Genetic dissection of microglia cannibalism reveals an IL10 signaling axis controls microglia lifespan

Genetic dissection of microglia cannibalism reveals an IL10 signaling axis controls microglia lifespan | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Genetic dissection of microglia cannibalism reveals an IL10 signaling axis controls microglia lifespan Hannah Gordon , Dailin Gan , Antonio Dolojan , John Dennen , Camden A. Hoover , Zachary M. Koh , Khang Chau , Ricky Avalos Arceo , Cara Cavanaugh , Jun Li , View ORCID Profile Cody J. Smith doi: https://doi.org/10.1101/2025.11.21.689277 Hannah Gordon 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dailin Gan 3 Department of Applied and Computational Mathematics and Statistics, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Antonio Dolojan 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Dennen 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Camden A. Hoover 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zachary M. Koh 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Khang Chau 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ricky Avalos Arceo 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cara Cavanaugh 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jun Li 3 Department of Applied and Computational Mathematics and Statistics, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cody J. Smith 1 Department of Biological Sciences, at the University of Notre Dame , Notre Dame, IN 2 The Center for Stem Cells and Regenerative Medicine, at the University of Notre Dame , Notre Dame, IN Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Cody J. Smith For correspondence: csmith67{at}nd.edu Abstract Full Text Info/History Metrics Preview PDF Abstract The development of complex organs, like the brain, demands a robust system for tissue remodeling and cellular debris clearance. In the brain, this function is performed by microglia, which must clear diverse debris substrates, including that caused by cell death. Although the subsequent fate of these phagocytic microglia is a critical regulatory point that impacts whether the brain resolves a debris environment, the genetic mechanisms that control microglia fate after debris clearance remain mostly unknown. To address this, we conducted a large-scale CRISPR screen in zebrafish using a custom-built robotic confocal microscope. We selected candidate genes from a single-cell RNA sequencing dataset of embryonic mouse microglia. This screen identified several modulators of microglial lifespan and cannibalism that are enriched in mouse and zebrafish microglia, including interleukin-10 receptor beta ( il10rb ), a receptor subunit for the cytokine IL10. Perturbation of il10 , il10rb, and downstream signaling molecules JAK/STAT in zebrafish reduced microglial death. Expression analysis in mouse and zebrafish confirmed that microglia express both il10 and il10rb . Given the established role of IL10 in lysosomal remodeling, we hypothesized that it regulates microglial survival through lysosomal acidification. While il10rb perturbation did not alter lysosome number or size, it caused a significant reduction in LysoTracker-positive lysosomes, indicating decreased lysosomal acidification. Inhibiting v-ATPase also reduced microglial death, reinforcing the link between lysosomal pH and cell fate. Our findings reveal a cytokine-regulated mechanism where lysosomal dynamics determine the survival of phagocytic microglia. We propose that a necroptosis-cannibalism process functions as a quality control mechanism for microglial turnover, which is critical for refining neuroimmune cell function in the brain. Introduction The clearance of dead cells is a critical component of organ development and health. Microglia, the resident immune cell of the central nervous system (CNS) 1 , serve as the dedicated undertakers of the CNS, by continuously clearing the environment of cellular debris and dead cells 2 , 3 . One of their most fundamental roles during embryonic development is efferocytosis 4 – 11 , the swift and non-inflammatory clearance of dead and dying cells 12 . This clearance is crucial for maintaining brain homeostasis 8 , 13 and tissue patterning 14 , as impaired efferocytosis by microglia can provoke inflammation 15 , 16 , lead to aberrant circuit function 17 , 18 , and drive neurological pathologies 11 . Despite this, the mechanisms regulating microglia themselves during periods of this intense phagocytic demand—and how their own survival is influenced by the debris they ingest—remain poorly understood. While efferocytosis is typically a protective and homeostatic process 13 , 19 , the high-volume uptake of dead cells can impose significant metabolic 20 – 22 and endolysosomal stress 23 – 25 on phagocytes. This concept is supported by literature showing that macrophages and other phagocytic cells can undergo cell death due to debris overload in contexts ranging from atherosclerosis 26 – 28 to spinal cord injury 29 . This death is not just a passive failure; it is likely an evolutionarily conserved mechanism to prevent prolonged cell damage or the propagation of cytotoxic proteins and undigested lipids within the tissue. In atherosclerosis, the continuous, high-volume uptake of oxidized lipids leads to the formation of lipid-laden (foamy) macrophages 30 , 31 . These phagocytically burdened macrophages are defective phagocytes 32 , 33 , and are prone to programmed cell death 34 – 36 , which represents a crucial, self-refining mechanism to eliminate overloaded cells and prevent the establishment of chronic, non-resolving inflammation 37 . This raises the intriguing possibility that their essential role in clearing debris comes at a cost to their own viability, and that the phagocytosis to cell death process is a self-limiting quality control mechanism. Indeed, recent work has revealed a paradoxical process where embryonic microglia die after becoming phagocytic, and their corpses are subsequently engulfed by other microglia in a process termed microglia cannibalism 38 . This form of microglial death appears to be mediated by necroptosis 38 , a regulated and inflammatory form of cell death characterized by plasma membrane rupture 39 , 40 . This previously unappreciated circuit of efferocytosis-induced necroptosis and cannibalism represents a key mechanism of microglial turnover and raises fundamental questions about its regulation and its developmental purpose. To investigate how microglial lifespan and cannibalism are regulated under the high phagocytic load of neural development, we performed a high-throughput CRISPR-Cas9 screen in larval zebrafish using a dataset of embryonic mouse microglia 41 . This screen revealed that a loss of function in interleukin-10 receptor subunit beta ( il10rb ) significantly reduced cannibalism by decreasing microglial death. The cytokine interleukin-10 (IL10) is known for its potent immunosuppressive effects through the canonical JAK/STAT signaling pathway 42 , 43 , which is mediated by the accessory receptor subunit IL10RB that is expressed by microglia 41 , 44 . While generally associated with cell survival 45 , 46 , IL10 has also been shown to induce cell death under specific stress conditions 47 – 51 , presenting a potential mechanism of the role of IL10 in developmental turnover. Mechanistically, downstream signaling through STAT3 is linked to the endolysosomal system; STAT3 increases the activity of the vacuolar H + -ATPase (v-ATPase) pumps 52 , 53 that are essential for maintaining the highly acidic environment of