Chronic macrophage activation derails muscle repair by disrupting mannose-receptor-linked plasticity revealed by endogenous irg1/acod1 tracking

Domain: biology
Published: 2026-01-07
Editorial outcome: major_revision

Abstract
Macrophages are central drivers of chronic inflammation, yet how a sustained inflammatory state alters their function remains unclear. Using GFP knock-in zebrafish targeting irg1/acod1 that marks macrophage activation, we track the dynamic transitions of macrophages during acute muscle injury under homeostatic and chronically inflamed conditions, induced by genetic mutation of nlrc3l. In the chronic inflammation model, muscle repair is impaired and expression of the mannose receptor mrc1b/cd206 is severely downregulated in a myd88-dependent manner. Two reparative macrophage subtypes, defined by their cellular behavior and single-cell transcriptomics profile, clustering and muscle-encasing, are lost. A chronic infection model recapitulates these defects, underscoring the link to macrophage mrc1b repression. Depleting either mrc1b or macrophages impairs muscle repair. Reinstating normal macrophage states by restoring macrophage nlrc3l expression or ablating myd88-mediated inflammatory pathways rescues muscle repair in nlrc3l mutants. Contrary to conventional discrete states, we identify hybrid M1/M2 macrophage states post-injury. While transient during normal injury response, a pro-inflammatory hybrid state persists during chronic activation, which restricts macrophage heterogeneity, represses mrc1b, and inhibits intracellular cathepsin K accumulation, a hallmark of reparative subtypes. Thus, our study provides mechanistic insight into the dynamics of macrophage activation during muscle injury and repair, and how these processes are modulated under chronic inflammation.

Introduction
Immunedysregulationthatcausespersistentinflammatorycellinfiltrationcanleadtochronictissuedamage,includingsecondaryinjurybeyondtheoriginalinsult1–5.Macrophagesplayacentralroleinthisprocess,asinappropriateorprolongedactivationdriveschronicinflammation1,3,4,6.However,theimpactofalteredmacrophagestatesoninjuryresponsesandtissuerepair,particularlyinthecomplexintactlivingorganism,remainsincompletelyunderstood.Furthermore,themechanismsbywhichmacrophagesbalancetheneedtopromoteacuteinflammationfortissuerepairwithpreventingchronicinflammationandassociatedcollateraldamageremainelusive.

Skeletalmusclehasbeenaprominentmodelforstudyingimmuneregulationoftissueinjuryandrepair3,6,7.Thismodelhighlightsthecriticalinteractionsamongmacrophages(theprimaryinflammatorycells),injuredmusclecells,satellitecells(muscle-specificstemcells),andothercelltypes,allofwhichcontributetotissuerecoveryfollowinginjury1,3,6,8.Recentresearchunderscorestheessentialandevolutionarilyconservedroleofacuteinflammationintissuerepair,withevidencespanningfromzebrafishtohumans7,9–11.Althoughpriorstudieshaveprovidedinsightsintotheroleofmacrophagesinrespondingtoandfacilitatingacutemuscleinjuryrepair1,3,6,8,includingwithsingle-celltranscriptomicsandtrajectoryanalysistoinfertemporalchangesandcellularinteractions12,13,directreal-timeinvivoimagingofmacrophagebehaviorsandinteractionsthroughouttheinjuryresponseremainslacking.Time-lapseimaging,combinedwitharigorouslongitudinalmicroscopyapproach,enabledustotrackmacrophagesacrossdistinctphasesofmuscleinjuryandrepairwithinthesamesubjects.Suchanalysesareessentialforfullyandpreciselyunderstandingtheprogressionfrominflammationtoresolutionatboththecellularandorganismallevelsinanintactlivingsystem.

Macrophagesarebelievedtotransitionfromapro-inflammatorystatetoapro-repairstateatdifferentphasesofinjuryresponse1,8.However,thereremainsdebateaboutwhetherthesemacrophagestatesaredistinctandnon-overlapping,oriftheyrepresentdifferentsubpopulations3,14,15.Understandingthesetransitionsiscritical,asmacrophagedysregulationisimplicatedinvariousdiseases,includingdiabetes,cancer,andneurodegenerativedisorders,wherechronicactivationofmacrophagesormicrogliacontributestopathology1,5,15.

Metabolicreprogrammingisahallmarkofmacrophageactivationandinvolvestheupregulationofthemitochondrialenzymeaconitatedecarboxylase(acod1),alsoknownasimmune-responsivegene1(irg1),inresponsetodiverseimmunetriggers,includingmicrobialinfectionsandendogenousdamage-associatedmolecularpatterns(DAMPs)16–19.Thetranscriptionalinductionofirg1inmacrophageactivationhasbeenwell-characterizedinbothzebrafishandmammals17,18,20–22.Toinvestigatemacrophagestatetransitionsduringinjuryinrealtimewithinalocalizedandcontrolledenvironment,wegeneratedaGFPknock-inalleleatthezebrafishirg1/acod1locus.Thisgeneticallymodifiedalleleallowstracingandisolationofmacrophagesatdifferentactivationstatesbasedondifferentialirg1expression.Previousstudiesinzebrafishhaveshownthatirg1inductionismacrophage-specificfollowingbacterialinfection,asdeterminedthroughco-localizationwithcell-specificmarkersandmacrophageablationapproaches17,22.Whileanearlierstudycreatedatransposon-generatedfluorescentreporterforirg122,weanticipatedthatthepreciseGFPknock-inallelewouldofferamorequantitativereadoutofendogenousirg1expression,ensuringreliableandconsistentquantificationacrossindividualsandclutcheswhileavoidingnon-specificexpression.Ourdirectcomparisonofthisknock-inmodelwithaconventionaltransposon-mediatedirg1reporterforanalysisofactivatedmacrophagessupportedtheseexpectations.

Toexploretheconsequencesofchronicmacrophageactivationinvivo,weemployedthezebrafishGFPknock-inalleleinamutantbackgroundst73lackingtheNOD-likereceptornlrc3l,amutationknowntocausechronicinflammation23,24.Thesemutantsdisplayconstitutivemacrophageactivationintheabsenceofovertimmunechallenges24,allowingconsistenttrackingofchronicmacrophageactivationwithouttheneedtoexperimentallyinduceimmuneresponses,therebyminimizingvariability.Throughdynamicimagingandlongitudinalanalysis,weevaluatedthechronicmacrophageactivationanddemonstratedthatitledtothedepletionoftwokeyfunctionalmacrophagesubtypesrequiredformuscleinjuryclearanceandrepairinvivo.AparallelmodelofchronicmacrophageactivationbypersistentE.coliinfectionmirroredthesephenotypes.Furthermore,impairedtissuerepairmimicstheeffectsofmacrophagedepletion,andislinkedtoasignificantreductionofthemannosereceptormrc1b(alsoknownasCD206).Single-cellanalysisrevealedaprofoundshiftinthetranscriptionallandscapeofthechronicallyactivatedmacrophagestowardadominatinginflammatorystate(sustainedexpressionofinflammatoryproteinasemmp9,tnfa,cxcl11.1amongotherinflammatorygenes)whilestillactivatingreparativepathwaygenes.Thisresultedinreducedcellularheterogeneityandlossofreparativesubtypesrequiredformusclerepair.Thus,chronicmacrophageactivationimpairsmuscleinjuryrepairnotbyenhancingorexpandinginflammatoryfunctions,butbydisruptingreparativeprograms—particularlythroughmrc1bdownregulation.

Takentogether,thisstudyfocusesonthedynamictransitionsandshiftsinmacrophagecellstatesbyvisualizingtheseprocessesinrealtimeDuringaninjuryresponse.Byforcingallmacrophagestowardchronicpro-inflammatorystatesusingthenlrc3lmutants,wetesthowadaptableandreversiblemacrophagestatesareuponaninjuryperturbationwithintheintactlivingorganism.Notably,chronicactivationdrivesmyd88-dependentrepressionofthemannosereceptormrc1b/cd206inmacrophagesinboththegeneticandpersistentinfectionmodelofchronicinflammation.Theseinsightsrevealapreviouslyunrecognizedmechanismlinkingchronicinflammationtoaseverelossofmannosereceptorasacauseforreducedmacrophageplasticityandimpairedtissuerepair.

Results
Generation of GFP knock-in zebrafish irg1/acod1 to monitor macrophage activation
We employed a 48-bp short DNA homology-mediated end joining CRISPR-Cas9 strategy, termed GeneWeld25,26, to facilitate the integration of a P2A-GFP reporter cassette into exon 2 of the zebrafish irg1/acod1 locus (referred to as irg1 herein), proximal to the coding sequence initiation (Fig. 1). Following the selection of irg1 gRNA #2 based on its superior efficacy in inducing CRISPR-induced double-stranded DNA breaks, the genomic region encompassing the gRNA was sequenced from multiple wild-type zebrafish to identify the upstream and downstream 48bp homology sequences for cloning into the gene targeting GeneWeld pGTag vector (Fig. 1a). Wild-type zebrafish harboring exact matches to the short homology sequences flanking their g1 gRNA target site were chosen as parents for single-cell zebrafish embryo injections for CRISPR/Cas9 targeting (Fig. 1a). Subsequent analysis revealed a germline transmission rate of less than 1% for precise GFP knock-in, validated by site-specific PCR assays with two correctly targeted founder fish (#7 and #31) in the F1 generation (Fig. 1b, c). The precise in-frame integration of P2A-GFP at the zebrafish irg1 locus was confirmed via Sanger sequencing in both F1 and F2 generations (Fig. 1c). Notably, zebrafish carrying the GFP knock-in allele of irg1, designated as “irg1-KI:GFP,” exhibited segregation consistent with Mendelian inheritance patterns expected for a single-site integration.

Furthermore, to test the function of the new knock-in reporter, we devised a dual labeling system utilizing irg1-KI:GFP to label activated macrophages coupled with mpeg1:BFP, which labels all macrophages with BFP (Fig. 1d). Upon LPS activation, macrophages in the brain, also known as microglia, robustly expressed GFP, with varying levels at the single-cell level, indicative of the capacity of the knock-in reporter to capture heterogeneity in activation levels compared to the uniformly low basal GFP expression observed in uninjected wild-type controls (Fig. 1d).

Since the GFP knock-in (KI) model effectively replaces the functional irg1 locus, creating a knock-in knockout condition, we independently created an irg1 knockout mutation bcz13 using CRISPR/Cas9 that causes a premature stop codon in irg1 (Supplementary Fig. 1). This mutation was studied to verify that heterozygous individuals did not exhibit a phenotype and were functionally equivalent to wild-type heterozygous fish akin to wild type (Supplementary Fig. 1). We, therefore, used heterozygous GFP knock-in transgenic zebrafish, carrying only one copy of the transgene, to track normal endogenous irg1 expression in all experiments.

Previous studies using whole-mount RNA in situ hybridization (WMISH) in zebrafish demonstrated a clear bimodal distribution of irg1 gene expression in macrophages, with irg1 specifically detected in macrophages at high levels following infection or other immune challenges and normally no expression at baseline17,24. In contrast, an irg1 fluorescent reporter using GFP, generated via Tol2 transposon-mediated transgenesis, showed expression in wild-type macrophages even at baseline, with a significant increase post-challenge in a macrophage-specific manner22. Considering the variability in number and location of GFP insertions by Tol2-mediated integration, we anticipated that the precise single-site GFP knock-in at the endogenous irg1 locus would offer a more accurate reflection of irg1 transcriptional levels. To directly address any differences between the GFP knock-in and Tol2-mediated GFP transgenesis, we generated a similar Tol2-mediated irg1 reporter line, utilizing approximately 4.8kb of regulatory sequence (Supplementary Fig. 2). Comparing the Tol2 and KI GFP reporters, we found that the KI reporter offered lower baseline GFP expression, a larger dynamic GFP range, and no off-target expression, while there was no difference in the reference macrophage BFP reporter used alongside the Tol2 or KI construct (Supplementary Fig. 3). These results also suggest fluorescent reporters are more sensitive in revealing very low levels of irg1 that would be below detection by WMISH.

Tracking macrophage activation in auto-inflammatory nlrc3l mutants reveals a MyD88 dependence
To systematically and continuously observe macrophage state changes in a living system without the need to provoke an immune response that is inherently variable from individual to individual, we utilized the irg1-KI:GFP reporter in nlrc3l st73 mutants. These mutants exhibit auto-inflammatory macrophages at baseline in the absence of any overt immune challenges23,24, but were previously distinguishable only by marker analysis in fixed samples, not in living individuals. Introducing a single copy of irg1-KI:GFP into nlrc3l st73 heterozygous fish and crossing them with non-transgenic nlrc3l st73 heterozygous individuals showed a Mendelian inheritance pattern, with about 50% of progeny inheriting the GFP knock-in reporter as expected for a single site GFP insertion. The irg1-KI:GFP reporter enabled rapid sorting of live nlrc3l homozygous mutants under a fluorescent stereoscope based on a strong GFP induction that is indicative of activated macrophages not observed in sibling and wild-type counterparts (Fig. 2a–d). These mutant macrophages also tend to aggregate on the yolk, thereby offering an ideal location to assay differential activation (Figs. 2a and 3a, b). A complete correspondence (100%) between the irg1-KI:GFP phenotype and nlrc3l st73 genotype was confirmed by PCR-restriction-based genotyping after sorting.

To profile macrophage states in nlrc3l mutants, we used FACS to sort macrophages based on GFP levels (high, low, negative) in irg1-KI:GFP mutants and their heterozygous and wild-type siblings (Fig. 2b, c). Flow cytometry analysis revealed an irg1-high population in mutants surpassing LPS-activated control macrophages in irg1 expression levels (Fig. 2d). Bulk RNA-sequencing of sorted populations identified distinct gene sets upregulated in mutant macrophages, including immune activation, cell stress, and inflammatory response pathways (Fig. 2e–h). Sorted macrophages confirmed their identity with elevated expression of macrophage-specific markers (c1qb, c1qc, csf1ra, havcr1, irf8, lgals3bpb, marco, mfap4, mpeg1.1)28,29, although a few markers showed inconsistent upregulation in mutant macrophages (Fig. 2g). Functional annotation highlighted increased expression of vesicle- and transport-related genes in irg1-high mutant macrophages, consistent with abnormal vesicle-filled phenotype observed in mutant macrophages with high irg1 expression (Fig. 2i), while irg1-low mutant macrophages showed enrichment in ECM and cell adhesion pathways (Fig. 2f–h). Although irg1-low mutant macrophages showed similarly low irg1 levels as control sibling macrophages, they modestly expressed pro-repair M2-like genes (arg2, irf3, ptger2a)28,29, and significantly downregulated the mannose receptor mrc1b/cd206, a M2-associated marker30,31. A substantial downregulation was also seen in irg1-high mutant macrophages (Fig. 2g). Additionally, irg1-low mutant cells displayed an enrichment for neutrophil-specific markers (mpx, lyz)29 (Fig. 2g). To directly confirm these cellular changes in vivo, we imaged double transgenic zebrafish expressing both neutrophil and irg1-KI:GFP reporters in vivo, and observed weak irg1 expression in mutant neutrophils in stark contrast to the absence of irg1 in control sibling neutrophils (Fig. 2i), suggesting that some irg1-low mutant cells are likely neutrophils exhibiting altered states. Furthermore, in vivo imaging revealed an unusually strong induction of inflammatory cytokine tnfa expression at baseline in almost all macrophages using the tnfa:GFP transcriptional reporter32, which is predominately macrophage cell-autonomous as it can be reversed by restoring macrophage nlrc3l expression (Supplementary Fig. 4). Weak tnfa in select few neutrophils was also observed in nlrc3l mutants, while no tnfa was detected in control sibling counterparts (Fig. 2i and Supplementary Fig. 4). These findings highlight substantially altered macrophage and neutrophil states in nlrc3l mutants, and similarly low irg1 immune cell expression in mutants and siblings can render significantly different cellular states.

Additionally, unsupervised hierarchical clustering33 of cell-specific expression levels for a target gene set, followed by protein network analysis34, identified significantly elevated TNF-alpha and non-canonical NF-kB pathways in nlrc3l mutant immune cells (Supplementary Fig. 5). This gene set comprised 55 genes known to be enriched in macrophages, neutrophils, or immune responses (Supplementary Fig. 5). Analysis was performed separately on sorted macrophages (high irg1-KI:GFP+ cells) and sorted neutrophils (lyz:GFP+ cells) from nlrc3l mutants compared to control sibling counterparts (Supplementary Fig. 5). These results revealed notable upregulation of inflammation-associated genes in nlrc3l mutant macrophages, particularly TNF-alpha and components of the non-canonical NF-kB pathway (nfkb2, traf2b, nik/map3k14a, relb) (Supplementary Fig. 5). Interestingly, mutant neutrophils exhibited expression of genes we found typically restricted to zebrafish macrophages (mfap4, tnfa, tlr22, tnfaip8l2b, tnfrs1b/TNFR2, traf6), suggesting a phenotypic shift resembling activated macrophages (Supplementary Fig. 5).

