies. Cy3-conjugated affiniPURE goat antirabbit immunoglobulin G (Jackson ImmunoResearch Laboratories, West Grove, PA) or fluorescein antigoat immunoglobulin G (Vector Laboratories, Burlingame, CA) were applied as secondary antibodies. Single- or double-labeled images were obtained using Zeiss LSM 510 and LSM 510 META laser scanning microscopes, respectively.

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Keratinocyte Cell Line and Cytokine Measurements

Mouse keratinocyte cell line (CL-177) was obtained from ATCC (Manassas, VA) and cultured in modified Dulbecco's modified Eagle medium with 20% fetal bovine serum and at least 30% of conditioned medium from 3T3 fibroblast cells. Chemokine production was stimulated by the addition of 10 ng/mL recombinant interleukin (IL)-1β (R&D Systems, Minneapolis, MN) or 50 ng/mL lipopolysaccharide (LPS) (Sigma, St. Louis, MO). In some experiments, 50 μM caspase-1 inhibitor (Ac-YVAD-CMK) (Calbiochem, San Diego, CA) or 10 mg/mL IL-1 antagonist (Anakinra; Amgen, Thousand Oaks, CA) was also added. After incubation, the amount of cytokine secreted into the supernatant was measured by enzyme immunoassay using a commercially available kit (R&D Systems), according to the manufacturer's instructions, relative to a standard curve. The lower limit of detection for all analytes varied between 4.7 and 15.6 pg/mL, the upper limit was between 300 and 1000 pg/mL, and the coefficient variation for each assay was <10%. The keratinocyte and fibroblast cell lines did not produce MIP-1α in response to IL-1β or LPS.

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Macrophage Isolation and Stimulation

Peritoneal macrophages were collected by peritoneal lavage using cold phosphate-buffered saline buffer containing 0.5% bovine serum albumin and 2 mM EDTA (Miltenyi Biotec, Bergisch Gladbach, Germany) from C57B6 or Balb/cJ mice. Macrophages were collected and purified using MACS CD11b magnetic beads (Miltenyi Biotec). Cells were cultured in modified Dulbecco's modified Eagle medium containing 10% fetal bovine serum, 4 mM L-glutamine, 1 mM sodium pyruvate, 100 U/mL penicillin, and 100 μg/mL streptomycin. We developed a method for selectively activating the Nalp1 pathway in the purified adherent macrophages. These cells were first primed by exposure to LPS, followed by stimulation with muramyl dipeptide (MDP), a bacterial product that stimulates IL-1β secretion by macrophages through a Nalp1-dependent pathway. MDP induces the formation of a NOD2 and Nalp1 protein complex that leads to caspase-1 activation.30,31 The cells were diluted to 3 × 105 cells/mL before seeding. After overnight culture, cells were primed with 50 ng/mL LPS for 6 hours, washed twice in phosphate-buffered saline, and stimulated with 10 μg/mL MDP complex for 16 hours before the supernatants were collected. To increase cellular MDP permeability, the MDP/TiO2/CaCl2 complex was constructed as described.30

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Statistical Analysis

A 2-sample t test with unequal variance was applied to compare the IL-1β production among C57B6, LG, BALBcBy, and BALBc mouse strains. All analyses were performed using R software (www.r-project.org).

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RESULTS

Genetic Analysis of the Incisional Wound Response

The amount of 16 different cytokines produced (Table 1) within wound tissue obtained 24 hours after a full-thickness surgical incision in 16 inbred mouse strains was measured. Of particular interest, the amount of KC within wound tissue varied 75-fold across the 16 strains (Fig. 1), whereas the level of MIP-1α varied 463-fold (Fig. 2). There were much smaller (<11-fold) and more continuous interstrain differences in the other measured cytokines (available in supplemental Figure S1 [see Supplemental Digital Content 1, http://links.lww.com/AA/A185]). The hierarchical clustering analysis of wound cytokines indicated that KC and MIP-1α production in wounds clustered together across this strain panel (Fig. 3). The hierarchical clustering divided the 16 wound analytes into 5 distinct clusters (using a dissimilarity cutoff of 9): macrophage chemotactic protein 1, (KC, MIP-1α), (granulocyte colony-stimulating factor, IL-1β, inducible protein 10), (eotaxin, vascular endothelial growth factor, IL-1α, IL-6), and (IL-23, transforming growth factor β, RANTES, tumor necrosis factor-α, IL-10, IL-13). Immunohistochemical staining confirmed that KC and MIP-1α were both abundantly produced within the wounds (Fig. 4), were coproduced within dermal tissue near the incision, and that these cytokines were produced by wound-infiltrating phagocytes (macrophages or polymorphonuclear [neutrophil] [PMN]) (Fig. 5).