the lysosome 52 , 54 , 55 . Additionally, there is recent evidence linking IL10 and necroptosis. In a study looking at the effects of IL10 on neonatal mice with unilateral ureteral obstruction, a model for congenital obstructive nephropathies, Il10 −/− mice showed a reduction in necroptosis 56 . However, whether IL10 signaling is the missing link that controls the necroptotic fate of cells after debris clearance remains unknown. Here, we show that IL10 signaling is a central orchestrator of microglial turnover during development. We demonstrate that microglia express both il10 and il10rb , and find that IL10 acts as a direct pro-death signal by engaging the IL10RB/JAK/STAT3 axis to drive necroptosis. Mechanistically, we show that disrupting this signaling impairs lysosomal acidification, a key step in debris degradation. This finding positions the lysosome as the critical stress checkpoint where high phagocytic load and IL10 signaling converge to determine cell fate. Furthermore, we demonstrate that exogenous IL10 accelerates microglial death. Perturbation of il10rb causes microglia to be longer-lived but also exhibit impaired debris clearance and pronounced morphological dysfunction following injury. These findings support a model in which IL10 signaling sensitizes phagocytic microglia to necroptosis by modulating lysosomal function, thereby linking immune regulation to a critical developmental cell death pathway that refines immune cell colonization in the developing brain. Results Building on the recent finding that embryonic microglia undergo necroptosis following phagocytic engulfment of dead cells, we sought to identify the molecular regulators of microglial lifespan and their cannibalism. To identify the molecular components governing this essential turnover mechanism, we designed a large-scale CRISPR knockdown screen. Candidate genes were selected from a re-analysis of a single-cell RNA sequencing (scRNA-seq) dataset of E14.5 embryonic mouse brains 41 ( Fig. 1A ). This analysis identified key clusters composed of microglia and their precursors ( Fig. 1A ). We focused on genes that were enriched in a cluster of cells that expressed transcripts consistent with immature microglia or their precursors and genes expressed in clusters of mature microglia ( Fig. 1 A-B ). These clusters expressed canonical microglial genes like P2ry12 and Tmem119 ( Fig. 1C ). Using differential enrichment of transcripts, we identified 556 transcripts in the mature microglia clusters and 137 enriched genes in the immature microglia cluster. To select genes for screening we prioritized first by identifying the transcripts most highly enriched throughout the dataset. Of those highly enriched transcripts, we then selected genes conserved in zebrafish. Finally, we honed primarily on genes coding for transcription factors (e.g. Irf8, Maf, Nfe2l2, Pou2f2, Spi1 ), cell-surface receptors (e.g. Ccr1, Nrp1, P2rx4, F11r, Csf1r, Fcgr3 ), and secreted proteins (e.g. Gas6 , Tgfb1, Ninj1, Mydgf ) due to their potential to drive large-scale changes in cell fate and communication. Since microglia are highly motile in order to scavenge and clear debris, we also included genes associated with cytoskeletal function to investigate their role in turnover (e.g. Arpc2, Arpc1b, Capg, Pfn1 ). The final screen list composed of 86 genes, 37 that were enriched only in the microglia precursor cluster, 43 that were enriched in mature microglia clusters, and 13 that were enriched in both mature and immature microglia (Table S1). Download figure Open in new tab Figure 1. A CRISPR-Cas9 screen reveals novel regulators of microglial lifespan and self-clearance. (A) UMAP representing all 13 clusters identified in our re-analysis of the Hammond et al., 2019 sc-seq data of E14.5 mouse microglia. (B) Expression of canonical microglia genes P2ry12 and Tmem119 across all 13 clusters shown in the UMAP plot of mouse microglia. (C) Heat map representing expression levels across all clusters to identify distinct embryonic microglia clusters in mice at E14.5. (D) Schematic of experimental timeline for CRISPR knockdown screen. (E) Max z-projection of 5 dpf Tg(pu1:Eos) microglia showing cannibalistic microglia in zebrafish. White arrowheads represent debris containing cannibalistic microglia. Magenta arrowheads represent non-debris containing microglia. (F-G) Quantification of the mean difference of (F) the number of cannibalistic microglia and (G) the ratio of cannibalistic cells compared to the total microglia population in zebrafish. P value calculated with Two-way ANOVA post doc Tukey’s, Cas9 vs geneX gRNA. (H) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) brains that were uninjected (wild-type), Cas9 only injected, or injected with Cas9 + gRNA for mef2ca/b , f11r.2 , arpc4 , or il10rb . Scale bar is 10 μm (E). To quantitatively analyze microglial cannibalism, we used the transgenic zebrafish line Tg ( pu1:Eos ) 57 , which expresses the photoconvertible protein Eos under the control of the microglia/macrophage-specific pu1 promoter. We achieved dual-color labeling of microglial progenitors by exposing zebrafish embryos to a 405 nm LED light array at 12 hours post-fertilization (hpf) ( Fig. 1D ) to selectively label a subset of microglia precursors that were expressing pu1 at 12 hpf 58 , 59 . Since some microglia precursors initiate pu1 expression after 12 hpf 60 , this early photoconversion created a mixed population of microglia at 4 dpf: some with only 488 Eos (these were non-photoconverted microglia that are pseudocolored cyan throughout images) and others with both 488 and 561 Eos (these were photoconverted microglia that are pseudocolored magenta throughout images). Embryos were grown to 4 dpf and imaged using a custom-built high-throughput robotic confocal microscope ( Fig. 1D ). The robot automatically positioned the midbrain of each animal to capture a 40 μm confocal z-stack. To quantify the effect of gene knockdown on microglia cannibalism, we quantified each image for the number of 488-Eos/cyan microglia that either contained 561-Eos/magenta debris (indicating a cannibalistic microglia) or did not contain 561-Eos debris (indicating a non-cannibalistic microglia) ( Fig. 1D ). This allowed us to quantify the number of cannibalistic microglia and the ratio of cannibalistic cells to the total microglial population. Our initial screen identified 19 genes that, when knocked down, significantly altered the number of cannibalistic microglia and/or ratio of cannibalistic microglia compared to the total population of microglia ( Fig. 1F-H , Fig. S1A-B ). The dominant outcome of the screen was the identification of genes required for efficient cannibalism. Notably, very few genes were found to increase either the raw number of cannibalistic microglia or the ratio of cannibalistic microglia ( Fig. 1F-H , Fig. S1A-B ). However, the presence of genes that both increase and decrease the number of cannibalistic microglia could suggest a network of genes that balance microglia cannibalism. Collectively, the dual nature of these hits, with genes promoting and restricting cannibalism, suggests that microglia function is not controlled by a simple linear pathway, but rather by a complex regulatory network of genes that fine-tune microglial phagocytic activity during development. Download figure Open in new tab Figure S1. Large scale CRISPR-Cas9 screen reveals perturbations in microglia cannibalism upon gene knockdown (A-B) Quantification of (A) the number of cannibalistic microglia (Cas9-injected vs. uninjected (-UV) p < 0.0001; Cas9-injected