Given significant upregulation of TNF-alpha and NF-kB pathway genes in mutant macrophages that may account for their chronic inflammatory state, we aimed to investigate the role of the central mediator MyD88 by analyzing nlrc3l/myd88 double mutants (Fig. 3a, b, d). MyD88 is crucial for TNF-alpha production and NF-kB pathway activation via Toll-like receptors (TLRs) and interleukin-1 receptors (IL-1Rs), and for non-canonical NF-kB signaling through TNF receptor-associated factors (TRAFs)35–37. In nlrc3l mutants, restoring macrophage nlrc3l expression, deleting myd88, or both, reversed the inappropriate macrophage activation, as evidenced by irg1 and tnfa downregulation, with the combination fully restoring a normal macrophage state on the yolk ball (Fig. 3d, e) and in the trunk (Supplementary Figs. 4, 6). The increase in irg1 expression in activated macrophages corresponded with the induction of macrophage tnfa, while restoring a normal macrophage state in nlrc3l mutants reduced irg1 to baseline levels (Fig. 3d, e) and eliminated tnfa expression (Supplementary Figs. 4, 6), validating irg1 and tnfa as consistent markers of macrophage activation in zebrafish, in agreement with previous reports that examined each marker individually17,38,39. Furthermore, because several Nod-like receptors are known to interact with the adaptor protein called apoptosis-associated speck like protein containing a CARD (also known as ASC) to form cytosolic multiprotein complexes called inflammasomes, responsible for activation of inflammatory signaling, we explored whether the inappropriate macrophage activation in nlrc3l mutants was ASC-dependent. We generated nlrc3l/asc double mutants that showed no change from the nlrc3l mutant activation phenotype or impaired muscle repair after injury, thereby suggesting nlrc3l functioned independently of asc in this context (Fig. 3c and Supplementary Fig. 7a–d). Given that MyD88 mediates TLR signaling responsible for bacterial recognition and response35, we evaluated macrophage activation in nlrc3l mutants under germ-free versus conventionally raised conditions (Supplementary Fig. 7e–g). Our findings showed that while commensal microbes contributed, nlrc3l mutant macrophages themselves retained substantial intrinsic activation (Supplementary Fig. 7e–g). In agreement with this, full rescue of inappropriate macrophage activation in nlrc3l mutants required both macrophage rescue and myd88 deletion, as neither intervention alone produced complete rescue consistently (Supplementary Fig. 6). This indicates contributions from both cell-intrinsic defects and likely non-cell-autonomous signals, supported by the need to delete myd88, a gene mediating TLR signaling. Taken together, these findings highlight the intricate nature of the inappropriate macrophage activation in nlrc3l mutants, where MyD88-dependent signaling, microbial cues, and internal cellular dysregulation collectively contribute to their chronic inflammatory activation state, in addition to the altered state of neutrophils. These results implicate both cell-autonomous and non-cell-autonomous mechanisms in the inappropriate immune activation.

Chronic macrophage activation impairs response to acute skeletal muscle injury
We focused on tracking macrophage states during tissue injury due to the controlled and localized perturbation injury provides, which progresses through distinct phases from inflammation to resolution, with macrophages playing a central role6,11,40. This is particularly evident in skeletal muscle injury where macrophages are thought to transition from a pro-inflammatory to a pro-repair state in both mammals and zebrafish1,6,41,42. Despite this, the precise cellular mechanisms by which macrophages coordinate an effective muscle injury response and repair in vivo, especially their dynamic transformations into diverse subtypes, have remained elusive through static or single-cell transcriptome analysis in previous studies lacking in vivo dynamic imaging.

To address this gap, we developed an acute skeletal muscle injury model in zebrafish involving a major tail amputation (Fig. 4a). We found this model to trigger robust immune responses, where both irg1 (Fig. 4b and Supplementary Fig. 8) and tnfa (Supplementary Fig. 9) are highly induced in macrophages in wild-type zebrafish post-injury, and significant skeletal muscle repair (Fig. 5), distinct from previous zebrafish tail injury studies which focus on less disruptive tail fin truncation and regeneration without extensive muscle injury11,40,43,44.

We used in vivo longitudinal and time-lapse imaging to monitor individual zebrafish embryos, employing a dual labeling system that marks all macrophages and tracks their activation status (Fig. 4b and Supplementary Fig. 10). This approach revealed a consistent macrophage response to injury in wild-type zebrafish (Fig. 4b, c). Initially, macrophages are recruited to the injury site, peaking during the inflammatory phase between 24–30 h post-amputation (hpa) (Fig. 4b, c). Concurrently, there is robust expression of irg1 (Fig. 4b, c and Supplementary Fig. 8) and significant tnfa induction (Supplementary Fig. 9) in a subset of macrophages at the cut site. Time-lapse imaging captured dynamic irg1 induction in macrophages from 5 to 14 h post-injury, both in those migrating to and already present at the cut site (Supplementary Fig. 10 and Supplementary Movie 1). Macrophage recruitment primarily occurred via migration outside circulation: dorsally along the dorsal longitudinal anastomotic vessel (DLAV), ventrally through the caudal vein plexus (CVP), or through the vasculature-free midline (Supplementary Fig. 10 and Supplementary Movie 1). Most macrophages at the cut site within 24 hpa exhibited intermediate to high GFP expression, indicating robust activation with elevated irg1 expression (Fig. 4b). Subsequently, macrophages migrated away from the injury site, redistributing throughout the body during immune deactivation, coinciding with tissue repair and regeneration from 48 hpa onwards (Fig. 4b and Supplementary Fig. 8). Time-lapse imaging showed macrophages and neutrophils engaging in reverse migration away from the injury site, and dynamically surveying the repairing tissue, accompanied by a significant macrophage irg1 downregulation (Supplementary Movie 2). By 96 hpa, complete tissue repair was evident with the tail muscle fully healed, though regeneration to original length did not occur (Fig. 4b).

In stark contrast, chronically activated mutant macrophages maintained consistently high levels of irg1 and tnfa expression both at homeostasis and post-injury (Fig. 4c and Supplementary Figs. 9, 11, 12), yet were deficient from the initiation of the inflammatory response to the acute muscle injury (Fig. 4d–g). Although mutants had comparable macrophage numbers to siblings at baseline, they showed no significant increase post-injury, unlike controls which about tripled in number (Fig. 4d). Mutants also had elevated neutrophil counts at baselines similar to post-injury levels seen in controls (Fig. 4d). Moreover, these mutants did not form the characteristic large and dense macrophage cluster at the cut site observed at ~24 hpa; instead, they exhibited a void in this region where removal of injured and dying cells, and regeneration of myocytes were expected (Fig. 4e, Supplementary Figs. 11, 12, 13). These mutant macrophages interacted as smaller groups of cells that persisted even through the expected resolution phase at 72 hpa and 96 hpa (Supplementary Fig. 12), as depicted in the graphical plots comparing wild-type and mutant macrophage responses (Fig. 4c). Furthermore, while tnfa expression was restricted to macrophages at the cut site in control animals (~31% of macrophages post-injury and nearly none at baseline), nearly all macrophages in the mutants, including those in the caudal hematopoietic tissue (CHT), showed uniformly high tnfa expression (~90% at baseline and >95% post-injury) (Supplementary Fig. 9). Single cell profiling reveals distinct differences in the patterns of immune cell activation between mutant and control macrophages and neutrophils (Supplementary Fig. 11). Mutant macrophages at baseline and post-injury consistently exhibit high irg1 expression levels comparable to or generally higher than activated control macrophages post-injury (Fig. 4d and Supplementary Fig. 11). Additionally, a small fraction of neutrophils in mutants show an atypical induction of irg1 and tnfa expressions at baseline compared with control neutrophils which express neither gene at baseline (Fig. 2i and Supplementary Figs. 4, 11). After injury, irg1 expression is detectable in a small number of neutrophils—on average 7.6% in siblings and 10.7% in nlrc3l mutants at 20 hpa (and 4.3% at baseline in mutants, none in siblings) (Supplementary Fig. 11c). These data show that most macrophages are bright irg1-KI:GFP+ after injury and in baseline mutants, while neutrophils rarely cross the detectable threshold at 30 A.U. (Supplementary Fig. 11b, c). Thus, despite low-level expression in a few neutrophils, irg1-KI:GFP remains a reliable reporter for tracking macrophage-specific responses. Overall, when detectable in injured controls or in mutants, whether at baseline or post-injury, neutrophil irg1 or tnfa expression is significantly weaker and limited to a select number of neutrophils, in contrast to the broad and strong induction of these genes in activated macrophages (Fig. 4d and Supplementary Figs. 9, 11). This data is also consistent with the previously discussed bulk RNA-seq and imaging results in Fig. 2g, i where irg1-low cells from nlrc3l mutants include that of the neutrophil cell type besides macrophages.

Most notably, during the inflammatory phase at ~24 hpa, time-lapse imaging revealed distinct cellular behavioral differences among activated macrophages at the cut site in wild-type and control siblings post-injury (Fig. 4e–g and Supplementary Movies 3 and 4). Macrophages at the injury site that displayed dynamically irregular and migratory cell shapes with high mobility (increased speed and distance traveled, Fig. 4f) are categorized as subtype 1 “mobile”. Other macrophages in close proximity to the repairing tail fin with increased vesicular content and higher phagocytic index (cell-to-cytosol volume ratio), indicating large intracellular vesicles such as phagosomes or endosomes (Fig. 4f) are categorized as subtype 2 “cluster”. The final macrophage population at the injury site exhibited largely stationary behavior with an elongated and columnar morphology oriented along the muscle fibers that are aligned with the body anterior-posterior axis is referred to as subtype 3 “encasing” herein (Fig. 4e–g, Supplementary Fig. 13). Subtype 3 macrophages encircle myocytes and take on a muscle-cell-like shape, showing the largest cell size and greater overall sphericity, particularly in the lowest 10th percentile of the population distribution, indicating less variability in cell shape than the other subtypes (Fig. 4f, g, Supplementary Fig. 13). In mutants, our dynamic tracking of the injury response indicated an apparent absence of subtypes 2 and 3 macrophages, which were consistently observed in all control animals (n=4 for each genotype, Fig. 4e–g and Supplementary Movies 3–6). These observations underscore the behavioral and morphological cellular diversity that may define distinct macrophage functions post-injury, which are compromised in chronically activated mutants.

Chronic macrophage activation linked with severe downregulation of mannose receptor causes unresolved muscle injury, reversible by reinstating a normal state
To delve into the functionally altered macrophages, we explored whether injured skeletal muscle in nlrc3l mutants could effectively repair and regenerate. To visualize muscle tissues, we used muscle actin antibody or actin-binding phalloidin staining, enabling co-localization of macrophages with injured or repairing myocytes (Fig. 5 and Supplementary Fig. 13). Detailed examination of macrophage-myocyte interactions identified three functional macrophage subtypes corresponding to those previously discussed: 1) mobile surveying cells, 2) clustering cells that appear likely phagocytic for clearing injured and dying cells, and 3) elongated stationary cells encasing injured or repairing muscle cells (Supplementary Fig. 13 and Supplementary Movies 3 and 4). Immediately after tail amputation (within 1 hpa), muscle injury was comparable across all genotypes (Supplementary Fig. 13). However, by 24 hpa, mutant macrophages inadequately infiltrated the cut site, although recruitment of neutrophils appeared normal, lacking both clustering subtype 2 and encasing subtype 3 (Fig. 5a, Supplementary Fig. 13 and Supplementary Movie 4). In contrast, sibling controls displayed macrophages that formed clusters appearing likely phagocytic (subtype 2) in the most severely damaged region of the injury site, and encasement of seemingly intact muscle fibers by macrophages (subtype 3) in the adjacent area (Supplementary Fig. 13). By 48 hpa, control siblings had mostly cleared injured cells and debris, resulting in a clean-cut tail end with a well-defined tissue boundary, and only occasional, if any, non-intact muscle fibers remaining (Fig. 5c, d and Supplementary 13). In nlrc3l mutants, although more macrophages were recruited to the injury site, they exhibited limited engulfment of damaged muscle cells, leaving significant cellular damage and debris compared to controls at the injury site (Fig. 5c–f). By 96 hpa, control siblings showed fully repaired muscle with regrowth at the tail tip, forming a pointed end (Fig. 5d-f). In contrast, mutants retained unresolved tissue and failed to form the expected muscle tip at the tail end (Fig. 5c–f). This coincided with deficient activation of satellite cells12,45 critical for regenerating myocytes during active muscle repair1,46, as evidenced by a significant reduction in the emergence of Pax7+ satellite cells46,47 at the injury site observed at both 24 hpa and 48 hpa in nlrc3l mutants (Fig. 5a). These findings underscore that the impaired initial inflammatory response by macrophages in these mutants significantly hindered the ability of macrophages to phagocytose and support injured muscle repair and regeneration.

The loss of essential macrophage functional subtypes 2 and 3, critical for clearance of cellular damage and muscle support, in the chronically activated mutant macrophages prompted us to investigate whether similar outcomes could result from macrophage ablation. To address this, we utilized irf8 mutants48, known to lack macrophages in steady-state zebrafish embryos at stages concurrent with our injury study. Interestingly, although initially devoid of macrophages, irf8 mutants after injury showed the presence of macrophages (Supplementary Fig. 14), likely due to injury-triggered hematopoiesis that is irf8 independent. Despite this partial macrophage recovery, muscle injury in macrophage-depleted irf8 mutants exhibited persistent impairment in repair and regeneration from 48 to 96 h post-amputation, resembling the phenotype of chronically activated nlrc3l mutants (Supplementary Fig. 14). These findings underscore that both chronic activation and depletion of macrophages lead to a similar impaired muscle repair outcome, suggesting a comparable loss of macrophage function during acute injury. To directly assess whether the impaired muscle injury repair was due to altered mutant macrophages, we restored normal macrophages devoid of inflammatory signatures by rescuing macrophage wild-type nlrc3l expression or deleting myd88 signaling. Both approaches effectively reinstated a normal macrophage state, reducing or eliminating irg1 and tnfa inductions (Fig. 3, and Supplementary Figs. 4, 6), and significantly facilitated recovery of injured muscle by 96 hpa to a level indistinguishable to controls (Fig. 5c–f). By contrast, genetic deletion of an inflammasome adaptor protein asc failed to restore a normal macrophage state or muscle injury repair in nlrc3l mutants (Fig. 3c, and Supplementary Fig. 7b–d), supporting that their chronic activation is asc-independent.

To investigate mechanisms underlying functional deficiencies of chronically activated mutant macrophages post-injury, we performed bulk RNA-seq on FACS-sorted macrophages from uninjured and 24 hpa zebrafish embryos. We identified several injury-induced upregulated immune cell genes, including significantly elevated matrix metalloproteinase-9 (mmp9), known as an inflammatory proteinase upregulated in various diseased and inflamed tissues that can facilitate tissue remodeling, cell migration and inflammatory signaling through cleaving and activating cytokines and other secreted proteins49–51, and relb, a non-canonical NF-kB pathway transcription factor52 (Supplementary Fig. 15). qPCR analysis of additional animals confirmed excessive mmp9 expression in nlrc3l mutants at baseline and post-injury, implicating dysregulated remodeling activities that may potentially hinder macrophage ability to respond and phagocytose injured cells (Supplementary Fig. 15). Additionally, relb was significantly increased in nlrc3l mutants at baseline and even higher post-injury as shown by the qPCR analysis, suggesting sustained NF-kB activation that may compromise macrophage function in injury response compared to controls (Supplementary Fig. 15).

Furthermore, mrc1b, a gene encoding the mannose receptor (also known as CD206) of the C-type lectin receptor family crucial for phagocytosis, was shown earlier by RNA-seq analysis as significantly downregulated in baseline mutant macrophages (Fig. 2g), but not its paralog mrc1a (Fig. 6a). To assess the normal post-injury expression of mrc1b, we performed qPCR analysis and HCR in situ hybridization, revealing strong expression in injury-responsive macrophages clustered at the cut site, corresponding to subtypes 2 and 3 in control siblings, and in the ventral region appearing in the caudal hematopoietic tissue (CHT) (Fig. 6b–e). qPCR and HCR validation confirmed downregulation of mrc1b in nlrc3l mutant macrophages at both baseline and post-injury (Fig. 6b–e). This aligns with the loss of functional subtypes 2 and 3, linked to phagocytosis and muscle support, respectively (Supplementary Fig. 13).

The excessive upregulation of mmp9 and relb, combined with a severe loss of mrc1b/cd206 in nlrc3l mutant macrophages at baseline and post-injury, elucidates persistent molecular changes that likely impede critical macrophage functions for facilitating tissue repair processes. In support of this, knockdown of mrc1b using transient CRISPR gRNA in injections with Cas9 was validated using T7 assay and sequencing (Supplementary Fig. 16); this resulted in similar reduction in cluster and muscle-encasing subtypes (2 and 3) (Supplementary Fig. 16) and repair defect as seen in chronically activated nlrc3l mutants, suggesting an essential role for mrc1b in muscle repair (Fig. 6f). The muscle repair defect was also confirmed in the stable mrc1b sa18640 mutant zebrafish (Fig. 6g and Supplementary Fig. 16). These mechanical alterations may be consequences of the chronic inflammatory activation state of nlrc3l mutant macrophages that hinders their ability to perform essential tissue repair functions.

Furthermore, myd88 knockout in nlrc3l mutants using double nlrc3l/myd88 mutants led to recovery of mrc1b expression in macrophages post-injury (Fig. 6h, i), thereby restoring a more homeostatic phenotype. These results are consistent with myd88-dependent signaling contributing to dysregulated macrophage state and significant macrophage mrc1b downregulation in nlrc3l mutants. To further explore the generalizability to additional paradigms of chronic macrophage activation, we developed a model based on persistent systemic E. coli infection (Supplementary Fig. 17a–c). We showed that similarly to nlrc3l mutants, the chronic macrophage activation caused by infection impaired normal skeletal muscle repair (Supplementary Fig. 17d, e), and was associated with a mrc1b downregulation and reduction of both clustering and encasing macrophage subtypes (Supplementary Fig. 17f–k).