Figure 1

Figure 1

Figure 2

Figure 2

Figure 3

Figure 3

Figure 4

Figure 4

Figure 5

Figure 5

To investigate the genetic basis for these interstrain differences, the KC and MIP-1α data were analyzed using haplotype-based computational genetic mapping to identify genes with a pattern of genetic variation that correlates with the pattern of chemokine production across the inbred strains. Four of the 22 haplotype blocks that were most highly correlated with the pattern of KC production (P value 3 × 10−5) were within the Nod-like receptor family pyrin domain containing 1 (Nalp1) region (Fig. 1). Similarly, genes within the Nalp1 haplotype block were also highly correlated with the pattern of MIP-1α production (P value 1 × 10−5) (Fig. 2). This region of the mouse genome contains 3 contiguous Nalp1 paralogs (Nalp1a, Nalp1b, and Nalp1c), and the pattern of genetic variation extends across this entire region (Fig. 6). Several independent lines of evidence indicated that Nalp1 alleles could contribute to the interstrain differences in wound responses. First, Nalp1b is a highly polymorphic gene; SNPs within its NACHT, LRR, and CARD domains cause multiple amino acid changes, and they form 7 haplotypes among the 16 inbred strains analyzed here (Fig. 6). Second, Nalp1 is part of an oligomeric protein complex that is referred to as the inflammasome. Conversion of the proIL-1 precursor into the active IL-1 protein requires the assembly of an intracellular complex called the inflammasome, which includes proteins such as Nalp1 that are members of the Nod-like receptor family.32 In response to a variety of stimuli, inflammasomes recruit and activate a protease (caspase-1), which in turn proteolytically processes the proIL-1 precursor into the active cytokine.33

Figure 6

Figure 6

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In Vitro Biological Analysis of the Nalp1 Allelic Effect on Chemokine Production

Based on the genetic correlation, we investigated whether chemokine production by mouse keratinocyte (CL-177) and fibroblast (NIH/3T3) cell lines, which represent cell types present in wound tissue, was induced by IL-1β. IL-1β stimulated KC production by both cell lines, and KC production was not inhibited by YVAD, a caspase-1 inhibitor (Fig. 7). Consistent with the keratinocyte results, macrophage KC and MIP-1α production was also not affected by the caspase-1 inhibitor (YVAD), even when the experiments were performed with a caspase-1 inhibitor concentration that inhibited macrophage IL-1β production (Fig. 8). The complete absence of an effect of the caspase-1 inhibitor indicates that IL-1β–induced KC production was not directly dependent on caspase-1 activity in this keratinocyte cell line.

Figure 7

Figure 7

Figure 8

Figure 8

Because IL-1β stimulated KC production and wound-infiltrating phagocytes (PMNs and macrophages) are the major cellular sources of IL-1β, this raises the possibility that Nalp1 alleles could affect wound chemokine levels through altering IL-1β production by wound-infiltrating phagocytes. Therefore, we investigated whether purified murine peritoneal macrophages could produce IL-1β in vitro in response to specific stimulation of the Nalp1 pathway. After Nalp1 pathway–specific stimulation, the purified macrophages produced significant amounts of IL-1β. Importantly, the ability of the caspase-1 inhibitor to block IL-1β production by these macrophages indicated that the stimulus was indeed caspase-1–dependent (Fig. 8). We then compared the amount of IL-1β produced by peritoneal macrophages purified from C57B6, LG, BALBcBy, and BALBc mice after selective stimulation of the Nalp1 pathway. BALBcBy and BALBc mice, which have a different Nalp1 allele than C57B6 and LG, had the lowest levels of KC in the wound tissue. C57B6 and LG macrophages produced significantly more IL-1β than BALBcBy or BALBc macrophages under these conditions (Fig. 9). The calculated P values from a 2-sample t test with unequal variance for comparison of the BALBcBy and BALB/c values with the other 2 strains were 0.002, 0.006, 0.002, 0.008, respectively; these differences remained significant even after a conservative Bonferroni adjustment for multiple testing.