vs. arpc2 p = 0.0089; Cas9-injected vs. arpc4 p = 0.0003; Cas9-injected vs. clic1 p = 0.0227; Cas9-injected vs. clptm1 p < 0.0001; Cas9-injected vs. ehd4 p = 0.0159; Cas9-injected vs. f11r.2 p < 0.0001; Cas9-injected vs. gmfb p = 0.0376; Cas9-injected vs. ifngr1l p = 0.0009; Cas9-injected vs. il10rb p < 0.0001; Cas9-injected vs. irf8 p = 0.0038; Cas9-injected vs. litaf p < 0.0001; Cas9-injected vs. mpp1 p = 0.0072; Cas9-injected vs. mydgf p = 0.01; Cas9-injected vs. nfe2l2 p < 0.0001; Cas9-injected vs. ostf1 p = 0.0237; Cas9-injected vs. pdlim4 p = 0.0011; Cas9-injected vs. rogdi p = 0.015; Cas9-injected vs. selenop p < 0.0001; Cas9-injected vs. sh3bgrl3 p = 0.0014; Cas9-injected vs. shisa10.1 p = 0.0436; Cas9-injected vs. snx3 p = 0.0024; Cas9-injected vs. ssr4 p = 0.0002; Cas9-injected vs. tmem176l.1 p < 0.0001; Cas9-injected vs. tmem59 p < 0.0001; Cas9-injected vs. tyrobp p < 0.0001; Cas9-injected vs. vamp8 p = 0.0049; Cas9-injected vs. adipor1a/b p = 0.0005; Cas9-injected vs. arpc5a/b p < 0.0001; Cas9-injected vs. capga/b p = 0.0044; Cas9-injected vs. csf1ra/b p = 0.0038; Cas9-injected vs. mafa/b p = 0.0001; Cas9-injected vs. mef2ca/b p < 0.0001; Cas9-injected vs. msna/b p = 0.0172; Cas9-injected vs. spi1a/b p = 0.0004; Dunnett’s multiple comparisons test) and (G) the ratio of cannibalistic microglia (Cas9-injected vs. uninjected (-UV) p < 0.0001; Cas9-injected vs. clic1 p = 0.043; Cas9-injected vs. clptm1 p = 0.014; Cas9-injected vs. cotl1 p = 0.0026; Cas9-injected vs. ehd4 p = 0.0034; Cas9-injected vs. il10rb p < 0.0001; Cas9-injected vs. litaf p = 0.0001; Cas9-injected vs. mydgf p = 0.0196; Cas9-injected vs. nenf p = 0.0223; Cas9-injected vs. pdlim4 p = 0.0064; Cas9-injected vs. pepd p = 0.007; Cas9-injected vs. selenop p < 0.0001; Cas9-injected vs. snx3 p = 0.0259; Cas9-injected vs. ssr2 p = 0.018; Cas9-injected vs. tyrobp p = 0.0001; Cas9-injected vs. csf1ra/b p < 0.0001; Cas9-injected vs. mef2ca/b p < 0.0001; Cas9-injected vs. spi1a/b p < 0.0001; Dunnett’s multiple comparisons) compared to the total microglia population upon gene knockdown with CRISPR-Cas9 in 4 dpf Tg(pu1:Eos) animals. To confirm the top hits from our initial CRISPR-Cas9 screen, we performed a secondary validation screen on 18 genes that showed a statistically significant phenotype (P<0.05). We excluded csfr1a/b from our validation screening, despite the significant decrease in the ratio of cannibalistic microglia that we saw ( Fig. 1F ), because of its known dominant role in microglia colonization 61 . We used the same Tg( pu1:Eos ) line and high-throughput workflow ( Fig. 1C ) to quantify the number ( Fig. 2A ) and ratio ( Fig. 2B ) of cannibalistic microglia after knocking down each gene individually. The majority of the validated hits were found to promote cannibalism, as their perturbation resulted in a significant reduction in both the number and ratio of cannibalistic microglia ( Fig. 2A-B ). The validation screen successfully reproduced the phenotypes for 10 of the 18 genes, confirming their roles as robust regulators of microglial cannibalism. Download figure Open in new tab Figure 2. Validation and expression of candidate regulators of microglial cannibalism. (A-B) Quantification of (A) the total number of cannibalistic microglia (Cas9-injected vs. uninjected (−UV) p 0.9999, Cas9-injected vs. arpc4 p = 0.0171, Cas9-injected vs. cd68 p = 0.931, Cas9-injected vs. clic1 p = 0.0009, Cas9-injected vs. clptm1 p = 0.9951, Cas9-injected vs. f11r.2 p > 0.9999, Cas9-injected vs. gmfb p = 0.1903, Cas9-injected vs. il10rb p = 0.0015, Cas9-injected vs. irf8 p < 0.0001, Cas9-injected vs. litaf p = 0.9865, Cas9-injected vs. nfe2l2 p = 0.0365, Cas9-injected vs. pepd p = 0.0844, Cas9-injected vs. selenop p < 0.0001, Cas9-injected vs. tmem59 p = 0.9916, Cas9-injected vs. tyrobp p = 0.0136, Cas9-injected vs. vamp8 p = 0.751, Cas9-injected vs. arpc5a/b p = 0.9956, Cas9-injected vs. mafa/b p = 0.0019, Dunnett’s multiple comparisons) and (B) the ratio of cannibalistic microglia (Cas9-injected vs. uninjected (−UV) p 0.9999, Cas9-injected vs. arpc4 p = 0.0001, Cas9-injected vs. cd68 p = 0.0781, Cas9-injected vs. clic1 p < 0.0001, Cas9-injected vs. clptm1 p = 0.1957, Cas9-injected vs. f11r.2 p = 0.7573, Cas9-injected vs. gmfb p = 0.2435, Cas9-injected vs. il10rb p < 0.0001, Cas9-injected vs. irf8 p < 0.0001, Cas9-injected vs. litaf p = 0.7613, Cas9-injected vs. nfe2l2 p 0.9999, Cas9-injected vs. tyrobp p = 0.0007, Cas9-injected vs. vamp8 p > 0.9999, Cas9-injected vs. arpc5a/b p = 0.4278, Cas9-injected vs. mafa/b p = 0.0079, Cas9-injected vs. mef2ca/b p = 0.0017., Dunnett’s multiple comparisons) in 4 dpf Tg(pu1:Eos) knockdown animals and control animals. (C) Heatmap expression representing gene expression of validated knockdown genes among the 13 clusters. (D) UMAPs showing expression data in mouse microglia clusters of six validated knockdown genes ( Clic1, Irf8, Nfe2l2, Arpc4, and Mef2c ). (E) Quantification of the percent of cells in microglia clusters expressing Clic1, Irf8, Nfe2l2, Arpc4, and Mef2c . (F) Quantification of the percent of 4C4 + cells in zebrafish that are labeled with HCR RNA probes for clic1, irf8, nfe2l2, arpc4, mef2ca, and mef2cb (G) Representative confocal z-projections of 4 dpf animals stained for 4C4 and HCR RNA probes for clic1, irf8, nfe2l2, arpc4, mef2ca and mef2cb . White arrowheads represent microglia that express the HCR probe of interest. Scale bar represents 10 μm (G). Two-way ANOVA posthoc Dunnet’s multiple comparison (A,B). Analysis of the validated genes revealed that microglial turnover is governed by a diverse, multiplex regulatory network rather than a single pathway. All listed genes were successfully validated as significant regulators of microglial cannibalism, and they represented a broad array of functional categories that highlight this complex control. This network includes master transcription factors vital for microglial identity and cell fate, such as irf8 , mafa/b , and mef2ca/b , the latter being a noteworthy hit given its recently appreciated role in regulating microglial functions linked to autism risk and age-related disease 62 . Cytoskeletal genes like arpc4 , which is responsible for actin polymerization, also significantly affected microglia cannibalism, likely due to defects in movement from cytoskeletal disorganization 63 . The validation of genes related to the phagocytosis/efferocytosis machinery, including clic1 , which is known to be important for the acidification of phagolysosomes 64 , indicates that the physical process of engulfment and subsequent processing are tightly coupled. The identification of f11r.2 (a junctional adhesion molecule) also underscores the role of membrane organization and adhesion in completing this process. Finally, the validation of genes coding for the transmembrane proteins and receptors tyrobp and il10rb reveal the crucial roles of cell-extrinsic signals in regulating the self-clearance process. To determine if these genes are expressed in subtypes of embryonic microglia, we re-examined the scRNA-seq dataset 41 of mouse microglia for five of the validated hits, including clic1 , irf8 , nfe2l2 , arpc4 , and mef2ca/b . Each of these genetic modifiers of microglia cannibalism were enriched throughout the mouse microglia transcriptional clusters. UMAPs of each genetic modifiers demonstrated their robust expression throughout the microglia clusters, albeit with different amounts for each modifier ( Fig. 2C ). A heatmap also shows gene expression of modifiers across all clusters to show specificity of expression in