Chronic macrophage activation erodes cellular heterogeneity, driving a universal pro-inflammatory program while still expressing repair-promoting genes
To better define the molecular impact of chronic macrophage activation and distinguish macrophage subtypes during muscle injury repair, we performed single-cell RNA-seq (scRNA-seq) on ~10,000 irg1+ cells from zebrafish at baseline (uncut), inflammatory phase (24 hpa), and resolution phase (48 hpa), as well as from nlrc3l mutants at 24 hpa (Fig. 7a and Supplementary Fig. 18). Seurat clustering of quality-filtered cells (n=9603 comprised of 1174 cells (uncut), 3557 cells (24 hpa), 1847 cells (48 hpa), and 3025 nlrc3l mutant cells (24 hpa)) revealed 16 clusters spanning macrophages and neutrophils, with the vast majority of cells expressing canonical macrophage markers (mpeg1.1, csf1ra, mpeg1:BFP) (Fig. 7b–f, Supplementary Fig. 18). Comparing cell distributions across conditions, baseline and resolution (uncut and 48 hpa) cells showed substantial overlap in UMAP space, indicating similar cell states (Fig. 7d). In contrast, cells from 24 hpa (control and nlrc3l mutant) were more divergent—both from other conditions and from each other—with nlrc3l mutant cells preferentially occupying distinct but confined clusters (notably 1, 4, and 11) (Fig. 7d and Supplementary Fig. 18, 19). Neutrophils were identified as clusters 4, 11, and 12, marked by mpx and lyz (Fig. 7f and Supplementary Fig. 20), confirming prior observations of irg1 expression in some neutrophils only after injury especially in nlrc3l mutants (Fig. 2i and Supplementary Fig. 11). The remaining clusters (10, 13–15) were sparse and uncharacterized. The skewed clustering pattern in mutant cells, compared to the broader distribution of control cells, suggests a loss of macrophage heterogeneity under chronic activation (Fig. 7d and Supplementary Fig. 18).

Using prior knowledge from in vivo imaging of macrophages and select markers, we identified Seurat clusters corresponding to previously characterized macrophage subtypes: mobile (subtype 1), clustering (subtype 2), and muscle-encasing (subtype 3) (Figs. 4e–g and 7d and Supplementary Fig. 19). Subtype 1 cells, known to express high levels of irg1 and tnfa, were enriched in cluster 1—predominantly composed of nlrc3l mutant and 24 hpa control cells (Fig. 7d and Supplementary Fig. 18d, e). Subtype 2, which appears only in 24 and 48 hpa control macrophages with strong irg1 expression, was identified in cluster 3 (Fig. 7d and Supplementary Fig. 18d, e). Subtype 3, found exclusively in 24 hpa controls with muscle-encasing macrophages, was mapped to cluster 9, distinguished by high mrc1b expression and predominance of 24 hpa control cells (Fig. 7d and Supplementary Fig. 18d, e). To molecularly profile these subtypes, we performed pseudobulk analysis comparing 24 hpa nlrc3l mutant and control macrophages. Clusters of interest (macrophage clusters 0, 1, 3, 4, 5, 9; neutrophil clusters 4, 11, 12) revealed key transcriptional signatures (Fig. 7e–i). Cluster 3 (subtype 2) showed enrichment for repair and homeostatic genes, particularly those involved in lipid metabolism (fabp4a, apoeb, apoc1) and phagocytosis/ECM remodeling (mertka, npc2.1, npc2.2, ctsk, ctsl.1, ifi30a) with moderate levels of pro-inflammatory genes (including tnfa and nfkb2). Cluster 9 (subtype 3) was characterized by upregulation of TGF-beta signaling (tgfbr1a, tgfbi, tgfbrap1) and endocytic pathways (cd302) (Fig. 7e). Overall, chronically activated nlrc3l mutant cells upregulated pro-inflammatory genes and negative regulators of inflammation—including TNF-alpha, interleukins, cytokines, type II interferon and NF-kB components (tnfa, ifngr1, il6, tgfb1b, il10ra, il4, nfkb2, traf2b, nik/map3k14a), while downregulating TGF-beta pathway genes that were normally upregulated in 24 hpa control macrophages (Fig. 7g–i). This shift points to a dysregulated and uniformly pro-inflammatory state in chronically activated mutant macrophages, consistent with and extending insights from bulk RNA-seq results (Fig. 2g).

To isolate macrophage-specific changes, we further subclustered the dataset using cells in clusters 0-3 and 5-9 (Fig. 7b), excluding neutrophils (Fig. 7j–m, Supplementary Fig. 19). UMAP projections of macrophage-only data revealed that nlrc3l mutant macrophages were concentrated in specific subclusters (notably 1 and 5), while control macrophages at various time points were broadly distributed (Fig. 7j, k). Baseline (control uncut) and 48 hpa control macrophages again showed close overlap, reinforcing their shared transcriptional identity. Despite high levels of pro-inflammatory genes (acod1, tnfa, cxcl11.1, mmp9), chronically activated mutant macrophages still express many repair-associated genes (mrc1b, ctsk, apoeb, fabp4a, tgfbi, sb:cb81 also known as ZFP36L1-like) and alternative activation markers (arg2, il4), albeit at lower levels (Fig. 7l, m). Among these, mrc1b was the most strongly downregulated gene in mutant macrophages at 24 hpa (Fig. 7l, Supplementary Fig. 19g). Although thought to support phagocytosis, mrc1b was unexpectedly most highly expressed in homeostatic and resolving macrophages (Fig. 7l, Supplementary Fig. 19g), rather than during the peak phagocytic period in the initial inflammatory phase of the injury response. Its strong suppression in chronically activated macrophages suggests that macrophage activation may negatively regulate mrc1b transcription and that its functional role in macrophage biology is more complex and not fully understood.

Moreover, a substantial proportion of mutant macrophages (ranging from ~10% to over 50%) co-expressed classical M1 and M2 markers, a phenomenon we termed hybrid M1/M2 states (Fig. 8a, Supplementary Fig. 19). These hybrid cells were less than 10% of the control 24 hpa macrophages, indicating that while hybrid states occur under normal conditions, chronic activation significantly enhances this mixed inflammatory/repair phenotype (Fig. 8a, Supplementary Fig. 19). Although gene markers corresponding to subtypes 2 (based on cluster 3 markers, apoeb+/ctsk+) and 3 (based on cluster 9 markers tgfbi+/sb:cb81+) were present in nlrc3l mutant macrophages, they were significantly underrepresented and localized to regions with high expression of pro-inflammatory activation genes like irg1 and tnfa (Figs. 7l, m and 8a). This further supports the conclusion that chronic macrophage activation skews the transcriptional landscape toward a uniform, hybrid inflammatory state while eroding the normal cellular diversity required for balanced muscle repair.

Although some irg1+ cells post-injury were identified as neutrophils (clusters 4, 11, and 12) (Fig. 7f), especially in nlrc3l mutants, their EGFP transcript counts were tens to hundreds times lower than in macrophages (Supplementary Fig. 19h), consistent with low reporter levels seen by in vivo imaging (Fig. 2i and Supplementary Fig. 11). Subclustering of neutrophils from scRNA-seq showed that most of these cells were from 24 hpa nlrc3l mutants and exhibited altered states, expressing both M1 and M2 markers (e.g., acod1, tnfa, mmp9, arg2) (Supplementary Fig. 20), consistent with bulk RNA-seq results showing phenotypic shift resembling activated macrophages (Fig. 2g and Supplementary Fig. 15). Overall, irg1-KI:GFP reliably tracks macrophages at baseline, when neutrophils do not express the reporter, and during activation, when macrophages express the reporter at a much higher intensity and abundance, clearly distinguishing them from neutrophils under perturbation.

Our scRNA-seq analysis identified an endolysosomal protease cathepsin K (ctsk)53 as a key marker highly upregulated in clustering subtype 2 macrophages during the initial inflammatory phase of a muscle injury response at 24 hpa (Fig. 7m). To validate this, we conducted in vivo experiments showing that cathepsin K (CTSK) protein was not only abundant in clustering macrophages, as predicted, but enriched in muscle-encasing macrophages, forming large dense cytosolic accumulations (Fig. 8b), suggesting intracellular collagen and protein degradation53,54 as a critical function shared by these subtypes at 24 hpa. Strikingly, these densely packed CTSK+ domains were entirely absent in chronically activated nlrc3l mutant macrophages post-injury (Fig. 8b), indicating a profound loss of a hallmark protease. During injury response, CTSK+ cells co-expressed tnfa, consistent with a hybrid reparative-inflammatory state in wild-type and control macrophages as suggested by the scRNA-seq data (Fig. 8a and Supplementary Figs. 18, 19). While mutant macrophages co-expressed tnfa and ctsk at the transcript level, ctsk expression was markedly reduced transcriptionally, and CTSK protein was detectably low (Fig. 8b and Supplementary Figs. 18, 19).

Overall, single-cell transcriptomic analysis revealed that chronic macrophage activation due to nlrc3l deletion reduced cellular heterogeneity, reinforced a dominant pro-inflammatory transcriptional program, and promoted hybrid M1/M2 states co-expressing inflammatory and repair-associated markers. These hybrid states, less frequent in control macrophages (<10% at 24 hpa), were significantly enriched in mutants. At least three macrophage subpopulations were identified, including the pro-inflammatory subtype 1 marked by high irg1 and tnfa, and two pro-repair subtypes: subtype 2, characterized by cholesterol efflux (fabp4a, apoeb, apoc1) and phagocytosis-related genes (mertka, npc2.2, ctsk, ctsl.1, ifi30a), and subtype 3, marked by TGF-β signaling (tgfbr1a, tgfbr1b, tgfbi). Both reparative subtypes were significantly depleted in mutants. Thus, chronic macrophage activation impairs muscle injury repair not by enhancing or diversifying inflammatory functions, but by disrupting reparative programs. Furthermore, pro-inflammatory gene expression underlies the transcriptome of these macrophages, constraining their plasticity despite showing expression of pro-repair pathways, albeit at a reduced level. Together, these results provide new mechanistic insights into how chronic inflammation disrupts macrophage-mediated repair by downregulating mrc1b/cd206, blocking cathepsin-K-rich degradative compartments, and promoting functionally deficient hybrid states, and also establish cathepsin K as a validated marker of reparative macrophage identity in zebrafish.

Methods
Zebrafish transgenic and mutant lines
Embryos from wild-type, mutant, and transgenic backgrounds were derived from: nlrc3st7323, irf8st9548, myd88b135881, irg1/acod1bcz13 (this study), ascbcz82/nc303cs (this study), mrc1bsa18640 (this study), irg1-KI:GFP (knock-in, this study), irg1:GFP (tol2-based, this study), tnfa:GFPpd102832, “macro-rescue” mpeg1:nlrc3l24, lyz:mCherry82, mpeg1:GFP61, and mpeg1:BFP82 and raised at 28.5°C to stage for analysis. Genotyping primers and assays are described in Supplementary Data 1. This study was carried out in accordance with the approval of UNC-Chapel Hill Institutional Animal Care and Use Committee (protocols 19-132 and 22-103).

Generating GFP knock-in at theirg1/acod1 locus using GeneWeld platform
GFP knock-in followed protocol as previously described25,26. High quality genomic DNA was used to identify the 48-bp upstream and downstream homologous arm sequences for cloning using Type IIS restriction enzymes BfuAI and BspQI for ligation into the GeneWeld (GW) plasmid, pGTag vector25,26. The following primers were used to verify the correct insertions: 5’_pgtag_seq: 5’-GCATGGATGTTTTCC CAGTC-3’ and 3’_pgtag_seq: 5’-ATGGCTCATAACACCCCTTG-3’. Single-cell injections into zebrafish were conducted using a mix containing the universal gRNA, irg1 gRNA-2, Cas9 mRNA, and theirg1-targeting GW vector, and also without the irg1-targeting GW plasmid as a negative control. A total of 15 injected F0 adults were outcrossed to generate stable F1 founders. Progeny from only 1 out of 15 F0 fish gave a GFP validation by PCR. Assessment of 49 adult F1s yielded 2 fish (#7 and 31) carrying GFP that was localized to the irg1 locus (yielding a 0.3% success rate) as verified by PCR and Sanger sequencing using multiple primer sets as well as by experimental evidence of a Mendelian segregation of the reporter expression. This new fish line is named “irg1-KI:GFP”.

Cloning and creating transgenic TOL2-based irg1:GFP reporter
Approximately 5kb of regulatory sequence upstream of the irg1/acod1 coding sequence for the start codon was cloned from the BAC DKEY-57A22, which contained the zebrafish chromosomal region encompassing theirg1 region in chromosome 9, using theirg1p−4794F and irg1p+18R primers as listed in Supplementary Data 1. This represents a longer fragment than that used in the previously published TOL2-based irg1 reporter by Sander et al.22. The ~5kb regulatory sequence of irg1 was cloned into a Gateway-compatible p5E vector backbone to be combined with a pME-GFP coding sequence to create the irg1:GFP plasmid. Tol2-mediated transgenesis was used to integrate this reporter cassette into the zebrafish genome to create the new irg1:GFP stable transgenic line, as shown in Supplementary Fig. 2.

Tail amputation
Zebrafish embryos at 2 dpf were anesthetized in 0.02% MS-222 (tricaine) supplemented with 0.003% PTU. Embryos were amputated at the halfway point between the end of the yolk extension and tail fin end (~0.5mm measured from tip of tail fin equivalent to ~8-10 somites from end of yolk extension) in a Sylgard lined petri dish using a 5mm straight microsurgical blade with a 15 degree angle (Sharpoint Microsurigical Knives, 72-1551). After the operation, embryos were immediately transferred to fresh water with PTU and monitored for recovery. Most experiments focus on the initial inflammatory phase of the injury response, so embryos were typically collected 18-24 h after amputation for the 24 hpa time point.

In vivo time-lapse and static confocal imaging and analysis
All time-lapse and static z-stack imaging were performed using a Nikon A1R+ hybrid galvano and resonant scanning confocal system equipped with an ultra-high speed A1-SHR scan head and controller. Images were obtained using an apochromat lambda 40x water immersion objective (NA 1.15) or a plan apochromat lambda 20x objective (NA 0.75). Z-steps at 1–3 µm were taken at 40x and 3–5 µm at 20x. Different stages of zebrafish were mounted on glass-bottom dishes using 1.5% low-melting agarose and submerged in fish water supplemented with 0.003% PTU to inhibit pigmentation. All image acquisition parameters were kept constant within an experiment (including laser power, gain, speed, and resolution). Image analysis was performed using ImageJ Fiji version 2.9.0 for injury analysis at the tissue or cell population level, or Imaris 10.1.1. software (Bitplane Oxford) for dynamic imaging or large-scale single cell quantifications (fluorescence, numbers). Traced ROIs were measured for area and fluorescence levels from original, unadjusted raw data. For tail cut images, “cut site” is defined as the region within the two intact somites from the edge of the injured tail. The largest ROI within one intact somite from the edge of the injured tail and injured tissue is defined as the “cut site cell cluster” for analysis. Imaris analysis was used to generate 3-dimensional surfaces of cells of interest using Machine Learning Pixel Classification with the Fiji/ImageJ Plugin Labkit, followed by manual curation to ensure accuracy. Quantification of fluorescence levels and other measurements were taken from surfaces created for the different cells using Imaris. For movie analyses, macrophage surfaces were generated using customized algorithms, where surfaces were tracked over time, and machine learning segmentation was used on the GFP channel for macrophages with repeated training. Slicer extended section was set at 3μm, the size of each Z-slice, and any ROIs less than 10 voxels were filtered out. Tracking was conducted using the autoregressive motion algorithm with a max distance of 20 μm. Repeated manual editing was required to separate clumps and cells in close contact using the cut surface tool, or to connect pieces that belonged to one cell using the unify tool at every time point. Tracks of each cell ROI were then aligned which required manual checks and editing to disconnect or reconnect to assemble a correctly integrated track, which was repeated for each ROI at every time point.

Fluorescent stereoscope imaging and analysis
Leica M165 FC microscope (Leica Microsystems, Germany) equipped with a Leica DFC9000 GT camera was used to acquire fluorescent images of live whole embryos. Embryos were mounted in petri dishes with 1% low-melting agarose and covered with water supplemented with 0.003% PTU, and imaged individually with consistent laser power and magnification settings within each experiment. Yolk ball analysis was performed using ImageJ Fiji. Any visible fluorescent cells within the boundary of the yolk ball were captured as an ROI. ROIs were created automatically by using the threshold tool to generate a mask of fluorescent cells and selecting the "Analyze Particles" option to create the ROI set. A freehand selection tool for manual tracing was used to generate additional ROIs of any missed cells from the automated threshold setting. ROIs were then used to measure area and fluorescence levels from original unadjusted images.

Whole mount immunohistochemistry
Embryos were fixed in 4% paraformaldehyde (PFA) for 2h at room temperature or overnight at 4°C, followed by a series of PBST washes (phosphate-buffered saline with 0.2% Tween 20) and passage through 100% methanol at −20°C until proceeding with immunostaining. Pax7 antibody staining required a shorter fixation protocol using 2% PFA fix for 20 min at room temperature. Blocking solution was PBST with 5% normal goat serum, followed by overnight incubation with the primary antibody at 4°C, then washed before proceeding to an overnight incubation with the appropriate secondary antibody at 4°C. The following primary antibodies were used in blocking solution: rabbit anti-smooth muscle actin (GTX100034, GeneTex) at 1:500, chicken anti-GFP (ab13970, Abcam) at 1:500, mouse anti-Pax7 (AB_528428, DSHB) at 1:100, and rabbit anti-CTSK (cathepsin K) at 1:500 (E7U5N, Cell Signaling Technology) followed by incubation with the appropriate secondary antibodies used at 1:500 to 1:2000. Use of antibodies were validated based on pattern of staining in control normal samples that matched description of reagent provided by the manufacturer and previously published data. DAPI (Roche) may be used in the last wash at 5 μg/mL for an hour. See Supplementary Data 1 for details of reagents used.

Phalloidin staining for muscle actin
Embryos were fixed in 4% paraformaldehyde (PFA) for 2h at room temperature or overnight at 4°C, followed by several 10-min PBST washes and incubation with Phalloidin-iFluor 647 (Abcam) at 1:500 dilution in PBST overnight at 4°C. After staining, embryos were washed in PBST and mounted in 1% low-melting agarose for imaging.

Whole mount hybridization chain reaction (HCR)
Embryos, either injured or normal, were fixed in freshly made 4% PFA overnight at 4°C and stored in 100% methanol. To proceed with HCR, embryos were rehydrated, permeabilized using proteinase K, and processed through a series of reagents as per protocols previously published and provided by the manufacturer (Molecular Instruments). Probe targets and amplifiers were designed and made by Molecular Instruments as listed in Supplementary Data 1.