Figure 9

Figure 9

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DISCUSSION

Our genetic findings led us to investigate a novel genetic and biological mechanism for regulating wound biology. We demonstrate that IL-1 induces chemokine production by fibroblasts, keratinocytes, and macrophages, which are cell types that are present in wounds. Furthermore, the in vitro experimental data indicate that Nalp1 allelic differences affect the amount of IL-1 produced by macrophages. Macrophages purified from strains (C57B6 and LG) with high levels of KC in their wounds produced larger amounts of IL-1 than did macrophages from other strains. Although novel, the finding that genetic variation within Nalp1, an inflammasome component that regulates IL-1 production, correlated with interstrain differences in wound chemokine production, is consistent with what is known about inflammasome biology. Inflammasome components are present in keratinocytes and regulate the skin response to ultraviolet irradiation,34 contact hypersensitivity,35 and even in wound healing.36Nalp1b allelic differences were recently shown to regulate interstrain differences in macrophage susceptibility to cell death37 and in IL-1β secretion30 after exposure to anthrax lethal toxin. Of note, the relative amount of IL-1 produced by C57B6 macrophages after Nalp1 pathway–specific stimulation observed here is different from that reported elsewhere. Although the data were not shown, it was reported that C57B6 macrophages produced less IL-1β after anthrax lethal toxin stimulation than did macrophages purified from other strains.30,37 However, it is likely that differences in the relative amount of IL-1β produced by C57B6 macrophages observed here and under other experimental conditions30,37 are caused by the use of different stimuli to induce IL-1β production. In addition, anthrax lethal toxin–induced lethality in vivo38 and macrophage cell death in vitro39 are complex processes that are also regulated by other genetic loci.39

The large interstrain differences in wound chemokine production could affect wound responses. KC injection into the paw was shown to increase pain sensitivity40; MIP-1α is a chemotactic protein for monocytes that can be produced by infiltrating PMNs and is a major inducer of monocyte entry into sites of inflammation.41 Although we did not observe correspondingly large interstrain differences in IL-1 (α or β) levels within wound tissue at 24 hours after incision (available in supplemental Figure S1 [see Supplemental Digital Content 1, http://links.lww.com/AA/A185]), IL-1 consumption could affect the amount of this cytokine in wound tissue, and this effect could be pronounced at 24 hours after wounding. It is also important to examine how much of the observed variation in wound chemokine levels would be explained by the pattern of genetic variation in Nalp1. The calculated genetic effect size is a frequently used variable that indicates the percentage of the observed phenotypic differences that are explained by a particular pattern of genetic variation. For the chemokine data, the genetic variation within Nalp1 could account for a very significant percentage (approximately 75%) of the observed interstrain variation in the amount of MIP-1α or KC produced in the wounds.

The results presented herein suggest a novel mechanism for regulating the production of wound inflammatory mediators. However, it must be determined whether this in vitro mechanism has in vivo relevance in mice, and if it translates to human wounds. If so, this mechanism for regulating wound chemokine production has a potentially important clinical application, which is explored in the accompanying article.45

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        AUTHOR CONTRIBUTIONS

        Yajing Hu performed experiments and wrote the manuscript; Deyong Liang, Xiangqi Li, Hong-Hsing Liu, Xun Zhang, Xiaoyou Shi, Yanli Qiao, and David Yeomans performed experiments; Ming Zheng, David Dill, and David Clark performed data analysis; Martin Angst and Brendan Carvalho contributed data and to the writing of the manuscript; and Gary Peltz, principal investigator, designed the study and wrote the manuscript.

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        © 2010 International Anesthesia Research Society