microglia ( Fig. 2D ). We also calculated the percentage of mouse microglia that expressed each genetic modifier ( Fig. 2E ), demonstrating that most mouse microglia at E14.5 express each genetic modifier. To determine if this gene expression was conserved in a system that we could thoroughly investigate microglia necroptosis and cannibalism, we tested expression in vivo using hybridization chain reaction RNA-FISH (HCR RNA-FISH) combined with immunohistochemistry (IHC) on 4 dpf zebrafish animals. To probe for expression in microglia, we stained for 4C4, a microglia specific antibody in zebrafish 65 , 66 , along with a set of probes for RNA expression of six genes that were hits in our screen. We generated HCR probes for clic1 , irf8 , nfe2l2 , arpc4 , and mef2ca/b. After staining, we imaged the midbrains of the 4 dpf animals and scored the percent of 4C4 + microglia that express each HCR probe per individual ( Fig 2F-G ). This revealed that all six genes were expressed in a majority of 4C4 + microglia in the brain, validating their conserved potential roles in microglial cannibalism and lifespan ( Fig. 2F-G ). Taken together, the conserved expression of these genetic modifiers in the majority of microglia across E14.5 mouse and 4 dpf zebrafish brains strongly validates their potential roles as core, conserved, regulators of microglial cannibalism and lifespan during development. Among our validated hits, interleukin-10 receptor beta ( il10rb ) was a particularly compelling candidate. Its knockdown affected both the number of cannibalistic microglia and the ratio of cannibalistic microglia ( Fig. 2A-B ). Additionally, its canonical role in anti-inflammatory signaling and cell survival presented an intriguing paradox. Re-examining the scRNA-seq mouse dataset 41 , we found that Il10rb expression was highly specific to microglia clusters, with negligible expression in other brain cell types ( Fig. 3A ). We tested if this was conserved in zebrafish with HCR RNA-FISH and IHC, showing that approximately 87.88% ± 10.5% of 4C4-positive microglia expressed il10rb in 4 dpf animals ( Fig. 3B-C ). Given that IL10RB is a receptor for the cytokine interleukin-10 (IL10), we similarly explored the expression of il10 in microglia to potentially suggest a cell-autonomous signaling cascade. HCR-FISH revealed that about 65.75% ± 15.46% of 4C4 + microglia expressed the ligand, il10 , at 4 dpf ( Fig. 3B-C ). There were 4C4 - cells in the brain that also expressed il10rb and il10 ( Fig. 3C ). This expression supports the hypothesis that il10rb is expressed by most developmental microglia and that IL10 signaling components are in the brain to potentially regulate microglia. Download figure Open in new tab Figure 3. il10rb is a regulator of microglial lifespan (A) Expression of Il10rb across all 13 clusters shown in the UMAP plot of mouse microglia. (B) Quantification of the percent of 4C4 + cells (microglia) expressing il10rb and il10 in the zebrafish midbrain at 4 dpf. (C) Representative confocal z-projections showing 4C4 + microglia that express il10rb or il10 . White arrowheads represent microglia that express the HCR probe of interest. Magenta arrowheads represent microglia that do not express the HCR probe of interest. (D) Schematic of experimental timeline for studying effect il10rb or il10 knockdown on microglia lifespan and cannibalism. Six cells were targeted and photoconverted in 4 dpf Tg(pu1:Eos) animals that were injected with Cas9 only, Cas9 + il10rb gRNA, or Cas9 + il10 gRNA. Animals were grown to 5 dpf and their brains were reimaged for the presence of photoconverted microglia and cannibal microglia. (E-F) Quantification of the number of (E) 561-Eos microglia (Cas9 only vs. Cas9 + il10rb gRNA p = 0.0009, Cas9 only vs. Cas9 + il10 gRNA p = 0.0101, Cas9 + il10rb gRNA vs. Cas9 + il10 gRNA p = 0.6626, Tukey’s multiple comparisons test) and (F) total microglia (Cas9 only vs. Cas9 + il10rb gRNA p = 0.961, Cas9 only vs. Cas9 + il10 gRNA p = 0.1615, Cas9 + il10rb gRNA vs. Cas9 + il10 gRNA p = 0.0967, Tukey’s multiple comparisons test) in 5 dpf animals injected with Cas9 only, Cas9 + il10rb gRNA, or Cas9 + il10 gRNA. (G) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected Cas9 only, Cas9 + il10rb gRNA, or Cas9 + il10 gRNA. White arrowheads represent 561-Eos+/photoconverted microglia. Scale bars represent 20 μm (G). While our screen quantified cannibalism, this metric serves as an indirect readout of microglial turnover. A lower amount of cannibalistic microglia could indicate two most likely yet distinct biological possibilities: 1) Microglial death was reduced, meaning fewer corpses were available for clearance, or 2) The efficiency of efferocytosis (cannibalism) was impaired, meaning corpses were present but were not cleared. To distinguish between these possibilities for il10rb , we performed a survival assay after perturbation of il10 and il10rb with CRISPR. Guide efficiency for the CRISPR perturbation was confirmed by T7 endonuclease assay, which had an 87% indel efficiency ( Fig. S2A ). Only animals positive for an indel were used for quantification. We used Tg(pu1:Eos) animals and photoconverted six midbrain microglia at 4 dpf. We then re-imaged the same animals at 5 dpf to track the survival of the labeled cells ( Fig. 3D ). Control animals injected with Cas9 only animals retained an average of 2.9 ± 1.3 561-Eos cells, consistent with ongoing developmental cell death 38 . In contrast, Cas9 plus il10rb or il10 gRNA animals retained significantly more 561-Eos cells (5.4 ± 2.0 and 4.8 ± 1.4, respectively) ( Fig. 3E ). While it is possible that this increased cell persistence was associated with changes in the total microglial population at 5 dpf, scoring the total microglia abundance in each perturbation showed the statistically indistinguishable abundance of microglia, indicating that the effect was specific to individual cell lifespan rather than colonization or proliferation ( Fig. 3F-G ). Additionally, when the number of cannibalistic microglia were quantified at 5 dpf, there were fewer cannibalistic microglia in Cas9 plus il10 rb or il10 gRNA injected animals compared to Cas9 only injected animals ( Fig. S2B ) (4.5 ± 1.9 cannibalistic microglia in Cas9 only; 1.6 ± 1.3 cannibalistic microglia in Cas9 + il10rb gRNA; 2.2 ± 1.8 cannibalistic microglia in Cas9 + il10 gRNA). These results decisively separate the two possibilities, indicating that il10 and its receptor il10rb are necessary for developmental microglial death and that the reduction in cannibalism observed in our screen is a secondary consequence of the microglia surviving longer, suggesting that IL10 acts as a critical regulator of microglial turnover rate during development. Download figure Open in new tab Figure S2. il10rb + il10 Perturbation Leads to Microglial Dysfunction (A) Quantification of CRISPR-Cas9 lesion efficiency for il10rb gRNA (Cas9 only vs Cas9 + il10rb gRNA p < 0.0001; unpaired t-test). (B) Quantification of the number of cannibalistic microglia in Cas9 only, Cas9 + il10rb gRNA, or Cas9 + il10 gRNA (Cas9 only vs. Cas9 + il10rb gRNA p = 0.0004, Cas9 only vs. Cas9 + il10 gRNA p = 0.0055, Cas9 + il10rb gRNA vs. Cas9 + il10 gRNA p = 0.6311, Tukey’s multiple comparisons test). (C) Quantification of the number of microglia PBS and rhIL10 injected animals 24 hours post injection (PBS vs rhIL10 p = 0.2532; unpaired t-test). (D) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected with PBS or rhIL10 showing cCASP + cells and microglia. (E) Quantification of the total number of cCASP + cells in 5 dpf