Isolation of macrophages for bulk transcriptome analysis by FACS
Embryos from nlrc3st73 heterozygous in crosses were sorted as siblings or mutants based on a high induction of irg1-KI:GFP expression at 3 dpf. Around 20-50 embryos were dissociated per sample on ice in FACSmax Cell Dissociation Solution (Amsbio) in a microcentrifuge tube using a motorized pellet pestle (Fisherbrand) until the sample is completely homogenized. The cell suspension was filtered through a sterile 35 μm nylon mesh (Falcon, 352235) and another passage through a sterile 20 μm mesh strainer (EASYstrainer, 542120) with an additional 500 μL FACSmax solution run through. The dissociated cell suspension was then analyzed and sorted directly into RNA lysis buffer (Ambion) on a BD FACSMelody Cell Sorter. General gating was applied using forward and side scatter to distinguish populations for single live cells that represented macrophages expressing high and low GFP expression from the irg1-KI:GFP transgene. See gating strategy in Supplementary Fig. 21.

RNA isolation and qPCR
RNA was isolated using the RNAqueous-Micro kit RNA Isolation Procedure (Ambion). Whole larvae were lysed in 100–300 uL RNA lysis buffer. cDNA was made from 150 or 200 ng of total RNA using oligo (dT) primer with SuperScript IV reverse transcriptase (Invitrogen). qPCR was performed on the QuantStudio 3 Real-Time PCR System (Applied Biosystems) using SYBR Green. The delta-delta CT method was used to determine the relative levels of mRNA expression between experimental samples and controls. ef1α was used as the reference gene for the determination of the relative expression of all target genes. Primer sequences for qPCR analysis are listed in Supplementary Data 1.

Bulk RNA-seq analysis
Paired-end RNA-Sequencing was performed on FACS-sorted macrophages derived from a pool of 20-50 embryos at 3 dpf either at baseline or 24 hpa. Three independent biological replicates for each condition were used for sequencing on an Illumina NovaSeq 6000 S2 or NovaSeq 6000 SP using 2×50 base pairs, each replicate represents a different cohort of embryos from which macrophages were isolated by FACS. The mutants were pre-sorted by spontaneous induction of the irg1-KI:GFP, and the genotypes of all RNA samples were also verified by PCR-restriction enzyme assay-based genotyping prior to library preparation using the SMARTer HT+ Nextera XT for low-input samples. 100% correspondence was found between the sorted phenotypes based on the presence or absence of irg1 induction and the expected nlrc3l mutant or sibling genotypes, respectively. RNA-seq analysis followed the previously used protocol24, which consists of modules and packages including Trimmomatic for data trimming, MultiQC for quality control, and BBMap for sequence alignment with the zebrafish reference genome (GRCz11). The differential expression analysis was performed using DESeq2. Gene ontology analysis was performed on the differentially expressed genes with Metascape34 and clustered heatmap analysis with NG-CHM33.

CRISPR-Cas9 targeted mutagenesis of irg1/acod1, asc and mrc1b
CRISPR gRNA designs, and synthesis of Cas9 mRNA and gRNAs for targeting zebrafish irg1/acod1 (NCBI accession: NM_001126456.2; Gene ID: 795305), asc (NCBI accession: NM_131495.3; Gene ID: 57923), and mrc1b (NCBI accession: NM_001423726.1; Gene ID: 559502) followed previously described methods82. Co-injection of Cas9 mRNA and guide RNAs (gRNAs) was conducted in 1-cell stage zebrafish embryos. gRNA target sequences and genotyping primers are provided in Supplementary Data 1. To ensure high mutagenesis rate and large deletion mutations, two or more gRNAs were simultaneously injected with Cas9 mRNA for each gene. Injected clutches of embryos were validated to contain CRISPR-mediated mutagenesis by a T7 endonuclease assay.

E. coli infection model combined with tail amputation
To induce systemic bacterial infection, wild-type transgenic zebrafish carrying irg1-KI:GFP; mpeg1:BFP at 2 dpf were anesthetized in 0.02% Tricaine (MS-222) for direct microinjection into the brain ventricle either with 1 nl of ~1000 CFU/nL of a common laboratory E. coli strain (MG1655 [CGSC6300]) or 1 nl of phosphate-buffered saline (PBS) as negative controls alongside uninjected animals for each experiment. Previous studies showed brain ventricle microinjection into the zebrafish embryo rapidly spreads systemically throughout the body82. Persistence of macrophage activation based on irg1 expression was assessed using the irg1-KI:GFP reporter with a single injection (4–6h before amputation) or double injections (day-of and ~24 hpa), either method caused a sustained irg1 induction and activation of macrophages. All data reflect a single brain injection to induce chronic inflammatory macrophage activation prior to muscle injury that lasted past the resolution phase at 72 hpa (Supplementary Fig. 17). After validation of a bacterial response 4-6 h post-injection based on a strong induction of the irg1-KI:GFP expression, the embryos were amputated to induce skeletal muscle injury as described previously. Zebrafish following tail amputation were placed back into the 28.5°C incubator to allow recovery until embryo collection at 20-24 hpa for downstream analysis.

scRNA-seq cell preparations and sequencing
Transgenic zebrafish carrying the GFP knock-in reporter irg1-KI:GFP generated in our lab were used to isolate macrophages at distinct phases of acute muscle injury response. Samples were collected at 24 hpa, representing the initial inflammatory phase, and at 48 hpa, marking the onset of tissue repair following debris clearance. Uninjured (“uncut”) animals served as baseline controls. Responses were compared between wild-type (or control sibling) zebrafish and mutants with a deleterious nlrc3l mutation that causes chronic macrophage activation. To induce acute muscle injury, large tail amputations were performed on 2 dpf zebrafish embryos. Activated macrophages upregulate irg1, displaying strong GFP fluorescence, while steady-state macrophages express minimal irg1, resulting in faint GFP signal. All irg1-KI:GFP+ cells expressing any detectable level of GFP were isolated using FACS on a BD FACSMelody across four conditions: control uncut, control 24 hpa, control 48 hpa, and nlrc3l mutant 24 hpa. Two biological replicates were collected per condition, resulting in a total of eight samples, each consisting of pooled cells from 90 embryos. To maintain cell viability and quality, embryos were dissociated and sorted in batches of 30, with three such batches pooled to constitute a single sample. Sample collection was interleaved to evenly distribute conditions across the processing timeline. Embryo dissociation was performed in a buffer containing ROCK inhibitor, protease, and DNase with gentle mechanical grinding, and a holding solution composed of HBSS (without phenol red), 1% BSA, and ROCK inhibitor. Cells were kept on ice until downstream processing using the 10x Genomics Chromium X Controller and the GEM-X Universal 3’ Gene Expression v4 4-plex kit (PN-1000779) following the manufacturer’s instructions. Cells were first verified for viability, concentration, and singleness using acridine orange and propidium iodide on the LUNA-FX7 Dual Fluorescence Cell Counter (Logos Biosystems) prior to 10x Genomics preparations. Single-cell libraries were prepared using the GEM-X OCM 3’ Chip, where samples were uniquely indexed and pooled in groups of four into two different GEMs during loading via on-chip multiplexing (OCM) technology. Reverse transcription was performed using a C1000 thermal cycler (Bio-Rad) to create cDNA libraries tagged with a cell barcode and unique molecular index (UMI). Dynabeads MyOne SILANE beads (Invitrogen) were used to purify broken GEMs prior to cDNA amplification, and final libraries with Illumina-compatible adapters were purified with SPRIselect magnetic beads (Beckam Coulter) and quantified using an Agilent Bioanalyzer High Sensitivity DNA chip (Agilent). Libraries were pooled in an equimolar ratio and sequenced on one lane of a NovaSeq X Plus 10B flow cell (Illumina) in paired-end format at Admera Health, LLC (Read 1: 28 cycles, i7 index: 10 cycles, i5 Index: 10 cycles, Read 2: 90 cycles).

scRNA-seq analysis
Eight samples spanning four conditions were processed across two Cell Ranger Multi runs. Custom transgenes (EGFP and TagBFP) were appended to the zebrafish reference genome (GRCz11, from 10x Genomics). Gene expression matrices were generated using Cell Ranger Multi with sample demultiplexing guided by configuration CSVs specifying sample IDs, reference paths, and OCM barcodes. Downstream analysis was performed in R using Seurat (v5). Cells were filtered using miQC with a posterior cutoff of 0.80, mitochondrial content column set as “percent.mt”, and nFeature_RNA as the gene feature input. Cells marked as “discard” by miQC were removed from the dataset. SCTransform was used for normalization and variance stabilization (SCT assay), followed by dimensionality reduction via PCA using the first 30 principal components. UMAPs were computed from these PCs, and clustering was performed using shared nearest neighbor (SNN) graph-based clustering across multiple resolutions, and 0.4 was selected for downstream analyses based on biological interpretability. Cells with expression >0 were classified as positive for each gene. For statistical comparison between conditions, pairwise t-tests with FDR correction were applied to both gene-positive fractions and average expression values, stratified by cluster. Differential expression analysis between conditions was performed using a pseudobulk DESeq2 approach. For each cluster and condition comparison, raw RNA counts were aggregated by sample and filtered to retain genes with at least 10 counts in more than one sample. Only samples with ≥5 cells were included, and comparisons were restricted to condition pairs with at least two biological replicates. DESeq2 was run with fitType=“parametric”, and estimateSizeFactors() was used with type=“poscounts”. All scripts were executed on the UNC-CH’s Longleaf computing cluster, and outputs were organized into directories for reference creation, quality control, clustering, visualization, and differential expression.

Statistics and reproducibility
For pairwise comparisons, unpaired two-tailed t-tests were performed unless otherwise noted. F test was used to compare variances. For unequal variances, Welch’s correction was used on the two-tailed t-test. For multiple comparisons of 3 or more groups, one-way ANOVA test was applied followed by multiple pair-wise comparisons to determine the pair(s) showing significant differences using FDR-adjusted p-values. Experiments were repeated at least twice independently with similar results. All graphical plots and statistical tests were generated using GraphPad Prism 10 unless otherwise noted.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study investigates distinct macrophage populations during the inflammatory response and their significance in muscle repair. To address this, the authors generated a KI irg1:GFP reporter zebrafish line and combined it with nlrc3 deficiency, which is known to promote chronic inflammation. Using RNA-seq analysis, they revealed the dynamic expression of mrc1b across macrophage polarization states and highlighted its importance in muscle repair. The manuscript is well written, the experiments are carefully designed and executed, and most conclusions are supported by the data. However, additional experiments are necessary to further validate the role of the three macrophage populations in tissue repair and the contribution of mrc1b.\n\nMajor Points\n1. Figure 4 and Supplementary Movies 3 & 4:\no The three macrophage subtypes should be quantified. The movies, as presented, do not allow a clear appreciation of the subtypes, and playback speed is too fast. Slower playback and subtype tracking would provide crucial insights.\n2. Figures 5, 6, and Supplementary Figure 13:\no Phagocytosis events are difficult to discern and should be quantified.\no The use of the irg1:GFP KI line to track macrophages may not be appropriate since irg1 expression is altered in nlrc3-deficient larvae. Alternative macrophage markers (mepg1, mfap4) should be employed for proper identification and tracking.\n3. Supplementary Figure 15:\no Bulk RNA-seq on sorted macrophages does not adequately resolve the different populations. Were irg1-low and irg1-high macrophages pooled? How was the purity of sorted populations verified using additional markers (mpeg1, mfap4, mpx, lyz)?\no Validation by RT-qPCR was performed on whole larvae rather than sorted macrophages. For example, mmp9 is predominantly expressed by neutrophils and keratinocytes, which could confound the results. Additionally, as irg1-positive cells were sorted, irg1-positive neutrophils may have contaminated the macrophage population.\no Single-cell RNA-seq would provide a more granular characterization of the three macrophage populations and significantly strengthen the conclusions.\n4. Figure 6:\no Quantification of the three macrophage subtypes and the effect of mrc1b knockdown (KD) is necessary. Additionally, the editing efficiency of mrc1b should be determined and reported.\n\nMinor Points\n1. Figure 1:\no This figure could be moved to the supplementary information section.\n2. Lines 155–171:\no The paragraph needs revision, as certain sentences are repeated.\n3. Figure 4c:\no The graphs are overly complex. Presenting the data as mean ± SEM would enhance clarity.\n4. Figure 3C:\no The term \"asc-/-\" is incorrect. Instead, use “crispant,” “deficient,” or “knockdown” (KD) as appropriate. Furthermore, these results need validation, including asc editing efficiency and/or casp1 activity.\n5. Supplementary Figure 14:\no irf8 deficiency results in macrophage depletion and neutrophilia. Since neutrophils also express irg1, the irg1-positive cells identified in irf8-deficient larvae may include neutrophils. This point requires clarification.\n6. Discussion:\no The advantages of the irg1:GFP KI reporter line over the well-characterized tnfa:GFP reporter line should be discussed. The results suggest that the two reporters yield similar findings, which raises questions about the added value of the irg1:GFP line.", "reviewer_2": "Chronic inflammation or immune disorders that impair tissue regeneration represent a significant clinical challenge, with the underlying mechanisms still not fully understood. Leveraging zebrafish, an excellent model organism for studying tissue regeneration, Spencer et al. employed an irg1/acod1 reporter line to reveal significant heterogeneity in macrophage behavior during muscle regeneration in wild-type zebrafish. Interestingly, they found that in nlrc3l mutants, which the authors previously showed to induce chronic inflammation and macrophage developmental defect, phagocytic and muscle-encasing macrophages were absent. They further suggested that a deficiency in the mannose receptor contributes to macrophage dysfunction under chronic activation. This study provides a unique system for observing the dynamic in vivo behavior of macrophages in tissue regeneration. However, several critical issues must be addressed before the study is suitable for publication in Nature Communications.\n\n1. The nlrc3l mutant is not an ideal model for studying the impact of chronic inflammation on tissue regeneration. As the authors previously demonstrated, it not only exhibits an automatic pro-inflammatory response but also causes defects in macrophage development. This raises the concern that the observed phenotypes are primarily due to developmental abnormalities in macrophages rather than chronic inflammation per se. To increase the generalizability and relevance of their findings, the authors should explore additional chronic inflammation models to demonstrate broader significance beyond the nlrc3l mutant.\n2. Observational data on macrophage behavior require deeper mechanistic insights.\nThe authors employed the irg1 transgenic zebrafish to observe macrophage behavior in vivo during acute muscle injury, confirming that macrophages adopt distinct subtypes during muscle regeneration. While this behavioral data is valuable, it remains largely observational.\nRegarding mechanistic exploration, the study links nlrc3 and myd88 as potential pathways influencing chronic inflammation and muscle regeneration. However, given that myd88 is a well-established master regulator of inflammation/infection, these findings are somewhat predictable. The authors should aim to identify more precise regulatory steps within the nlrc3-myd88 pathway.\nSimilarly, the study attempts to establish CD206 as a critical regulator of macrophages in muscle repair. However, since tissue repair involves extensive cell death and macrophage phagocytosis, it is expected that CD206, a key marker of phagocytosis, would be upregulated. A more in-depth investigation is needed to uncover why certain macrophage subtypes (subtypes 2 and 3, specifically those capable of phagocytosis) are absent in chronic inflammation. Sorting and analyzing these subtypes individually, or employing single-cell sequencing to identify differential pathways, followed by functional validation, could provide meaningful insights. The current comparison of injured versus uninjured macrophages is too simplistic to pinpoint these critical pathways.\n3. The authors state: \"In nlrc3l mutants, restoring macrophage nlrc3l expression, deleting myd88, or both reversed the inappropriate macrophage activation, as evidenced by irg1 and tnfa downregulation, with the combination fully restoring a normal macrophage state (Fig. 3 and Supplementary Figs. 4, 6). These results implicate both cell-autonomous and non-cell-autonomous mechanisms in the inappropriate immune activation.\"\nHowever, the manuscript does not provide direct evidence for the involvement of non-cell-autonomous mechanisms. The authors need to clarify or provide experimental data to support this conclusion.\n4. The data on irf8 mutants following tissue regeneration does not offer significant insights. Any mutation affecting macrophage function or development would be expected to exhibit tissue regeneration defects. Further exploration is necessary to demonstrate the unique relevance of irf8 in this context.", "reviewer_3": "Spencer et al. first produced ifg1/acod1-KI zebrafish for tracing activated macrophages. They compared the KI zebrafish with existing models and KO lines and demonstrated the effective and non-functional impairment of the newly established line. Using this line, next, the authors investigated the properties of activated macrophages in a chronic inflammatory state induced by the loss of nlrc3, which could be suppressed by the loss of Myod88 and the restoration of nlrc3 expression. Furthermore, using a muscle regeneration model, the authors verified the regeneration process including macrophage dynamics under control and nlrc3-deficient conditions, and demonstrated that regeneration does not occur when activated macrophages continue to exist, as evidenced by rescue experiments. Finally, the authors focused on the decreased expression of CD206 in the chronically activated macrophages and concluded that CD206 deficiency causes muscle regeneration failure and that CD206 in macrophages is responsible for regeneration failure under persistent inflammation. Overall, the experiments are well-conducted, and the data are convincing. However, this reviewer has some concerns about the model and results of CD206-KD. In particular, it is questionable whether the conceptual advance of this study meets the criteria of Nature Communications.\n\nMajor comments\n1) The chronic model used here is an artificial model. It is unclear whether this model is applied to naturally occurring disease models. Based on the results found in this study, is it possible to verify the efficacy of the treatment by targeting a conceptually new molecule or pathway?\n2) Given the role of CD206 in macrophage-mediated phagocytosis, it is unsurprising that CD206 knockdown (CD206-KD) results in impaired muscle regeneration. However, the relationship between CD206-KD and MyD88-null experiments remains unclear. Does the loss of MyD88 in NLRC3-null conditions restore CD206 expression? If so, how is CD206 expression regulated under chronic conditions?\n3) Lines 65-66；dynamic in vivo and longitudinal analyses of cellular interactions across distinct phases of the injury and repair process are lacking\nSome studies conducted dynamic and longitudinal analyses using scRNA-seq. For instance, the following studies conducted dynamic, longitudinal, interactome analyses using scRNA-seq during muscle regeneration in detail. This reviewer recommends citing these papers and re-rewrite more precisely.\niScience. 2020 Apr 24;23(4):100993. doi: 10.1016/j.isci.2020.100993.\nCell Rep. 2020 Mar 10;30(10):3583-3595.e5. doi: 10.1016/j.celrep.2020.02.067.\n4) Lines 204; It is difficult to find Mrc1b/cd206 in the figure.\n5) Line 244 ;\nWhat is ASC? Please add a description of the relationship between ASC and nlrc3l.\n6) Lines 451-452; The precise role of macrophages in skeletal muscle injury and repair remains incompletely understood.\nPlease describe what the precise role is not understood. In addition, the authors need to underscore what the present study reveals in the role of macrophages in muscle regeneration. This reviewer thinks that mechanisms inducing chronic inflammatory conditions in muscle regeneration are unexplored. However, the disruption of muscle regeneration by chronic inflammation is not conceptually new.\n7)Lines 358-361, 461\nThe authors described that chronically activated macrophages inhibit satellite cell activation. There is no evidence that chronic macrophages directly inhibit satellite cell activation. Is it possible that chronically activated macrophages inhibit not the activation, but the proliferation? And is it possible that the chronic macrophages disrupt the balance of pro-inflammatory macrophages inducing satellite cell activation or proliferation?"}, "author_response": "Point-by-point response to the reviewers’ comments is shown in italicized text.\nReviewer #1 (Remarks to the Author):\nThis study investigates distinct macrophage populations during the inflammatory response\nand their significance in muscle repair. To address this, the authors generated a KI irg1:GFP\nreporter zebrafish line and combined it with nlrc3 deficiency, which is known to promote\nchronic inflammation. Using RNA-seq analysis, they revealed the dynamic expression of mrc1b\nacross macrophage polarization states and highlighted its importance in muscle repair. The\nmanuscript is well written, the experiments are carefully designed and executed, and most\nconclusions are supported by the data. However, additional experiments are necessary to\nfurther validate the role of the three macrophage populations in tissue repair and the\ncontribution of mrc1b.\nMajor Points\n1. Figure 4 and Supplementary Movies 3 & 4:\no The three macrophage subtypes should be quantified. The movies, as presented, do not\nallow a clear appreciation of the subtypes, and playback speed is too fast. Slower playback and\nsubtype tracking would provide crucial insights.\nThank you for your helpful feedback. In response, we have added new Supplementary Movie files\ncorresponding to the original Movies 3 and 4, now renamed Supplementary Movies 3 and 5 (timelapse\nimaging of control sibling and mutant, respectively). These are accompanied by Supplementary\nMovies 4 and 6, which show 3D renderings of the same datasets with macrophage subtypes\nannotated and presented at slower playback speed to highlight cell behavioral and morphological\nfeatures for quantitative analyses.\nSupporting the additional movie files (Supplementary Movies 4 and 6), we have included new\nquantitative analyses characterizing the three macrophage subtypes during the initial injury response\nat 24 hpa, now presented in Figure 4f. Examples of individual macrophages from each subtype are\nalso shown in Figure 4g, using Imaris to digitally isolate fluorescent data to show individually rendered\nmacrophage cellular outlines for each subtype.\nWe define the three subtypes—subtype 1 (“mobile”), subtype 2 (“cluster”), and subtype 3\n(“encasing”)—based on distinct behavioral and morphological features:\n-Subtype 1 (mobile): Highly motile cells, with increased speed and distance traveled (Fig. 4f).\n-Subtype 2 (cluster): Characterized by increased vesicular content, with a higher phagocytic index\n(cell-to-cytosol volume ratio), indicating large intracellular vesicles such as phagosomes or endosomes\n(Fig. 4f).\n-Subtype 3 (encasing): Largely stationary cells with elongated, columnar morphology. These cells\nencircle myocytes and adopt a muscle-cell-like shape, showing the largest cell volume and greater\noverall sphericity, particularly evident in the lowest 10th percentile of the population distribution (Fig.\n4f–g, Supplementary Fig. 12).\nOur data also show that mutants lack subtypes 2 and 3, highlighting subtype-specific alterations in\nmacrophage behavior. Relevant text describing these subtypes and their associated quantifications\nhas been added to the Results section and to Figure 4 legend.\n2. Figures 5, 6, and Supplementary Figure 13:\no Phagocytosis events are difficult to discern and should be quantified.\nWe have renamed subtype 2 as “clustering” to better reflect its defining characteristic, namely the\ntendency of these macrophages to coalesce and adopt a rounded morphology with visibly increased\nvesicular content. To support this, we now include a phagocytic index quantification based on\nmorphological features, specifically the ratio of total cellular to cytosolic volume, which is indicative of\nvesicular content and thereby phagocytic activity.\nOur analysis shows that subtype 2 cells exhibit more than double the phagocytic index compared to\nthe other macrophage subtypes, suggesting that they contain, on average, more than twice the\nvesicular volume (Fig. 4f).\nPlease note that the previous Supplementary Fig. 13 is now Supplementary Fig. 12.\no The use of the irg1:GFP KI line to track macrophages may not be appropriate since irg1\nexpression is altered in nlrc3-deficient larvae. Alternative macrophage markers (mpeg1, mfap4)\nshould be employed for proper identification and tracking.\nThank you for this insightful question. We agree that validating the irg1-KI:GFP reporter is important.\nTo address this, we performed dual labeling with the established mpeg1:BFP line wherever possible.\nOur results demonstrate that irg1-KI:GFP reliably marks macrophages with high specificity and\nintensity, including after tail-cut injury.\nAt baseline, irg1-KI:GFP fully overlaps with mpeg1:BFP in macrophages (Fig. 3, Supp. Figs. 3, 8),\nconfirming its specificity. After injury, all cells clustering or encasing muscle at the wound site remain\nmpeg1+ (Fig. 4b, Supp. Fig. 13), indicating that irg1-KI:GFP continues to label macrophages\nspecifically. Although a small number of neutrophils show weak knock-in reporter expression post-\ninjury (7.6% in controls, 10.7% in mutants; none in controls or 4.3% in mutants at baseline), these cells\nare rare and express significantly lower GFP levels than macrophages. We now include quantitative\nthresholds (Supp. Fig. 11b; 10 A.U. detection, 30 A.U. bright GFP) showing that macrophages\nconsistently exhibit strong expression, while neutrophils rarely reach the bright threshold.\nThis is further substantiated by our single-cell RNA-seq data: while a portion of the irg1-KI:GFP+ cells\nsequenced were neutrophils, more prevalent in nlrc3l mutants, the levels of GFP expression in the\nneutrophil clusters (clusters 4/11/12) were significantly lower than the macrophage clusters (Supp. Fig.\n18d). Moreover, quantification of the eGFP transcripts in the sequenced cells clearly show a large\ndifference where neutrophils range from 0 to less than 30 normalized counts per sample while\nmacrophages range is at least 10 to 100 times more counts at 420 to 2,700 in activated macrophages\n(Supp. Fig. 19h). We now include this analysis and quantification in the manuscript to highlight the\nlarge expression gap.\nImportantly, while mpeg1:BFP served as a valuable control, its very low fluorescence precluded use in\nlive animal sorting on a fluorescent stereoscope and cell sorting. The irg1-KI:GFP reporter was\ntherefore indispensable for identifying live nlrc3l mutants without requiring post-fix genotyping, thereby\nenabling the core time course and live-cell experiments presented in this study.\nIn summary, although low-level knock-in reporter expression can occur in a small number of\nneutrophils under specific conditions such as inflammation or injury, irg1-KI:GFP remains a robust tool\nfor tracking macrophages—both at baseline, when neutrophils do not express the reporter, and upon\nactivation, when macrophages express the reporter at high intensity and in much greater abundance\nthan neutrophils. The reporter makes macrophages readily distinguishable even under perturbation\nand has been essential for the experiments in this study.\n3. Supplementary Figure 15:\no Bulk RNA-seq on sorted macrophages does not adequately resolve the different populations.\nWere irg1-low and irg1-high macrophages pooled? How was the purity of sorted populations\nverified using additional markers (mpeg1, mfap4, mpx, lyz)?\nWe thank the reviewer for raising this important point. The goal of our bulk RNA-seq was to\ncharacterize cells expressing irg1-KI:GFP at baseline. For cell sorting, we used stringent GFP gating\nto distinguish “high” vs. “low” GFP-expressing populations, based on thresholds set using non-\ntransgenic negative controls (see Supplementary Fig. 21). Specifically, irg1-high cells (found only in\nmutants) exhibited GFP levels exceeding those of controls, while irg1-low cells (present in both\ngroups) had lower GFP intensity. FACS was performed under high-purity settings with low event rates\nto ensure collection accuracy.\nTo further validate and resolve the identity of these populations, we have now included single-cell\nRNA-seq analyses (Figs. 7, 8 and Supplementary Figs. 18-20). These data show that irg1-high cells\nconsistently represent macrophage cell identities, while irg1-low cells include a minority neutrophil cell\npopulation—primarily in mutant animals—alongside macrophage cells. This aligns with the bulk RNA-\nseq data, where irg1-high cells exclusively expressed macrophage markers, and irg1-low cells from\nmutants expressed both macrophage and neutrophil markers (Fig. 2).\nTogether, the combination of stringent FACS gating and new single-cell analysis provides a clear\nresolution of cell identities and supports the specificity of our macrophage-related conclusions.\no Validation by RT-qPCR was performed on whole larvae rather than sorted macrophages.\nFor example, mmp9 is predominantly expressed by neutrophils and keratinocytes, which could\nconfound the results. Additionally, as irg1-positive cells were sorted, irg1-positive neutrophils\nmay have contaminated the macrophage population.\nSingle-cell RNA-seq would provide a more granular characterization of the three macrophage\npopulations and significantly strengthen the conclusions.\nWe agree with the reviewer that single-cell analysis would help clarify the complexity of the\nmacrophage populations and distinguish the transcriptome changes between macrophages and\nneutrophils. As discussed, we have now performed scRNA-seq, which provides the necessary clarity\nbetween macrophages and neutrophils, and further characterization of macrophage subsets. These\nnew data, presented in Figs. 7, 8 and Supplementary Figs. 18 and 19, reveal macrophage–specific\nresponses to acute tail-cut injury, as well as mutation-induced alterations driven by chronic\ninflammation.\nImportantly, the single-cell analysis conveys differences in the macrophage population during an injury\nresponse, including hybrid states in the initial inflammatory phase at 24 hpa, marked by co-expression\nof M1 and M2 markers in individual macrophages in controls and nlrc3l mutants, albeit even more\npronounced in mutants (Fig. 8 and Supplementary Fig. 19e). Moreover, we observe a significant loss\nof subtypes 2 and 3 corresponding to repair-associated macrophages expressing ctsk/fabp4 and\ntgfbi/sb:cb81 (or ZFP36L1-like), respectively, in nlrc3l mutants.\nTo isolate macrophage-specific profiles, we used scRNA-seq data to subcluster macrophage-identity\ncells to analyze only the cells making up the macrophages (clusters 0-9, except 4), excluding\nneutrophil populations (clusters 4, 11, and 12), which is particularly important for genes like mmp9,\nwhich are expressed in neutrophils (Supplementary Fig. 18e). The macrophage-specific scRNA-seq\nanalysis revealed and confirmed significant mmp9 upregulation at 24 hpa in both control and mutant\nmacrophages post-injury, with the highest expression in mutant macrophages, while mmp9 expression\nremained low or undetectable in macrophages at baseline and resolution (Fig. 7l, Supplementary Figs.