Tg(pu1:Eos) animals injected with PBS or rhIL10 (PBS vs rhIL10 p = 0.2666; unpaired t-test). (F) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected with cas9 only or cas9 + il10rb gRNA showing similar vacuole morphology. Given that perturbing il10rb or il10 increased the number of live, 561-Eos microglia at 5 dpf, we next investigated whether IL10 signaling actively promotes the developmental death of microglia. To directly test if exogenous IL10 could drive microglial death in vivo , we photoconverted six microglia in the midbrain of 4 dpf Tg(pu1:Eos) animals and immediately injected either recombinant human IL10 (rhIL10) or PBS (vehicle control) into the brain ventricles ( Fig. 4A ) We utilized recombinant human protein to further test the potential conservation of this process. We re-imaged the animals at 5 dpf to assess the fate of the labeled cells. In PBS-injected controls, an average of 4.0 ± 0.8 561-Eos microglia persisted, while rhIL10-injected animals retained only 2.1 ± 1.2 561-Eos microglia ( Fig. 4B ). This indicates that IL10 exposure significantly accelerated microglial removal between 4 and 5 dpf. To further confirm cell death, we quantified the number of cannibal microglia containing the remnants of dead microglia. rhIL10 injected animals had an average of 6.4 ± 2.8 cannibal microglia, double the 3.1 ± 1.1 cannibal microglia observed in PBS controls ( Fig. 4C-D ). Notably, total microglial abundance was unchanged, indicating that rhIL10 caused a selective loss of the labeled population rather than affecting colonization or proliferation ( Fig. S2C ). Download figure Open in new tab Figure 4. IL10 signaling drives microglial death via necroptosis. (A) Schematic of experimental timeline for studying effect of increased IL-10 signaling on microglia lifespan and cannibalism. Six cells were targeted and photoconverted in 4 dpf Tg(pu1:Eos) animals. After photoconversion, animals were injected with PBS or rhIL10 in their brain ventricles. Animals were grown to 5 dpf and their brains were reimaged for the presence of photoconverted microglia and cannibal microglia. (B-C) Quantification of the (B) number of 561-Eos microglia (PBS vs. rhIL10 p = 0.0004, PBS vs. Cas9 + il10rb gRNA + rhIL10 p = 0.0006, rhIL10 vs. Cas9 + il10rb gRNA + rhIL10 p < 0.0001; Tukey’s multiple comparisons test) and (C) number of cannibalistic microglia (PBS vs. rhIL10 p = 0.0423, PBS vs. Cas9 + il10rb gRNA + rhIL10 p = 0.1705, rhIL10 vs. Cas9 + il10rb gRNA + rhIL10 p = 0.0015; Tukey’s multiple comparisons test) in 5 dpf animals injected with PBS or rhIL10. (D) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected with PBS or rhIL10 showing photoconverted microglia and the presence of cannibal microglia. (E-F) Quantification of the (E) number of 561-Eos (rhIL10 +DMSO vs rhIL10 + Nec1 p < 0.0001; unpaired t-test) and (F) number of cannibalistic microglia (rhIL10 +DMSO vs rhIL10 + Nec1 p < 0.0001; unpaired t-test) in 5 dpf animals injected with rhIL10 and bath treated with DMSO or Nec1. (G) Representative confocal z-projections showing 5 dpf Tg(pu1:Eos) animals injected with rhIL10 and then bath treated with DMSO or Nec1 showing photoconverted microglia and photoconverted debris/presence of cannibalistic microglia. White arrowheads denote 561-Eos + photoconverted microglia (D,G). Magenta arrowheads denote 561-Eos + debris containing cannibalistic microglia (D,G). Scale bars represent 20 μm (D,G). If IL10 functions through the IL10RB receptor, we would expect that the effect of IL10 on microglia death would be eliminated in il10rb knockdown. To test this, we repeated the rhIL10 injection in Cas9 plus il10rb gRNA injected animals. As expected, the loss of receptor function abolished the pro-death effect. rhIL10 injection failed to reduce the number of 561-Eos microglia in il10rb gRNA injected animals (average 6.5 ± 1.4 561-Eos microglia), and yielded almost no cannibal microglia (0.4 ± 0.6 cannibalistic microglia) ( Fig. 4 B-D ). These results confirm that IL10 is sufficient to promote microglial death in vivo , and this activity is dependent on IL10RB-mediated signaling. With the role of IL10 in microglia death established, we next sought to identify the specific mechanism of cell death caused by IL10 signaling. We first tested for apoptosis, a common form of programmed cell death, by performing immunohistochemistry for the active form of caspase-3, cleaved caspase-3 (cCASP3), a canonical apoptotic marker. We found no cCASP3 + microglia in either PBS- or rhIL10-injected animals ( Fig. S2D ), indicating that apoptosis is not the primary mode of death. To confirm the effect was specific to microglia and not to other neural cell types, we also quantified the total number of cCASP3 + cells in the brain and found no change (34.4 ± 7.6 cCASP3 + cells per PBS injected animal; 38.9 ± 8.4 cCASP3 + cells per rhIL10 injected animal), suggesting IL10 is not acting on other neural cell types through caspase-mediation ( Fig. S2D-E ). We previously discovered that debris-burdened microglia die via necroptosis, and their corpses are subsequently cleared by neighboring microglia in a process termed microglia cannibalism 38 . Given that embryonic microglia are known to undergo necroptosis, we hypothesized that IL10 might instead be acting through this pathway. To test this, we co-treated rhIL10-injected animals with a necrostatin-1 (Nec-1) bath treatment, a specific RIPK1 inhibitor that blocks necroptosis 67 . Nec-1 treatment successfully rescued microglial survival, with animals retaining an average of 5.6 ± 1.0 561-Eos microglia compared to DMSO treated animals that only retained an average of 1.9 ± 1.2 561-Eos microglia ( Fig 4E ). Additionally, the Nec-1 treated animals only had an average of 0.4 ± 0.6 cannibalistic microglia compared to DMSO treated animals that had an average of 3.1 ± 1.4 cannibalistic microglia ( Fig 4F-G ). These findings strongly suggest that IL10 promotes microglial death via a necroptotic pathway in an il10rb -dependent manner. We next sought to determine the intracellular signaling cascade downstream of the IL10 receptor that leads to microglial death. Interleukin-10 receptor signaling is canonically known to activate the Janus kinase (JAK) and Signal Transducer and Activator of Transcription 3 (STAT3) pathway 43 . To test if this canonical pathway mediates the IL10-induced microglial death, we used a pharmacological approach to inhibit JAK and STAT3 activity. We first photoconverted six microglia in the midbrain of 4 dpf Tg(pu1:Eos) animals. Immediately following photoconversion, animals were treated with either DMSO (vehicle control), a pan JAK inhibitor (JAKi), or a STAT3 inhibitor (STAT3i). We then re-imaged the same animals at 5 dpf to assess the survival of the labeled cells ( Fig 5A ). In DMSO-treated control animals, we observed an average of 3.5 ± 1.3 561-Eos microglia remaining, consistent with the ongoing cell death seen in previous experiments ( Fig. 5B , Fig. 3E ). In stark contrast, animals treated with the STAT3i or JAKi retained an average of 5.8 ± 1.1 and 5.7 ± 0.8 561-Eos cells, respectively ( Fig 5B ). These results strongly suggest that both JAK and STAT3 signaling are required for the natural, developmental loss of microglia. Additionally, we quantified the number of cannibalistic microglia. JAKi and STAT3i treatment resulted in almost no cannibalistic microglia (an average of 0.2 ± 0.4 and 0.1 ± 0.3 cannibalistic microglia per animal, respectively), while DMSO-treated controls had an average of 2.4 ± 1.4 cannibalistic cells per animal, further supporting the