\n18e and 19g).\nThese findings not only validate but also extend our bulk RNA-seq findings, offering high-resolution\ninsight into both cell identity and the functional consequences of chronic inflammation on macrophage\nheterogeneity, which is clearly diminished in the chronically activated nlrc3l mutants.\n4. Figure 6:\no Quantification of the three macrophage subtypes and the effect of mrc1b knockdown (KD) is\nnecessary. Additionally, the editing efficiency of mrc1b should be determined and reported.\nWe agree and appreciate the reviewer’s suggestion and have now addressed this by presenting data\nin Supplementary Fig. 16 demonstrating the efficiency of mrc1b editing using T7 endonuclease assay\nand DNA sequencing on embryos injected with Cas9 mRNA with mrc1b-targeting gRNAs (#4 and #31)\ncompared with universal gRNA/Cas9 injected negative controls in Supplementary Fig. 16. T7 assay\nshows ~96% CRISPR efficiency, with Sanger sequencing confirming mrc1b-targeting induced indels\ncausing frameshifts and premature stops. Additionally, sequencing mrc1b- targeted embryos suggests\nCRISPR often mutates only one allele, resulting in heterozygous, non-deleterious outcomes, which is\nconsistent with the partial phenotypes observed (Fig. 6).\nFurthermore, we analyzed the macrophage subtypes at 24 hpa in mrc1b knockdown animals that\nindicated a similar trend of reduction, although not statistically significant, in subtypes 2 (clustering)\nand 3 (muscle-encasing) with those observed in nlrc3l mutants with chronic inflammation\n(Supplementary Fig. 16d), supporting the involvement of mrc1b in driving the observed mutant\nphenotype. Due to the variable degree of gene knockdown from transient CRISPR, we decided to\ninject CRISPR reagents into zebrafish that were heterozygous for a stable mrc1b knockout to increase\nthe rate of gene knockdown. Separating the heterozygous fish from sibling WT showed a more clear\ntrend of reduction particularly in the muscle-encasing macrophage subpopulation (Supplementary Fig.\n16d).\nIn addition, to strengthen the function of mrc1b in acute muscle injury repair, we obtained a putative\nmrc1b knockout allele (sa18640) from ZIRC, derived from a large-scale mutagenesis in the UK Sanger\nCenter Zebrafish Project. We confirmed the sa18640 mutation by sequencing and demonstrated\nMendelian segregation in progeny. This mutation introduces a G>T point substitution resulting in a\npremature stop codon in mrc1b. To our knowledge, this novel allele has not been previously validated\nor reported in any study. Data verifying the mutation and its associated phenotype are also included in\nthe newly added Supplementary Fig. 16 and Fig. 6g, respectively. As generating new transgenic\nsa18640 mutant zebrafish would require several additional months—beyond the scope of this study—\nwe focused on using this mutation for muscle actin staining to assess injury repair following sa18640\ndeletion rather than also macrophage subtyping. These results were consistent to that found in mrc1b\nknockdown animals by CRISPR.\nMinor Points\n1. Figure 1:\no This figure could be moved to the supplementary information section.\nThank you for your comment. We chose to include this figure in the main manuscript to highlight the\nreporter system, which was technically challenging to generate and had a low success rate. We\nbelieve its inclusion is important to emphasize the novelty and technical significance of this tool, which\nunderpins several key findings in the study. That said, if space constraints are a concern, we are open\nto streamlining the figure and relocating detailed components to the supplementary section while\nretaining a simplified version in the main text for clarity and emphasis.\n2. Lines 155–171:\no The paragraph needs revision, as certain sentences are repeated.\nThis paragraph describes the rationale and the results of the experiments comparing transposon\nversus knock-in based GFP reporters for irg1. We have refined and shortened the text.\n3. Figure 4c:\no The graphs are overly complex. Presenting the data as mean ± SEM would enhance clarity.\nWe appreciate the suggestion regarding the plot format. Because this was a longitudinal study\ncarefully designed and tediously conducted to track macrophage cell dynamics in the same individual\nanimals over multiple timepoints, this plot was chosen to preserve that continuity. A bar graph, for\nexample, would not effectively convey the temporal progression of an individual, or the variation\nbetween individual animals. To present the data comprehensively, we have made each line in the plot\nrepresent the measurement of a specific parameter (y-axis) per timepoint for a single animal, allowing\nvisualization of within-subject changes.\nTo improve visualization of the plots for clarity, we have revised the graphs to show bolder black and\nred lines to indicate the group means for control and mutant animals, respectively, with shaded areas\nrepresenting the standard error of means (SEM), which we hope helps with enhancing clarity.\n4. Figure 3C:\no The term \"asc-/-\" is incorrect. Instead, use “crispant,” “deficient,” or “knockdown” (KD) as\nappropriate. Furthermore, these results need validation, including asc editing efficiency and/or\ncasp1 activity.\nWe are using a stable knockout of asc that we generated using CRISPR, and the mutant line has been\nstably maintained for several generations as allele bcz82 (also known as nc303cs); so the denotation\nof “asc -/-“ is correct. Thank you for pointing out the unintended omission of the supporting data in the\ninitial manuscript version; we have now provided Sanger sequencing validation of the missense\nmutation due to a 4-bp deletion in the asc (or pycard) coding region in Supplementary Fig. 7a.\nMutants segregate according to Mendelian ratios from a heterozygous incross, and genotyping using\nthe primers in the Resources Table has provided a reliable method to identify the genotypes for this\nasc mutant bcz82 allele.\n5. Supplementary Figure 14:\no irf8 deficiency results in macrophage depletion and neutrophilia. Since neutrophils also\nexpress irg1, the irg1-positive cells identified in irf8-deficient larvae may include neutrophils.\nThis point requires clarification.\nThere was an error in the original figure legend, which incorrectly stated that macrophages were\nlabeled using the irg1-KI:GFP reporter. We have corrected the figure and legend to reflect that, in the\ninjury experiments, both mutant and sibling fish carried the macrophage-specific mpeg1:GFP reporter.\nImportantly, the irf8 mutant fish were available only with the mpeg1:GFP reporter background.\n6. Discussion:\no The advantages of the irg1:GFP KI reporter line over the well-characterized tnfa:GFP reporter\nline should be discussed. The results suggest that the two reporters yield similar findings, which\nraises questions about the added value of the irg1:GFP line.\nWe appreciate the opportunity to clarify the unique value of the irg1-KI:GFP reporter line in\ncomparison to the existing tnfa:GFP reporter.\nWe have added to Discussion the following text to address the raised question:\n“While existing reporters like tnfa:GFP label macrophage activation, they reflect distinct pathways.\ntnfa, encoding a pro-inflammatory cytokine, marks inflammatory signaling, while irg1, a mitochondrial\nenzyme, tracks metabolic reprogramming. Both show partial overlap during peak inflammation (~24\nhpa; Fig. 7j, Supplementary Fig. 17), but irg1 expression persists into resolution, indicating broader,\nsustained activation. scRNA-seq data support this, showing irg1 is more broadly expressed post-injury\nthan tnfa (Fig. 7, Supplementary Fig. 17). irg1-KI:GFP, generated via targeted knock-in, ensures\nconsistent, quantifiable expression across animals. In contrast, expression of tnfa:GFP, inserted via\ntransposon, varies with copy number and integration site. tnfa:GFP also shows expression in non-\nimmune cells, including CNS and PNS neurons (Smith et al., 2017 Plos Genetics PMC5397050;\nSupplementary Figs. 4, 9), complicating immune-specific analysis, such as by FACS and\ntranscriptomics. irg1-KI:GFP, by contrast, is predominantly macrophage-specific, where its\nupregulation marks a shift in activation state without detectable expression in non-immune cells. Thus,\nirg1-KI:GFP offers a stable, specific, and quantitative in vivo tool for tracking immune activation and\nmetabolic state unmatched by existing reporters.”\nUltimately, irg1-KI:GFP fills a critical gap in the current toolkit: it is the first immune reporter line that\nfaithfully tracks irg1 transcription, a marker of metabolic activation, in a quantitative, genetically\nprecise, and immune cell-type manner. This makes it an unmatched tool for dissecting immune cell\nstates, particularly macrophage and neutrophil biology, in vivo.\nReviewer #2 (Remarks to the Author):\nChronic inflammation or immune disorders that impair tissue regeneration represent a\nsignificant clinical challenge, with the underlying mechanisms still not fully understood.\nLeveraging zebrafish, an excellent model organism for studying tissue regeneration, Spencer\net al. employed an irg1/acod1 reporter line to reveal significant heterogeneity in macrophage\nbehavior during muscle regeneration in wild-type zebrafish. Interestingly, they found that in\nnlrc3l mutants, which the authors previously showed to induce chronic inflammation and\nmacrophage developmental defect, phagocytic and muscle-encasing macrophages were\nabsent. They further suggested that a deficiency in the mannose receptor contributes to\nmacrophage dysfunction under chronic activation. This study provides a unique system for\nobserving the dynamic in vivo behavior of macrophages in tissue regeneration. However,\nseveral critical issues must be addressed before the study is suitable for publication in Nature\nCommunications.\n1. The nlrc3l mutant is not an ideal model for studying the impact of chronic inflammation on\ntissue regeneration. As the authors previously demonstrated, it not only exhibits an automatic\npro-inflammatory response but also causes defects in macrophage development. This raises\nthe concern that the observed phenotypes are primarily due to developmental abnormalities in\nmacrophages rather than chronic inflammation per se. To increase the generalizability and\nrelevance of their findings, the authors should explore additional chronic inflammation models\nto demonstrate broader significance beyond the nlrc3l mutant.\nThe reviewer raises a valid point that warrants clarification of our previous studies. In the original\npublication (Shiau et al., 2013, Cell Reports), the novel nlrc3l mutation was uncovered from a forward\ngenetic screen in zebrafish led by the senior author of the current manuscript (Shiau). That study\nrevealed the unexpected finding that macrophages failed to form microglia, because they did not\nmigrate into the brain rather than having developmental defects (such as lack of maturation). This was\nattributed to inappropriate inflammatory activation of macrophages that diverted their normal migration:\nthe macrophages behaved as if responding to an active infection, despite the absence of any immune\nchallenge. The molecular mechanisms underlying this aberrant activation remained unknown at the\ntime.\nOur current study, along with recent work (Kwon et al., 2022, Communications Biology), builds on this\nfoundation by showing that macrophages in nlrc3l mutants are functional and capable of responding to\ninfection. However, they are constitutively activated at baseline, expressing pro-inflammatory\ncytokines and irg1/acod1. We therefore consider the nlrc3l mutant zebrafish a uniquely valuable\ngenetic model to study inappropriate macrophages activation, providing a consistent and genetically\ncontrolled system for chronic inflammatory activation.\nNonetheless, we agree that including an independent model strengthens the generality of our findings.\nWe therefore developed an infection-based chronic inflammation model to examine how persistent\nmacrophages activation affects acute muscle injury repair. Using a commonly employed E. coli lab\nstrain (MG1655), we microinjected a high dose of bacteria into the brain ventricle of early embryos\nprior to injury and monitored both injury response and macrophages activation over time. We\nconfirmed that our paradigm induced robust, systemic, and enduring macrophage activation (new data\npresented in Supplementary Fig. 17). Using this new model, we found that the muscle repair defects\nclosely resemble those seen in nlrc3l mutants. Furthermore, these defects were associated with the\nloss of the two key macrophages subtypes (clustering and muscle-encasing) and downregulation of\nmacrophage mrc1b expression, all reminiscent of nlrc3l mutants (Supplementary Fig. 17).\nWe have added this new data in Supplementary Fig. 17 and the following text to the Results section:\n“To further explore the generalizability to additional paradigms of chronic macrophage activation, we\ndeveloped a model based on persistent systemic E. coli infection (Supplementary Fig. 17a-c), and\nshowed that similar to nlrc3l mutants, the chronic macrophage activation caused by infection disrupted\nnormal skeletal muscle repair (Supplementary Fig. 17d-e), and was associated with a mrc1b\ndownregulation and reduction of both clustering and encasing macrophage subtypes (Supplementary\nFig. 17f-i).”\n2. Observational data on macrophage behavior require deeper mechanistic insights.\nThe authors employed the irg1 transgenic zebrafish to observe macrophage behavior in vivo\nduring acute muscle injury, confirming that macrophages adopt distinct subtypes during\nmuscle regeneration. While this behavioral data is valuable, it remains largely observational.\nRegarding mechanistic exploration, the study links nlrc3 and myd88 as potential pathways\ninfluencing chronic inflammation and muscle regeneration. However, given that myd88 is a\nwell-established master regulator of inflammation/infection, these findings are somewhat\npredictable. The authors should aim to identify more precise regulatory steps within the nlrc3-\nmyd88 pathway.\nWe appreciate the reviewer’s comment regarding the perceived predictability and novelty of the\ngenetic interaction between nlrc3l and myd88. However, we respectfully disagree that this interaction\nis expected or well-established. While zebrafish nlrc3l shares some similarity with mammalian NOD-\nlike receptors (e.g., NLRC3), it lacks the canonical leucine-rich repeat (LRR) domain that define this\nfamily, and as described in Shiau et al., 2013, it represents a non-canonical and teleost-specific NLR\nreceptor without a clear mammalian NLR ortholog. Thus, its mechanism of action in vivo has remained\nundefined.\nPrevious in vitro studies suggested a potential link to inflammasome signaling via ASC (pycard), based\non in vitro binding assays (Shiau et al., 2013), but without in vivo validation. Our current study through\ngenetic experiments demonstrate that asc deletion does not modify nlrc3l mutant phenotypes (Fig. 3).\nIn contrast, deletion of myd88 consistently rescues key chronic macrophage activation phenotypes in\nnlrc3l mutants (Fig. 3 and 6), establishing a specific and functionally relevant genetic interaction. This\nis further supported by transcriptomic data (bulk and single-cell RNA-seq), which show that myd88-\nand NF-kB-associated pathways are significantly dysregulated in nlrc3l mutant macrophages (Fig. 2, 7\nand Supplementary Figure 19).\nImportantly, the identification of nlrc3l-myd88 connection was the result of testing several other\ncandidate genes and pathways—experiments not shown here—but found that none modified nlrc3l\nmutant phenotypes, highlighting the specificity and uniqueness of the nlrc3l–myd88 interaction.\nMoreover, discovering this link was not only mechanistically informative but also critical to our overall\nstudy: it provided a genetic lever to reverse the chronic immune activation in nlrc3l mutants, thereby\nenabling us to assess how chronic immune dysregulation impairs tissue repair. While the mechanistic\ndetails of nlrc3l-myd88 signaling would be interesting, dissecting this pathway in depth lies beyond the\nscope of the present study, which focuses on how chronic macrophage activation, rather than nlrc3l\nitself, affects muscle injury repair. We believe the discovery of the nlrc3l-myd88 connection is both\nnovel and foundational, and merits future study in its own right.\nSimilarly, the study attempts to establish CD206 as a critical regulator of macrophages in\nmuscle repair. However, since tissue repair involves extensive cell death and macrophage\nphagocytosis, it is expected that CD206, a key marker of phagocytosis, would be upregulated.\nA more in-depth investigation is needed to uncover why certain macrophage subtypes\n(subtypes 2 and 3, specifically those capable of phagocytosis) are absent in chronic\ninflammation. Sorting and analyzing these subtypes individually, or employing single-cell\nsequencing to identify differential pathways, followed by functional validation, could provide\nmeaningful insights. The current comparison of injured versus uninjured macrophages is too\nsimplistic to pinpoint these critical pathways.\nThank you for your insightful comments. While the Mrc1/CD206 may be expected to influence\nphagocytosis, its specific role in macrophage-mediated skeletal muscle repair has not been\nestablished. A key finding of this study is the differential role of the Mrc1/CD206, particularly the\ndownregulation of mrc1b, in chronically activated macrophages, a novel insight that may explain\npreviously unrecognized deficiencies in macrophage function under chronic inflammation. Our data\nsuggest that mrc1b downregulation contributes to the loss of pro-repair macrophage subtypes 2 and 3\nin nlrc3l mutants. Notably, single-cell transcriptomic analysis across injury timepoints shows that\nmrc1b dynamically marks macrophage states, with unexpectedly high expression at baseline rather\nthan during peak phagocytic activity, highlighting how its in vivo role remains poorly understood.\nFurthermore, we agree that a more in-depth investigation would be important to further distinguish the\nmacrophage subtypes during muscle repair. To address this, we performed a large single-cell RNA-\nseq experiment using our irg1-KI:GFP reporter line. We profiled macrophages and all irg1-expressing\ncells at 24 hours post-injury (hpa), 48 hpa, and in uninjured controls, using large numbers of zebrafish\nembryos (two independent samples per condition, 90 animals each). As shown in the newly added\ndata in Figs. 7, 8 and Supplementary Figs. 18, 19, 20, the vast majority of the cells were macrophages\nwith some neutrophil presence, from which we attempted to molecularly define the two pro-repair\nmacrophage subtypes.\nWe summarize here the main points of the text we added to the Results and Discussion in relation to\nour scRNA-seq data. Clustering subtype 2, enriched in both 24 and 48 hpa controls, expressed mrc1b\nand showed upregulation of cholesterol efflux (fabp4a, apoeb, apoc1) and phagocytosis-related genes\n(mertka, npc2.1, npc2.2, ctsk, ctsl.1, ifi30a). Muscle-encasing subtype 3, observed only at 24 hpa, also\nexpressed mrc1b and had significantly elevated expressions of genes involved in TGF-β signaling\n(tgfbr1a, tgfbi, tgfbrap1). In nlrc3l mutants, chronic macrophage activation reduced cellular\nheterogeneity, with macrophages clustering in a restricted region of UMAP space corresponding to\nmacrophages. These mutant cells shared core pro-inflammatory signatures but still expressed some\npro-repair genes, including markers of subtypes 2 and 3, but uniformly downregulating mrc1b. This\nresulted in hybrid M1/M2 states, co-expressing inflammatory and repair-associated markers, which\nwere infrequent in controls (<10% at 24 hpa) but dominated in mutants (up to 50%). These findings\nsuggest that chronic activation impairs repair not by enhancing inflammatory function, but by disrupting\nreparative programs, particularly through mrc1b downregulation and loss of key reparative\nmacrophage subtypes. Chronic persistence of the pro-inflammatory program appears to ultimately\nconstrain macrophage plasticity despite partial expression of repair pathways that we found to involve\ncholesterol processing, phagocytosis, and TGF-β signaling.\nMoreover, our scRNA-seq data uncovered cathepsin K (ctsk), a cysteine protease, as a marker of\nreparative macrophage subtype 2 (Figs. 7, 8). In vivo validation showed that cathepsin K protein\naccumulates in the cytosol not only in clustering (subtype 2) but also muscle-encasing (subtype 3)\nmacrophages post-injury, suggesting intracellular collagen and protein degradation as a critical function\nfor a subpopulation of both reparative subtypes (Fig. 8). These densely packed cathepsin K⁺\ncompartments are absent in chronically activated nlr3l mutant macrophages, which show\nreduced ctsk expression at both transcript and protein levels. Notably, cathepsin K⁺ cells co-express\ntnfa, supporting a hybrid inflammatory-reparative M1/M2 state. This identifies CTSK protein\naccumulation as a new functional marker of reparative macrophage identity and further clarifies how\nchronic inflammation disrupts macrophage function.\n3. The authors state: \"In nlrc3l mutants, restoring macrophage nlrc3l expression, deleting\nmyd88, or both reversed the inappropriate macrophage activation, as evidenced by irg1 and\ntnfa downregulation, with the combination fully restoring a normal macrophage state (Fig. 3\nand Supplementary Figs. 4, 6). These results implicate both cell-autonomous and non-cell-\nautonomous mechanisms in the inappropriate immune activation.\"\nHowever, the manuscript does not provide direct evidence for the involvement of non-cell-\nautonomous mechanisms. The authors need to clarify or provide experimental data to support\nthis conclusion.\nWe thank the reviewer for pointing out the confusion caused by the original placement of this\nstatement. The sentence, “These results implicate both cell-autonomous and non-cell-autonomous\nmechanisms…” was previously included before presenting the germ-free data, which led to ambiguity.\nTo address this, we have moved the statement to the end of the section, after presenting the data\nshowing that commensal microbes contribute to inappropriate immune activation—evidenced by\nreduced irg1 expression in germ-free nlrc3l mutants compared to conventionally raised nlrc3l mutants.\nThe data supporting the non-cell-autonomous role of commensal microbes in aberrant macrophage\nactivation are presented in Supplementary Fig. 7.\nThe revised text in the Results section now reads: “Given that MyD88 mediates TLR signaling\nresponsible for bacterial recognition and response35, we evaluated macrophage activation in nlrc3l\nmutants under germ-free versus conventionally raised conditions (Supplementary Fig. 7). Our findings\nshowed that while commensal microbes contributed, nlrc3l mutant macrophages themselves retained\nsubstantial intrinsic activation (Fig. 3 and Supplementary Fig. 7). Consistent with this, full rescue of\ninappropriate macrophage activation in nlrc3l mutants required both macrophage rescue and myd88\ndeletion, as neither intervention alone was sufficient (Fig. 6). This indicates contributions from both\ncell-intrinsic defects and likely non-cell-autonomous signals, supported by the need to delete myd88, a\ngene mediating TLR signaling. Taken together, these findings highlight the intricate nature of the\ninappropriate macrophage activation in nlrc3l mutants, where MyD88-dependent signaling, microbial\ncues, and internal cellular dysregulation collectively contribute to their chronic inflammatory activation\nstate, in addition to the altered state of neutrophils. These results implicate both cell-autonomous and\nnon-cell-autonomous mechanisms in the inappropriate immune activation.”\n4. The data on irf8 mutants following tissue regeneration does not offer significant insights.\nAny mutation affecting macrophage function or development would be expected to exhibit\ntissue regeneration defects. Further exploration is necessary to demonstrate the unique\nrelevance of irf8 in this context.\nWe thank the reviewer for this comment. We agree that this is important to clarify. Since the role of\nmacrophages in skeletal muscle repair has not been definitively established in zebrafish, the animal\nmodel used in our study, it was essential for us to openly and rigorously investigate their involvement.\nThis allowed us not only to validate whether macrophages contribute to the repair process in this\nspecies, but also to directly compare the response and repair outcomes between macrophage-\ndeficient irf8 mutants and that observed in our genetic nlrc3l mutant model for chronic inflammation.\nReviewer #3 (Remarks to the Author):\nSpencer et al. first produced ifg1/acod1-KI zebrafish for tracing activated macrophages. They\ncompared the KI zebrafish with existing models and KO lines and demonstrated the effective\nand non-functional impairment of the newly established line. Using this line, next, the authors\ninvestigated the properties of activated macrophages in a chronic inflammatory state induced\nby the loss of nlrc3, which could be suppressed by the loss of Myod88 and the restoration of\nnlrc3 expression. Furthermore, using a muscle regeneration model, the authors verified the\nregeneration process including macrophage dynamics under control and nlrc3-deficient\nconditions, and demonstrated that regeneration does not occur when activated macrophages\ncontinue to exist, as evidenced by rescue experiments. Finally, the authors focused on the\ndecreased expression of CD206 in the chronically activated macrophages and concluded that\nCD206 deficiency causes muscle regeneration failure and that CD206 in macrophages is\nresponsible for regeneration failure under persistent inflammation. Overall, the experiments are\nwell-conducted, and the data are convincing. However, this reviewer has some concerns about\nthe model and results of CD206-KD. In particular, it is questionable whether the conceptual\nadvance of this study meets the criteria of Nature Communications.\nMajor comments\n1) The chronic model used here is an artificial model. It is unclear whether this model is applied\nto naturally occurring disease models. Based on the results found in this study, is it possible\nto verify the efficacy of the treatment by targeting a conceptually new molecule or pathway?\nOur current experimental paradigm represents a conceptually novel approach by targeting a novel\nNOD-like receptor, nlrc3l-like, in zebrafish to induce a consistent, highly reproducible, and broad-\nbased inflammatory activation of macrophages. This strategy allows us to study the systemic impact of\nchronic inflammation on acute skeletal muscle injury within a vertebrate model using a robust genetic\nframework that had not been available previously. Unlike the transient and tightly regulated\nmacrophage activation observed in wild-type animals, typically following a bell-shaped curve, our\nnlrc3l mutant model exhibits sustained and inappropriate macrophage activation throughout the injury\nand repair process (see Supplementary Fig. 12).\nImportantly, this is a genetic model designed to uncover fundamental principles underlying\nmacrophage mis-programming, rather than to mimic a specific disease state. We appreciate the\nreviewer’s suggestion to explore the generalizability of our findings using an alternative paradigm.\nIn response, we have developed an additional model based on a persistent systemic E. coli infection.\nThis new model enables us to examine whether chronic macrophage activation similarly disrupts\nnormal muscle repair and alters the functional subtypes of macrophages, particularly those associated\nwith Mrc1/CD206 receptor downregulation. Using a commonly employed E. coli lab strain (MG1655),\nwe microinjected a high dose of bacteria into the brain ventricle of early embryos prior to injury and\nmonitored both injury response and macrophages activation over time. We confirmed that our\nparadigm induced robust, systemic, and enduring macrophage activation (new data presented in\nSupplementary Fig. 17). Using this new model, we found that the muscle repair defects closely\nresemble those seen in nlrc3l mutants. Furthermore, these defects were associated with the\nloss of the two key macrophages subtypes (clustering and muscle-encasing) and downregulation of\nmacrophage mrc1b expression, all reminiscent of nlrc3l mutants (Supplementary Fig. 17).\nWe have added this new data in Supplementary Fig. 17 and the following text to the Results section:\n“To further explore the generalizability to additional paradigms of chronic macrophage activation, we\ndeveloped a model based on persistent systemic E. coli infection (Supplementary Fig. 17a-c), and\nshowed that similar to nlrc3l mutants, the chronic macrophage activation caused by infection disrupted\nnormal skeletal muscle repair (Supplementary Fig. 17d-e), and was associated with a mrc1b\ndownregulation and reduction of both clustering and encasing macrophage subtypes (Supplementary\nFig. 17f-i).”\nTogether, these complementary approaches strengthen the broader relevance of our findings and\nprovide valuable insight into how chronic inflammatory conditions may derail tissue repair mechanisms\nthrough sustained macrophage activation.\n2) Given the role of CD206 in macrophage-mediated phagocytosis, it is unsurprising that\nCD206 knockdown (CD206-KD) results in impaired muscle regeneration. However, the\nrelationship between CD206-KD and MyD88-null experiments remains unclear. Does the\nloss of MyD88 in NLRC3-null conditions restore CD206 expression? If so, how is CD206\nexpression regulated under chronic conditions?\nWe appreciate the reviewer’s thoughtful comments. While the Mrc1/CD206 may be expected to\ninfluence phagocytosis, its specific role in macrophage-mediated skeletal muscle repair has not been\nestablished. A key finding of this study is the differential role of the Mrc1/CD206, particularly the\ndownregulation of mrc1b, in chronically activated macrophages in both genetic and persistent infection\nmodels, a novel insight that may explain previously unrecognized deficiencies in macrophage function\nunder chronic inflammation. Furthermore, its essential role in acute muscle injury repair and ability to\nlabel macrophage subtypes involved in this process had not been previously demonstrated.\nOur study reveals that mrc1b downregulation contributes to the loss of pro-repair macrophage\nsubtypes 2 and 3. Notably, single-cell transcriptomic analysis across injury timepoints shows that\nmrc1b dynamically marks macrophage states, with unexpectedly high expression at baseline rather\nthan during peak phagocytic activity, highlighting further how its in vivo role remains poorly\nunderstood.\nIn response to the reviewer’s suggestion, we performed additional experiments to assess whether loss\nof MyD88 can restore mrc1b expression in nlrc3l mutants. Our results show that MyD88 knockout in\nnlrc3l mutants indeed leads to the recovery of mrc1b expression in macrophages. This finding\nsupports the hypothesis that MyD88-dependent signaling contributes to the dysregulated macrophage\nstate observed in nlrc3l mutants that involves inappropriate repression of mrc1b transcription, and that\nits deletion helps restore a more homeostatic macrophage phenotype, including re-expression of\nmrc1b following muscle injury. This new data has been added to Fig. 6g,h.\nWhile the exact molecular mechanism regulating mrc1b remains unclear, our findings provide a\nfoundation for future studies into how chronic inflammatory activation alters mrc1b expression during\ninjury and repair. Notably, depletion of MyD88 signaling partially restores mrc1b levels, suggesting that\nthe NF-kB pathway downstream of MyD88 may negatively regulate mrc1b transcription, or through\nNF-kB target genes that repress mrc1b transcription. Fully elucidating this mechanism will require\ndedicated studies to identify key transcription factors or regulators, develop new reporters, and\nperform targeted functional assays, which are beyond the scope of this work. We view this as an\nexciting future direction and have added relevant discussion to the revised manuscript.\n3) Lines 65-66；dynamic in vivo and longitudinal analyses of cellular interactions across\ndistinct phases of the injury and repair process are lacking\nSome studies conducted dynamic and longitudinal analyses using scRNA-seq. For instance,\nthe following studies conducted dynamic, longitudinal, interactome analyses using scRNA-seq\nduring muscle regeneration in detail. This reviewer recommends citing these papers and re-\nrewrite more precisely.\niScience. 2020 Apr 24;23(4):100993. doi: 10.1016/j.isci.2020.100993.\nCell Rep. 2020 Mar 10;30(10):3583-3595.e5. doi: 10.1016/j.celrep.2020.02.067.\nPoint well taken. We have revised the text to more clearly distinguish our study, which, to the best of\nour knowledge, is the first to capture real-time in vivo imaging of dynamic cellular interactions during\nskeletal muscle repair in intact, living animals. This was made possible through time-lapse imaging\ncombined with a rigorous longitudinal microscopy approach. The recommended citations have also\nbeen added.\nRevised text in manuscript states: Although prior studies have provided insights into the role of\nmacrophages in responding to and facilitating acute muscle injury repair1,3,6,8, including via single-cell\ntranscriptomics and trajectory analysis to infer temporal changes and cellular interactions12,13, direct\nreal-time in vivo imaging of macrophage behaviors and interactions throughout the injury response\nremains lacking. Timelapse imaging as well as a rigorous longitudinal microscopy approach enabled\nus to track macrophages across distinct muscle injury and repair phases within the same subjects.\n4) Lines 204; It is difficult to find Mrc1b/cd206 in the figure.\nWe have now made the mrc1b/cd206 text in red in Figure 2g, so that the data for this gene is easier to\nfind in the heat map.\n5) Line 244 ;\nWhat is ASC? Please add a description of the relationship between ASC and nlrc3l.\nThank for pointing out the lack of description on ASC. We have added and modified text to address\nthis, which now states: “Furthermore, because several Nod-like receptors are known to interact with\nthe adaptor protein called apoptosis-associated speck like protein containing a CARD (also known as\nASC) to form cytosolic multiprotein complexes called inflammasomes, responsible for activation of\ninflammatory signaling, we explored whether macrophage activation was ASC-dependent. We\ngenerated nlrc3l/asc double mutants that showed no change from the nlrc3l mutant activation\nphenotype, thereby indicating nlrc3l functioned in an inflammasome-independent manner in this\ncontext (Fig. 3).”\n6) Lines 451-452; The precise role of macrophages in skeletal muscle injury and repair remains\nincompletely understood.\nPlease describe what the precise role is not understood. In addition, the authors need to\nunderscore what the present study reveals in the role of macrophages in muscle regeneration.\nThis reviewer thinks that mechanisms inducing chronic inflammatory conditions in muscle\nregeneration are unexplored. However, the disruption of muscle regeneration by chronic\ninflammation is not conceptually new.\nThank you for your helpful comments. We have revised the text to better highlight the knowledge gap\nwe are addressing, now stating: “The impact of prolonged inflammatory activation on macrophage\nheterogeneity and function during muscle repair remains poorly defined.”\nTo highlight the key advances of our study, we emphasize the work we have conducted to show that\nchronic inflammatory activation of macrophages reconfigures their states in a manner that impairs their\nability to support muscle repair. Integrating in vivo dynamic imaging with single-cell RNA-seq, we\nidentified two previously unknown reparative macrophage subtypes, apoeb+/ctsk+ clustering and\ntgfbi+/sb:cb81+ muscle-encasing, that are selectively lost in both genetic and persistent infection\nmodels of chronic inflammation (Fig. 7 and Supplementary Figs. 13, 17-19). Contrary to conventional\ndiscrete states, we show that chronic activation drives macrophages into a dysfunctional hybrid M1/M2\nstate, marked by sustained pro-inflammatory gene expression despite partial activation of reparative\npathways. Mechanistically, chronic inflammatory activation of macrophages represses mrc1b via a\nMyD88-dependent pathway, leading to the loss of reparative subtypes enriched for genes involved in\ncholesterol efflux, phagocytosis, and TGF-β signaling. scRNA-seq further identified cathepsin K (ctsk),\na cysteine protease, as a novel marker of reparative subtype 2. With further in vivo validation, we\nshow that dense CTSK protein accumulations are found intracellularly in a subpopulation of both\nreparative subtypes post-injury, an effect strikingly absent in chronically activated nlrc3l mutants (Fig.\n8). Notably, CTSK⁺ macrophages co-express tnfa, consistent with a hybrid inflammatory-reparative\nphenotype (Fig. 8). These findings establish CTSK protein accumulation as a functional marker of\nreparative macrophage identity and provide new mechanistic insight into how chronic inflammation\nreshapes macrophage states, generally restricting functional plasticity, compromising their role in\ntissue repair. We have added text in the manuscript to better highlight our new findings and the\nsignificance of this study.\n7)Lines 358-361, 461\nThe authors described that chronically activated macrophages inhibit satellite cell activation.\nThere is no evidence that chronic macrophages directly inhibit satellite cell activation. Is it\npossible that chronically activated macrophages inhibit not the activation, but the\nproliferation? And is it possible that the chronic macrophages disrupt the balance of pro-\ninflammatory macrophages inducing satellite cell activation or proliferation?\nWe thank the reviewer for the thoughtful comment. We agree that it remains unclear whether the\neffects of chronically activated macrophages on stem cell activation are direct or indirect. We do not\nmake this claim, but agree this represents an interesting avenue for future study to dissect the\nunderlying signals.\nSatellite cell activation has been defined in literature as the re-entry of quiescent cells into the cell\ncycle, leading to proliferation and relocalization of these stem cells from their typical location between\nthe sacrolema of the muscle fibers to the site of injury. Therefore, activation is coupled with\nproliferation. Both of these features—an increase in Pax7⁺ satellite cells and their enrichment at the\ninjury site—are observed post-injury in wild-type and controls, but not in mutants, as shown in Fig.\n12a. We therefore concluded that the chronically activated macrophages in the mutant \"coincided with\ndeficient activation\" of stem cells (lines 358-361), and in the Discussion, in line 460, the data suggest\nstem cell activation is impaired in the mutant.\nWe have now added a citation to Fu et al., 2015 Cell Mol Life Sci. (doi: 10.1007/s00018-014-1819-5)\nand scRNA-seq study characterizing muscle stem activation (Micheli et al., 2020 Cell Reports\nhttps://doi.org/10.1016/j.celrep.2020.02.067) to provide further context on stem cell activation in\nskeletal muscle regeneration. We agree with the reviewer that the chronic activation of mutant\nmacrophages is likely causing a major shift in macrophage states. We added text in the Discussion\nfollowing line 460 that the impaired repair is “likely due to a significant imbalance in macrophage\nstates, skewing heavily toward a chronically pro-inflammatory profile,”."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed all my concerns in the revised manuscript. Importantly, they have now included a comprehensive scRNA-seq analysis, which provides high-resolution validation of the bulk RNA-seq data presented in the original version. These new data not only strengthen the conclusions but also significantly expand the impact of the work.\nThe exhaustive characterization of macrophages and neutrophils in the context of chronic inflammation is exceptional and provides information of broad relevance to the field, beyond the scope of this article. Of particular interest is the identification of a hybrid M1/M2 macrophage state that predominates under chronic inflammation, as well as the delineation of numerous markers of macrophage polarization, such as ctsk.\nOverall, the manuscript is now excellent in all respects. The study represents a major advance in our understanding of immune cell heterogeneity and plasticity during chronic inflammation and tissue repair.\nI strongly recommend acceptance of this article.", "reviewer_2": "The overall quality of the manuscript has improved significantly after revision, and some of my previous concerns have been addressed. However, several issues remain that the authors must further clarify and revise.\n\nMajor points\n1. I acknowledge and agree that zebrafish Nlrc3l may represent a unique NLR without a clear mammalian ortholog. Nevertheless, its mechanism of action is expected to be evolutionarily conserved. Currently, there is insufficient evidence to support that zebrafish Nlrc3l functions through a completely distinct mechanism from mammals. As the authors noted, zebrafish nlrc3l lacks the LRR domain. In mammals, the only reported NLR lacking an LRR is NLRP10 (Kanneganti TD et al., Immunity 2007). Previous studies have demonstrated that NLRP10 can induce ASC speck formation and participate in anti-inflammatory regulation in human keratinocytes and mouse intestinal epithelial cells (Próchnicki T et al., Nat Immunol 2023; Zheng D et al., Nat Immunol 2023). However, the authors’ current conclusion that Nlrc3l is independent of Asc is based solely on low-resolution stereomicroscope imaging in Fig. 3C, which seems premature. Zebrafish are three-dimensional organisms, where signals from the opposite side are easily missed, and out-of-focus GFP signals are inherently attenuated. More reliable approaches should include qRT-PCR or quantitative GFP Western blot. Moreover, the number of irg1⁺ cells shown in Fig. 3C appears to be slightly reduced in Nlrc3l/Asc double mutants. Even within zebrafish studies, evidence already suggests that Nlrc3l regulates microglial cell death in part through Asc (Chang MX et al., Dev Comp Immunol 2021; Wang T et al., J Genet Genomics 2019). Taken together with mammalian and zebrafish findings, as well as potential misinterpretation of the current data, it remains premature to exclude the possibility that Nlrc3l phenotypes are ASC-related. Additional experimental data are required.\n2. The authors attempt to explain the phenotype of Nlrc3l deficiency via the “master regulator” Myd88, but this level of mechanistic interpretation is insufficient for a Nature Communications-level study. This is somewhat analogous to showing that an anti-inflammatory drug partially rescues the phenotype—an expected observation, but not true mechanistic insight. Furthermore, the irg1 used in the Myd88-dependent assays is expressed only in myeloid cells, so the conclusion applies only to this lineage, not to the entire organism. Similarly, the irg1 reporter line and mpeg1-nlrc3l rescue address immune cell-specific phenotypes, but cannot rule out contributions from non-immune cells. In Fig. 3D, the difference between the last two groups exceeds threefold, yet the small sample size (n ≈ 5 per group) makes the lack of statistical significance unconvincing. The subsequent germ-free model experiments further underscore the presence of non-cell-autonomous mechanisms, reinforcing this concern. In such models, commensal bacteria primarily interact with the skin and intestinal epithelium, where NLRP10 has been shown to be highly expressed. Given that the tissue injury model used by the authors inherently damages epithelial cells, a more plausible explanation is that Nlrc3l deficiency triggers commensal-driven mucosal systemic inflammation, which in turn disrupts macrophage function. This hypothesis may actually represent a more valuable research direction. I encourage the authors to integrate findings from NLRP10-related studies to explore this potential mechanistic conservation between zebrafish Nlrc3l and mammalian NLRP10.\n3.The association of CD206 with tissue regeneration has been well documented (Shook B et al., J Invest Dermatol 2016; Honda A et al., EMBO Rep 2025). While not necessarily specific to skeletal muscle regeneration, the underlying logic remains the same. The current findings resemble more of a “me-too” type of study. The authors should sufficiently reference and acknowledge existing literature and refine the novelty of their study in light of prior research.