conclusion that inhibiting this pathway prevents microglial death ( Fig 5C-D ). Download figure Open in new tab Figure 5. IL10 Signaling Promotes Microglial Death Through the JAK/STAT Pathway (A) Schematic of experimental timeline for studying effect of blocking JAK/STAT signaling on microglia lifespan and cannibalism. Six cells were targeted and photoconverted in 4 dpf Tg(pu1:Eos) animals. After photoconversion, animals were bath treated with DMSO, STAT3i, or JAKi. Animals were grown to 5 dpf and their brains were reimaged for the presence of photoconverted microglia and cannibal microglia. (B-C) Quantification of the (B) number of 561-Eos microglia (DMSO vs STAT3i p < 0.0001, DMSO vs JAKi p < 0.0001; Dunnett’s multiple comparisons test) and (C) number of cannibal microglia (DMSO vs STAT3i p < 0.0001, DMSO vs JAKi p < 0.0001; Dunnett’s multiple comparisons test) in 5 dpf animals bath treated with DMSO, STAT3i, or JAKi. (D) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals bath treated with DMSO, STAT3i, or JAKi showing photoconverted microglia and photoconverted debris containing presence of cannibalistic microglia. (E-F) Quantification of the (E) number of 561-Eos (cas9 + il10rb gRNA + DMSO vs cas9 + il10rb gRNA + STAT3i p = 0.1821; unpaired t-test) and (F) number of cannibal microglia (cas9 + il10rb gRNA + DMSO vs cas9 + il10rb gRNA + STAT3i p = 0.0962; unpaired t-test) in 5 dpf cas9 + il10rb gRNA bath treated with DMSO or STAT3i. (G) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) cas9 + il10rb gRNA animals bath treated with DMSO or STAT3i showing photoconverted microglia and presence of cannibal microglia. (H) Quantification of the number of 561-Eos microglia in 5 dpf rhIL10 injected animals bath treated with DMSO or JAKi. White arrowheads denote 561-Eos microglia (D,G). Magenta arrowheads denote 561-Eos+ debris containing cannibal microglia (D,G). Scale bars represent 20 μm (D,G). To confirm that JAK and STAT3 act in the same pathway as IL10RB, we first repeated the experiment in Cas9 plus il10rb gRNA injected animals. We treated Cas9 plus il10rb gRNA injected animals with either DMSO or STAT3i after photoconversion, and found no significant difference in the number of surviving 561-Eos microglia between the two groups (5.2 ± 1.0 561-Eos microglia in Cas9 plus il10rb gRNA injected + DMSO treated animals; 5.9 ± 1.0 561-Eos microglia in Cas9 plus il10rb gRNA injected + STAT3i treated animals) ( Fig 5E ). We also quantified the number of cannibalistic microglia and found no discernable difference between groups (0.8 ± 0.8 cannibalistic microglia Cas9 plus il10rb gRNA injected + DMSO treated animals; 0.2 ± 0.4 cannibalistic microglia Cas9 plus il10rb gRNA injected + STAT3i treated animals) ( Fig 5F-G ). The lack of an additive effect in the il10rb gRNA is consistent with the hypothesis that JAK activity is epistatic to IL10RB, supporting the idea that they function in the same signaling cascade. Finally, to directly link IL10 signaling to JAK activity, we tested whether JAK inhibition could block the pro-death effect of exogenous IL10. We injected rhIL10 into the brain ventricles of 4 dpf animals and then bathed the animals in DMSO or JAKi water. We found that JAKi treatment successfully rescued microglial survival, with animals retaining a high number of 561-Eos microglia, a result similar to JAKi treatment alone (1.9 ± 1.2 561-Eos microglia in rhIL10 + DMSO treated animals; 5.2 ± 0.7 561-Eos microglia in rhIL10 + JAKi treated animals) ( Fig 5H ). This confirms that the pro-death effect of IL10 is mediated through a JAK-dependent signaling pathway. Collectively, these findings demonstrate that IL10 signaling promotes microglial necroptosis by activating the canonical JAK/STAT pathway. This establishes a clear molecular cascade, linking the extracellular cytokine signal to the intracellular machinery that governs microglial lifespan during development. Our central model proposes that IL10 signaling acts as a quality control checkpoint, linking the phagocytic burden within a cell to the initiation of cell death. Having established that il10rb perturbation significantly reduces microglia death, we next investigated the relationship between IL10 signaling and the act of phagocytosis itself. Specifically, we tested if il10rb -mediated necroptosis required the presence of phagocytic activity. To address this, we performed a microglial survival assay on il10rb gRNA, treating them with either water (H 2 O) as a control or with O-phospho-L-serine (L-SOP), a known inhibitor of phagocytosis. L-SOP has been shown in our previous study to decrease microglia death 38 . Six microglia were photoconverted prior to drug treatment and animals were bath treated for 24 hours as done before ( Fig. 5A ). After 24 hours of treatment of L-SOP or H 2 O, we quantified the number of surviving photoconverted microglia and cannibal microglia in both groups. We found no significant difference in either the number of surviving 561-Eos cells (5.9 ± 1.1 561-Eos microglia per H 2 O treated il10rb gRNA; 5.8 ± 0.7 561-Eos microglia per L-SOP treated il10rb gRNA) or the number of cannibal microglia between the H2O- and L-SOP-treated il10rb gRNA (0.6 ± 0.7 cannibalistic microglia per H 2 O treated il10rb gRNA; 0.3 ± 0.5 cannibalistic microglia per L-SOP treated il10rb gRNA) ( Fig 6A-C ). This lack of an additive effect suggests that IL10 signaling acts downstream of, or in parallel with, the initial phagocytic engulfment signal, and that IL10RB and phagocytosis are components of the same cell biological process that regulates the final cell death decision. Download figure Open in new tab Figure 6. IL10 Signaling and Phagocytic Resolution (A-B) Quantification of the (A) number of 561-Eos (cas9 + il10rb gRNA + H2O vs cas9 + il10rb gRNA + L-SOP p = 0.7942; unpaired t-test) microglia and (B) number of cannibal microglia (cas9 + il10rb gRNA + H2O vs cas9 + il10rb gRNA + L-SOP p = 0.2462; unpaired t-test) in 5 dpf cas9 + il10rb gRNA animals bath treated with H 2 O or the phagocytosis inhibitor L-SOP. (C) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) cas9 + il10rb gRNA animals bath treated with H 2 O or L-SOP showing photoconverted microglia and photoconverted debris/presence of cannibal microglia. (D-E) Quantification of the (D) number of 561-Eos microglia (rhIL10 + H2O vs rhIL10 + L-SOP p < 0.0001; unpaired t-test) and (E) number of cannibal microglia (rhIL10 + H2O vs rhIL10 + L-SOP p = 0.0116; unpaired t-test) and in 5 dpf cas9 + il10rb gRNA animals bath treated with DMSO or STAT3i. (F) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected with rhIL10 and then bath treated with H 2 O or L-SOP showing photoconverted microglia and photoconverted debris/presence of cannibal microglia. (G-H) Quantification of the average (G) number (Cas9 only vs cas9 + il10rb gRNA p = 0.6614; unpaired t-test) and (H) diameter of vacuoles (Cas9 only vs cas9 + il10rb gRNA p = 0.2615); unpaired t-test) in cas9 only injected animals and cas9 + il10rb gRNA animals. White arrowheads denote 561-Eos+ microglia (C,F). Magenta arrowheads denote 561-Eos+ debris/cannibal microglia (C,F). Scale bars represent 20 μm (C,F). Conversely, we performed a related experiment to test if the cell death-promoting effect of IL10 over-activation is dependent on phagocytic activity. In this experiment, we again photoconverted six microglia per 4 dpf Tg(pu1:Eos) animal. We then injected rhIL10 into the brain ventricles to acutely increase IL10 signaling, and bath-treated the animals with either H2O (control) or the phagocytosis inhibitor