\n\nMinor points\n1. In Fig. S17, the bacterial injection site is not the brain ventricle.", "reviewer_3": "In the first round of review, this reviewer raised three major concerns: (1) the generalization of the findings in the Nlrc1 mutant model, (2) the expression in Nlrc3l/Myd88 double mutant mice, and (3) the conceptual advance of this study. The authors have sincerely addressed these concerns with new data and descriptions. In addition, the authors performed scRNA-seq analyses, which strengthen their findings on the alteration of macrophage subtypes in chronic environments.\nPlease address the following comments to further improve the manuscript.\n• There are several instances in the main text where the specific figure panels are not indicated. Please provide this information consistently. In particular, the descriptions of Figures 3, 5, 8, and supplemental figures do not mention the corresponding panels.\n• Related to the above comments, it is unclear which figure corresponds to the description of the scRNA-seq results. The relationship between subtypes 1–3 and the scRNA-seq clusters represents a crucial result in this manuscript. The reviewer recommends that all genes used to analyze the relationship between imaging subtypes and scRNA-seq clusters be presented in the main figure, so that readers can readily recognize them.\n• Figure 6, Figure 4, Supplemental Figure 11, 15 contain errors in their preparation.\n•The meaning of the sample name in Supplemental Figure 19f is unclear. What does 3d_1 signify?"}, "author_response": "Point-by-point response to the reviewers’ comments is shown in italicized text.\nReviewer #1 (Remarks to the Author):\nThe authors have satisfactorily addressed all my concerns in the revised manuscript.\nImportantly, they have now included a comprehensive scRNA-seq analysis, which provides\nhigh-resolution validation of the bulk RNA-seq data presented in the original version. These\nnew data not only strengthen the conclusions but also significantly expand the impact of\nthe work.\nThe exhaustive characterization of macrophages and neutrophils in the context of chronic\ninflammation is exceptional and provides information of broad relevance to the field,\nbeyond the scope of this article. Of particular interest is the identification of a hybrid M1/M2\nmacrophage state that predominates under chronic inflammation, as well as the delineation\nof numerous markers of macrophage polarization, such as ctsk.\nOverall, the manuscript is now excellent in all respects. The study represents a major\nadvance in our understanding of immune cell heterogeneity and plasticity during chronic\ninflammation and tissue repair.\nI strongly recommend acceptance of this article.\nWe are grateful to Reviewer 1 for their recognition of the depth and significance of our work, and\nfor their insightful and constructive feedback, which have substantially strengthened our study.\nReviewer #2 (Remarks to the Author):\nThe overall quality of the manuscript has improved significantly after revision, and some of\nmy previous concerns have been addressed. However, several issues remain that the\nauthors must further clarify and revise.\nMajor points\n1. I acknowledge and agree that zebrafish Nlrc3l may represent a unique NLR without a\nclear mammalian ortholog. Nevertheless, its mechanism of action is expected to be\nevolutionarily conserved. Currently, there is insufficient evidence to support that zebrafish\nNlrc3l functions throug h a completely distinct mechanism from mammals. As the authors\nnoted, zebrafish nlrc3l lacks the LRR domain. In mammals, the only reported NLR lacking\nan LRR is NLRP10 (Kanneganti TD et al., Immunity 2007). Previous studies have\ndemonstrated that NLRP10 can induce ASC speck formation and participate in anti-\ninflammatory regulation in human keratinocytes and mouse intestinal epithelial cells\n(Próchnicki T et al., Nat Immunol 2023; Zheng D et al., Nat Immunol 2023).\nWe thank Reviewer 2 for the continued thoughtful feedback. While we understand the desire to\ndraw parallels between nlrc3l and known mammalian NLRs such as NLRP10 because it also lacks\nLRR, it is important to underscore that nlrc3l lacks a mammalian ortholog, making it inherently\ndifficult to predict its mechanism of action based on conserved domains or canonical pathways.\nNotably, NLRP10 has been shown to act through inflammasome and non-inflammasome pathways\n(Joly et al., 2013 J. Immunol. and reviewed in Zhong et al., 2013 Front. Immunol). Several other\nNLRs (e.g., NOD1/2, NLRC5) are well-documented to also function through non-inflammasome\npathways, activating transcriptional regulators like NF-κB or MAPKs, and many mechanistic\naspects of mammalian NLRs especially the less-studied members remain unresolved (reviewed in\nPlatnich and Muruve 2023 Arch Biochem and Biophys).\nHowever, the authors’ current conclusion that Nlrc3l is independent of Asc is based solely\non low-resolution stereomicroscope imaging in Fig. 3C, which seems premature. Zebrafish\nare three-dimensional organisms, where signals from the opposite side are easily missed,\nand out-of-focus GFP signals are inherently attenuated.\nRegarding the use of the low-resolution fluorescent stereomicroscope imaging, we would like to\nclarify that this setup was intentional for stringent screening of inflammatory macrophage\nactivation, requiring a higher GFP detection threshold, to identify embryos with high GFP\nexpression as a clear indicator for irg1/acod1 induction using the irg1-KI:GFP reporter. As shown\nin Fig. 3C, high GFP+ macrophages persist in nlrc3l/asc double mutants, comparable to nlrc3l\nsingle mutants, as opposed to wild-type and control siblings which have either undetectable or\nbarely detectable GFP+ cells. Quantification of the data is adjacent to the images, and two\nbiological replicates of single nlrc3l and double nlrc3l/asc mutants are shown to display the typical\nrange of macrophage presence on yolk ball (Fig. 3C). There is no concern of missing GFP signals\nbecause our conclusion is based on finding high GFP expression in the nlrc3l/asc double mutants,\nand therefore supporting the conclusion that macrophage activation still persists despite asc\ndeletion. Additional new data from qPCR in this submission as described next supports this finding\n(Supplementary Fig. 7).\nMore reliable approaches should include qRT-PCR or quantitative GFP Western blot.\nMoreover, the number of irg1⁺ cells shown in Fig. 3C appears to be slightly reduced in\nNlrc3l/Asc double mutants. Even within zebrafish studies, evidence already suggests that\nNlrc3l regulates microglial cell death in part through Asc (Chang MX et al., Dev Comp\nImmunol 2021; Wang T et al., J Genet Genomics 2019). Taken together with mammalian and\nzebrafish findings, as well as potential misinterpretation of the current data, it remains\npremature to exclude the possibility that Nlrc3l phenotypes are ASC-related. Additional\nexperimental data are required.\nTo address the reviewer’s concern with additional data, we performed additional experiments in\nthis revision. Specifically, we added qPCR analysis of endogenous irg1/acod1 expression and a\nfunctional skeletal muscle repair assay to test whether asc deletion modifies the inflammatory\nmacrophages or tissue repair defects of nlrc3l mutants. In both assays, asc deletion failed to\nrescue the nlrc3l phenotype, consistent with our prior imaging and genetic epistasis data (shown in\nFig. 3). By contrast, macrophage-rescue of nlrc3l mutants was used as a positive control, which\ndemonstrated rescue of the repair deficiency. These new findings are presented in Supplementary\nFig. 7 and the corresponding figure legend text describing the results is copied below.\nRelevant text to new data added in Supplementary Fig. 7: \"b Quantification of endogenous irg1\n(also known as acod1) transcript levels by qPCR demonstrates aberrantly elevated irg1 expression\nat 3 dpf in baseline nlrc3l mutants, as well as in nlrc3l/asc double mutants, indicating no evidence\nof a genetic interaction between nlrc3l and asc. c Functional assessment of the nlrc3l–asc\ninteraction during the resolution phase of acute muscle injury response at 48 hours post-\namputation (hpa) shows comparable persistence of unresolved muscle tissue (orange arrows) in\nnlrc3l single and nlrc3l;asc double mutants, whereas controls exhibit effective clearance of\ndamaged muscle, further supporting an asc-independent role for nlrc3l. Macrophage-specific\nrescue of nlrc3l expression, which restores normal repair, was included as a positive control for the\nassay. d Quantification of phenotypic outcomes across genotypes is presented in the\naccompanying bar chart.\"\nWith regard to the citations on other studies of zebrafish nlrc3l, we are well aware of them, one\nbeing a review article Chang MX et al., Dev Comp Immunol 2021 that summarizes the primary\nresearch study by Wang et al., J. Genet. Genom. 2019. The rescue observed in a temperature-\nsensitive nlrc3l mutant by asc deletion (Wang et al.) is partial and reflects a different model and\nbiological process (microglial maintenance and survival after microglia establishment where they\nwere looking for recovery of microglial numbers), and uses a milder allele compared to the\nnonsense mutation of nlrc3l employed here. These differences in context and allele strength may\nexplain the divergence in results regarding the role of asc.\nIn sum, across multiple independent approaches, our datasets consistently show that deletion of\nasc does not modify the nlrc3l mutant phenotype, namely inappropriate macrophage activation and\nimpaired tissue repair (see Supplementary Fig. 7). While nlrc3l shares some structural features\nwith other NLRs, its mechanism is yet unknown and requires future dedicated mechanistic\ninvestigation beyond the scope of this study. The additional transcriptional and functional data\npresented in this revision further reinforces a mechanism by which nlrc3l negatively regulates\nmacrophage inflammation independently of asc.\n2. The authors attempt to explain the phenotype of Nlrc3l deficiency via the “master\nregulator” Myd88, but this level of mechanistic interpretation is insufficient for a Nature\nCommunications-level study. This is somewhat analogous to showing that an anti-\ninflammatory drug partially rescues the phenotype—an expected observation, but not true\nmechanistic insight.\nWe thank Reviewer 2 for their comments and the opportunity to clarify the scope and significance\nof our study.\nRegarding the Reviewer’s concern that the involvement of myd88 is not a “true mechanistic\ninsight,” our genetic approach provides gene-specific analysis not achievable with pharmacological\ninhibition, which often produces complex off-target effects. While myd88 is a known adaptor in\nseveral inflammatory pathways pertaining to TLRs, its role in chronic macrophage activation,\nparticularly in our nlrc3l mutant model, was previously unknown. Moreover, myd88 does not\nmediate all inflammatory signaling, and its involvement in Nod-like receptor signaling remains\npoorly understood; importantly, myd88-independent pathways such as TRIF-dependent TLR\nsignaling are also well established. The finding that myd88 knockout switches aberrantly\nactivated nlrc3l mutant macrophages to more normal states was a key finding for our study, and\nfrom another perspective, it underscores the relevance of our study to other chronic inflammatory\nconditions driven by excessive Myd88 activation.\nThe broader goal of our study is to address a key challenge in immunology, which is to understand\nthe dynamic transitions and shifts in immune cell states by direct visualization of these processes\nin real time at single cellular resolution during a perturbation. This study is not focused on\ndefining the molecular mechanism of nlrc3l, but rather on using nlrc3l mutants as a genetic tool to\nprobe macrophage plasticity. By forcing all macrophages toward chronic pro-inflammatory (M1-\nlike) states in vivo using the nlrc3l mutants (as shown in Figure 2 and Supplementary Fig. 12),\nwe can then directly test how adaptable and reversible macrophage states are upon an injury\nperturbation within the intact living organism, capturing its full physiological complexity, often in real\ntime, in contrast to most studies that are limited to in vitro and ex vivo analyses.\nCombining new imaging tools, including a GFP knock-in at the irg1/acod1 locus, with single-cell\nanalysis we identified dynamic hybrid M1/M2 macrophage states as well as novel reparative\nsubtypes such as muscle-encasing macrophages, all previously not known, that coordinate early\nrepair but become functionally impaired or lost under chronic inflammation. Notably, we found that\nchronic activation drives myd88-dependent drastic downregulation of the mannose\nreceptor mrc1b/cd206 in both the genetic and persistent infection model of chronic inflammation.\nThis dynamic modulation of mrc1b links chronic inflammatory signaling to loss of macrophage\nreparative capacity (including expression of pro-repair genes such as accumulation of cathepsin\nK), providing a mechanistic bridge between inflammation and defective tissue repair.\nFurthermore, the irg1 used in the Myd88-dependent assays is expressed only in myeloid\ncells, so the conclusion applies only to this lineage, not to the entire organism. Similarly,\nthe irg1 reporter line and mpeg1-nlrc3l rescue address immune cell-specific phenotypes,\nbut cannot rule out contributions from non-immune cells.\nWe appreciate the reviewer's comment. To clarify, while the roles of non-immune cells may be\ninteresting, they are beyond the scope of this study. Our work specifically focuses on how chronic\nactivation affects macrophage cellular heterogeneity and plasticity on both a functional and\nmolecular basis. The experimental design was intentionally tailored to target macrophages, and\nour conclusions are limited to the immune cells that were directly manipulated, analyzed, and\ncharacterized in this study.\nIn Fig. 3D, the difference between the last two groups exceeds threefold, yet the small\nsample size (n ≈ 5 per group) makes the lack of statistical significance unconvincing.\nWe interpret the Reviewer’s comment as referring to the last two groups containing the\nmacrophage–rescue (mpeg1-nlrc3l) construct: comparing nlrc3l mutants and nlrc3l/myd88 double\nmutants, both with the macrophage–rescue. In both groups, irg1 expression was generally very\nlow or undetectable, indicating the restoration of normal homeostatic states in macrophages.\nAlthough the double mutants with the macrophage-rescue showed a trend toward even lower irg1\nexpression, suggesting a more complete rescue, this difference was not statistically significant.\nSince the macrophage-rescue restores both conditions to relatively more normal states, the\npotential statistical difference would not alter the overall conclusion. To provide more context to the\nexperimental design, these experiments are technically challenging, as they require double\nheterozygous incrosses, which yield only 1 double mutant in every ~ 16 animals. To obtain the\nseven double knockouts we analyzed, we conducted multiple experiments totaling over 100\nanimals. All double mutants were analyzed, and a random subset of control animals without\nthe nlrc3l deletion was included. Because all controls consistently exhibited low or undetectable\nirg1 expression, random sampling of controls provided an adequate comparison.\nThe subsequent germ-free model experiments further underscore the presence of non-cell-\nautonomous mechanisms, reinforcing this concern. In such models, commensal bacteria\nprimarily interact with the skin and intestinal epithelium, where NLRP10 has been shown to\nbe highly expressed. Given that the tissue injury model used by the authors inherently\ndamages epithelial cells, a more plausible explanation is that Nlrc3l deficiency triggers\ncommensal-driven mucosal systemic inflammation, which in turn disrupts macrophage\nfunction. This hypothesis may actually represent a more valuable research direction. I\nencourage the authors to integrate findings from NLRP10-related studies to explore this\npotential mechanistic conservation between zebrafish Nlrc3l and mammalian NLRP10.\nThe data do not indicate any major off-target effects in tissues or cell types beyond those\nanalyzed. First, nlrc3l mutant macrophages exhibit inappropriate baseline activation even without\ninjury or external challenge (Figs. 2, 3). Moreover, macrophage-specific rescue in nlrc3l mutants\nrestored appropriate muscle injury repair (Fig. 5), indicating that the observed phenotypes related\nto injury response are macrophage-cell-autonomous. Furthermore, whole-body and in vivo imaging\nduring muscle injury showed no abnormal immune cell coalescence or migration to the skin or\nother non-injured sites. Given that the imaging captures the entire body, including the skin, any off-\ntarget immune responses (particularly the skin) would have been detectable but were not\nobserved.\n3.The association of CD206 with tissue regeneration has been well documented (Shook B et\nal., J Invest Dermatol 2016; Honda A et al., EMBO Rep 2025). While not necessarily specific\nto skeletal muscle regeneration, the underlying logic remains the same. The current\nfindings resemble more of a “me-too” type of study. The authors should sufficiently\nreference and acknowledge existing literature and refine the novelty of their study in light of\nprior research.\nThank you for the Reviewer’s comment. We agree that expanding the Discussion to include\nadditional studies identifying CD206 as a marker for reparative macrophages in other tissue injury\nmodels strengthens the broader relevance of our findings. Accordingly, we have cited Shook et al.\n(2016) and Honda et al. (2025), which demonstrated that CD206 marks major macrophage\npopulations associated with skin wound repair, respectively, along with other relevant CD206\nstudies in the Discussion.\nWe also clarify in the revised Discussion how our work distinguishes from these prior studies. The\nnovelty of our findings lies not in identifying Mrc1/CD206 as a reparative macrophage marker, but\nin uncovering its dynamic regulation during injury and chronic inflammation. Specifically, our new\nscRNA-seq analysis shows that Mrc1/CD206 expression is highest in steady-state macrophages,\nnormally downregulated to enable reparative programs during the initial inflammatory phase of an\ninjury response, but becomes pathologically suppressed under chronic inflammatory conditions\n(shown by several independent in vivo experiments- bulk and single-cell RNA-seq of sorted\nmacrophages, HCR-based RNA in situ hybridization, and complementary infection model). We\nfurther demonstrate that this drastic suppression in chronically activated macrophages is MyD88-dependent and associated with loss of reparative features, including cytosolic cathepsin K\naccumulation. These insights reveal a previously unrecognized mechanism linking chronic\ninflammation to a severe loss of mannose receptor as a cause for reduced macrophage plasticity\nand impaired tissue repair.\nMinor points\n1. In Fig. S17, the bacterial injection site is not the brain ventricle.\nThank you for pointing out this issue that we missed. The cartoon has been corrected to show the\nneedle pointing into the brain ventricle region.\nReviewer #3 (Remarks to the Author):\nIn the first round of review, this reviewer raised three major concerns: (1) the generalization\nof the findings in the Nlrc1 mutant model, (2) the expression in Nlrc3l/Myd88 double mutant\nmice, and (3) the conceptual advance of this study. The authors have sincerely addressed\nthese concerns with new data and descriptions. In addition, the authors performed scRNA-\nseq analyses, which strengthen their findings on the alteration of macrophage subtypes in\nchronic environments. Please address the following comments to further improve the\nmanuscript.\n• There are several instances in the main text where the specific figure panels are not\nindicated. Please provide this information consistently. In particular, the descriptions of\nFigures 3, 5, 8, and supplemental figures do not mention the corresponding panels.\nThank you for the helpful feedback. We have added reference to specific figure panels to the main\nfigures and supplemental figure where specific panels, rather than entire figures, are relevant.\n• Related to the above comments, it is unclear which figure corresponds to the description\nof the scRNA-seq results. The relationship between subtypes 1–3 and the scRNA-seq\nclusters represents a crucial result in this manuscript. The reviewer recommends that all\ngenes used to analyze the relationship between imaging subtypes and scRNA-seq clusters\nbe presented in the main figure, so that readers can readily recognize them.\nThank you for the helpful comment. We have added additional references in the manuscript to\nspecific scRNA-seq datasets corresponding to Figure 7 and Supplementary Figures 18-20, as we\nagree this better highlights the molecular profiling of the subtypes. We have also revised the main\nFigure 7 to include the key genes defining the three subtypes, which were originally shown in\nSupplementary Figure 19. Additional supporting data characterizing the macrophage-specific cells\nwill remain in Supplementary Figure 19 due to space constraints.\n• Figure 6, Figure 4, Supplemental Figure 11, 15 contain errors in their preparation.\nThanks to Reviewer's careful review of these figures. We have corrected all errors we detected,\nincluding the image panels that were not aligned and missing annotations on plots or images.\n•The meaning of the sample name in Supplemental Figure 19f is unclear. What does 3d_1\nsignify?\nThanks for pointing out the missing descriptions. The sample names indicate the condition based on\ngenotype and injury-response timepoint from which the cells were derived. The suffix (e.g., “3d_1”)\ndenotes the zebrafish's stage (3 days post-fertilization) and the biological replicate (replicate 1 of 2).\nThe bubble plot in Fig. 19f displays data for all samples, allowing comparison across all biological\nreplicates and conditions. It highlights that the DEGs were highly robust and consistent across\nreplicates. Unsupervised hierarchical clustering shows that samples grouped by condition, with mutant\n24 hpa samples being the most distinct, followed by the control 24 hpa samples.\nWe have added the following text to the Figure legend to clarify the labels:\n\"The sample names below the bubble plot denote the genotype and either the injury-response time\npoint (24 h or 48 h) or the uncut baseline, with the suffix indicating zebrafish stage (such as 3d for 3\ndpf) and biological replicate (such as replicate 1 of 2).\""}]

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