L-SOP. As expected, rhIL10 administration significantly reduced the survival of photoconverted microglia in the rhIL10 + H2O group, but the addition of L-SOP rescued the dying microglia. (2.3 ± 1.0 561-Eos microglia per rhIL10 + H2O treated animal; 6.1 ± 0.7 561-Eos microglia per rhIL10 + LSOP treated animal) ( Fig 6D ). We also saw a similar trend when we quantified the number of cannibal microglia per treatment group, with the L-SOP treated animals having significantly fewer cannibalistic microglia (2.6 ± 1.1 cannibalistic microglia per rhIL10 + H2O treated animal; 1.0 ± 0.8 cannibalistic microglia per rhIL10 + L-SOP treated animal) ( Fig 6 E-F ). This lack of an additive effect in the il10rb gRNA, coupled with the rescue of IL10-induced death by L-SOP, suggests that IL10 signaling acts downstream of, or in parallel with, the initial phagocytic engulfment signal, and that IL10RB and phagocytosis are components of the same cell biological process that regulates the final cell death decision. Given that the sheer volume of phagocytosed material represents an acute degradative burden that requires active regulation of lysosomal capacity, we first considered that IL10 signaling might be involved in regulating lysosomal dynamics. Phagocytosed material is processed within phagolysosomes, which appear as prominent debris-containing vacuoles in Tg(pu1:Eos) animals 38 . Given that these large vacuoles accumulate in the setting of intense phagocytic demand at 4 dpf and previous work confirms they contain various types of neural debris, we assessed them as the likely functional phagolysosomal compartments. However, lacking a specific secondary marker to assign them as phagolysosomes, phagosomes, or autophagic structures, we hereby refer to them simply as vacuoles. We therefore hypothesized that loss of IL10 signaling would alter the number or size of these vacuoles. To test this, we quantified the number of microglial vacuoles in Cas9-only control and il10rb gRNA in 4 dpf Tg(pu1:GAL4;UAS:GFP ) animals, focusing on the number and diameter of vacuoles. This analysis revealed no significant difference in either the number (3.5 ± 2.7 vacuoles per cas9 only animal; 3.2 ± 2.8 vacuoles per il10rb gRNA) or the average diameter of vacuoles (6.1 ± 2.8 micrometers per cas9 only microglia; 5.4 ± 2.6 micrometers per il10rb gRNA microglia) between the two groups ( Fig 6G-H ) and thereby inconsistent with the hypothesis that IL10 signaling is required for the physical formation or maturation of the phagolysosome. Based on the morphological consistency between groups, we infer that the IL10 signaling does not regulate the structure of the phagolysosome, which prompted us to next investigate if it plays a role in functional capacity. Given no gross changes in the number or size of vacuoles, we considered the hypothesis that the biochemistry of the phagocytic machinery could be regulated by IL10. Specifically, given that STAT3 (the key downstream mediator of IL10) is known to regulate v-ATPase pumps 52 , we focused on lysosomal acidification as the most likely functional target. Lysosome pH is the critical determinant of degradative efficiency and has been shown to be a major checkpoint for cell fate 25 , 68 . We hypothesized that il10rb knockdown would impair lysosomal acidification. To explore that, we used LysoTracker Red, a fluorescent probe that specifically accumulates in and labels acidic compartments, to assess lysosomal pH in microglia. We quantified the number of LysoTracker + puncta per microglia in Cas9 + il10rb gRNA injected animals at 4 dpf and compared them to Cas9-only control animals. Our analysis revealed that microglia in il10rb perturbed animals had significantly fewer LysoTracker + puncta, demonstrating a clear defect in lysosomal acidification when IL10 signaling is disrupted (8.1 ± 3.3 LysoTracker + puncta per cas9 only animal; 4.9 ± 1.9 3 LysoTracker + puncta per Cas9 + il10rb gRNA animal) ( Fig 7A-B ). This key finding establishes a mechanistic link between the IL10RB/STAT3 signaling axis and the failure of lysosomal processing. Download figure Open in new tab Figure 7. IL-10 Signaling Regulates Microglial Survival via Lysosomal Acidification (A) Quantification of the number of LysoTracker+ inclusions per microglia (Cas9 only vs cas9 + il10rb gRNA p < 0.0001; unpaired t-test) in cas9 only injected animals and cas9 + il10rb gRNA animals. (B) Representative confocal z-projections and IMARIS surface renderings of 4 dpf Tg(pu1:Eos) animals injected with cas9 only or cas9 + il10rb gRNA animals stained with LysoTracker showing acidified lysosome compartments within microglia. (C-D) Quantification of the (C) number of 561-Eos microglia (DMSO vs BafA1 p = 0.0113; unpaired t-test) and (D) number of cannibal microglia (DMSO vs BafA1 p = 0.0368; unpaired t-test) in 5 dpf animals bath treated with DMSO or lysosomal acidification inhibitor BafA1. (E) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals bath treated with DMSO or BafA1 showing photoconverted microglia and photoconverted debris/presence of cannibalisti microglia. (F-G) Quantification of the number of (F) 561-Eos microglia (rhIL10 + DMSO vs rhIL10 + BafA1 p < 0.0001; unpaired t-test) and (G) cannibalistic microglia (rhIL10 + DMSO vs rhIL10 + BafA1 p = 0.0003; unpaired t-test) in 5 dpf rhIL10 injected animals bath treated with DMSO or BafA1. (H) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) animals injected with rhIL10 and bath treated with DMSO or BafA1 showing photoconverted microglia and photoconverted debris/presence of cannibal microglia. White arrowheads denote 561-Eos+ microglia (E,H). Magenta arrowheads denote 561-Eos+ debris/ cannibalistic microglia (E,H). Scae bars represent 10 μm (B) and 20 μm (E,H). If the acidification of lysosomes is critical for microglia death, potentially regulated via IL10 signaling, then independently altering lysosomal acidification should impact microglial death. To further test the link between lysosomal acidification and microglial death, we used bafilomycin A1 (BafA1), a specific inhibitor of v-ATPase, the proton pump responsible for acidifying lysosomes. We hypothesized that inhibiting acidification would phenocopy the survival phenotype of il10rb perturbation. We photoconverted six microglia in 4 dpf Tg(pu1:Eos) animals and treated them with either DMSO or BafA1. Consistent with our hypothesis, BafA1-treated animals showed a significant increase in the number of surviving 561-Eos+ cells (4.8 ± 0.9 561-Eos microglia per DMSO treated animal; 6.4 ± 1.3 561-Eos microglia per BafA1 treated animal) and a concomitant decrease in cannibalistic microglia compared to DMSO controls (2.0 ± 1.4 cannibalistic microglia per DMSO treated animal; 0.6 ± 0.9 cannibalistic microglia per BafA1 treated animal) ( Fig 7C-E ). This provides strong evidence that lysosomal acidification is a key determinant of microglial fate following phagocytosis. Given that our model predicts that the pro-necroptotic effect of IL10 is mediated by driving lysosomal acidification, we hypothesiszed that pharmacologically blocking acidification would rescue microglia from IL10 induced death. To test this, we injected rhIL10 into the brain ventricles and simultaneously treated the animals with BafA1. The BafA1 treatment successfully negated the pro-death effect of IL10, with survival rates similar to those of BafA1 treatment alone (3.0 ± 1.4 561-Eos microglia per rhIL10 + DMSO treated animal; 5.9 ± 0.9 561-Eos microglia per rhIL10 + BafA1 treated animal), and similarly there were fewer cannibalistic microglia in BafA1 treated animals compared to DMSO treatment (2.7 ± 1.5 cannibal microglia per rhIL10 + DMSO treated animal; 0.6 ± 0.6 cannibal microglia per rhIL10 + BafA1 treated animal) ( Fig 7F-H ). This is consistent with the hypothesis that the lysosomal acidification pathway is a crucial downstream effector of IL10 signaling in driving microglial death. The simplest explanation for this collective data is that IL10 signaling promotes microglial necroptosis by regulating lysosomal acidification, revealing that the very process required for efficient phagocytosis also serves as the critical checkpoint for triggering cell turnover. Our findings suggest that IL10 signaling promotes the turnover of phagocytically-burdened cells, establishing a key quality control mechanism. Failure of this mechanism results in the persistence of cells that, though living, are potentially functionally compromised due to the chronic phagocytic stress. Therefore, we next explored the consequences of having longer-lived, il10rb -deficient microglia in the context of a neuroimmune challenge. To specifically assess the impact of less microglia turnover on acute injury resolution, we utilized a laser ablation model to induce a focal brain injury in the midbrain, creating a controlled, high-volume source of neural debris that resident microglia must clear. This model was chosen because it allows for a precise, repeatable injury in vivo , enabling us to track the dynamics of debris clearance and injury resolution over time, providing a relevant functional readout for the clearance efficiency of the microglial population. We performed this experiment on 4 dpf Tg(pu1:Eos) animals. We photoconverted six microglia per animal, performed a laser ablation injury 50 μm below the surface of the skin in the midbrain, and then re-imaged the same animals at 5 dpf to assess survival and morphology. We compared three groups: wild-type (WT) animals with injury, il10rb gRNA-injected animals with injury, and il10rb perturbations with a mock injury. We first examined the overall microglial population in the lesion site to assess the general neuroimmune response to injury. Previous work has shown that the microglia population expands in response to injury. To investigate if il10rb perturbation had an effect on this injury response, we quantified the total number of microglia within the imaging window 24 hours post injury (hpi). The total number of microglia in both injured groups ( il10rb gRNA and WT) was significantly higher than in the mock-injured group, confirming a typical expansion of the microglial population in response to injury, however, there was no difference in the total microglial count between the two injured groups (17.0 ± 5.1 microglia per mock injured il10rb gRNA; 25.6 ± 4.9 microglia per injured il10rb gRNA; 25.2 ± 3.6 microglia per injured WT animal) ( Fig 8A ). We had initially hypothesized that because il10rb mediates microglia death, il10rb perturbed animals would retain a higher number of surviving photoconverted 561-Eos cells. Interestingly, while the mock-injured il10rb perturbation retained a high number of 561-Eos microglia (consistent with inhibited microglial developmental death), the injured il10rb gRNA-injected animals and WT animals both showed a significant reduction in the number of surviving 561-Eos cells (5.9 ± 0.7 561-Eos microglia per mock injured il10rb gRNA; 4.0 ± 1.0 561-Eos microglia per injured il10rb gRNA; 3.7 ± 0.8 photoconverted microglia per injured WT animal) ( Fig 8B-C ). This suggests that the IL10 mediated quality control mechanism that governs developmental microglia turnover is superseded by a more potent, injury-induced cell death pathway, potentially as phagocytic stress reaches a severe acute threshold. Download figure Open in new tab Figure 8. il10rb Perturbation Leads to Microglial Dysfunction and Impaired Resolution After Injury (A-B) Quantification of the (A) total number of microglia (Cas9 + il10rb gRNA + mock injury vs. il10rb gRNA + injury p = 0.0079; Cas9 + il10rb gRNA + mock injury vs. WT + injury p = 0.0147; Cas9 + il10rb gRNA + injury vs. WT + injury p = 0.9865; Tukey’s multiple comparisons test) and (B) number of 561-Eos microglia (Cas9 + il10rb gRNA + mock injury vs. il10rb gRNA + injury p = 0.002; Cas9 + il10rb gRNA + mock injury vs. WT + injury p = 0.0006; Cas9 + il10rb gRNA + injury vs. WT + injury p = 0.7624; Tukey’s multiple comparisons test) in mock-injured Cas9 + il10rb gRNA animals, injured Cas9 + il10rb gRNA animals, and injured Cas9 only injected animals. (C) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) mock-injured Cas9 + il10rb gRNA animals, injured Cas9 + il10rb gRNA animals, and injured cas9 only injected animals (D) Quantification of the average percent of normal and highly vacuolated microglia in Cas9 + il10rb gRNA animals that were mock-injured or injured. (E) Representative confocal z-projections of 5 dpf Tg(pu1:Eos) mock-injured Cas9 + il10rb gRNA animals and injured Cas9 + il10rb gRNA animals showing microglia morphology. (F) Quantification of the nbt - lesion size in 5 dpf Tg(nbt:dsRed) Cas9 only injected animals and il10rb gRNA injected animals (Cas9 only vs cas9 + il10rb gRNA p = 0.0102; unpaired t-test with Welch’s correction). White arrowheads denote 561-Eos+ microglia (C). Magenta arrowheads denote 561-Eos + debris containing cannibal microglia (C). Scale bars represent 20 μm (C). Next, we investigated whether the failure of IL10 mediated death led to a defect in the remaining microglial function. While we observed that acute injury triggers significant microglial death even in il10rb perturbed animals, the surviving cells in these animals that escaped death may have accumulated chronic phagocytic stress from injury clearance. We therefore hypothesized that these surviving, compromised cells would display signs of morphological breakdown and functional failure when exposed to the severe stress of an acute injury. Indeed, we observed a profound difference in microglial morphology following 24 hpi via laser ablation. In the injured il10rb perturbed animals, 60% exhibited a highly rounded, vacuolated phenotype while only 40% of microglia displayed a normal, ramified morphology ( Fig. 8D-E ). In contrast, microglia in the mock-injured il10rb gRNA maintained a largely normal appearance (85.7% showing normal morphology). Crucially, we found virtually no microglia with this abnormally vacuolated morphology in the injured WT control group ( Fig. 8D-E ). This direct comparison highlights that the vacuolated phenotype is not a generic response to injury but is specifically linked to the absence of proper IL10 signaling. This observation strongly suggests that the vacuolated phenotype represents a state of chronic cellular stress and dysfunctional debris clearance in the long-lived, il10rb -deficient cells. To evaluate the consequence of this dysfunctional microglial state, we quantified the resolution of the tissue lesion following injury. We performed the same focal laser ablation in Tg(nbt:dsRed) animals, which fluorescently labels neurons, allowing us to quantify the size of the tissue lesion. We compared Cas9-only controls to il10rb gRNA 24 hours post-injury. The lesion size was significantly larger in il10rb gRNA compared to Cas9-only controls (1452 ± 435.3 pixels 2 per cas9 only animal; 2703 ± 1297 pixels 2 per il10rb gRNA) ( Fig. 8F ). This demonstrates that the failure to execute the IL10RB-driven quality control mechanism—resulting in the persistence of longer-lived, but dysfunctional, microglia—directly leads to impaired debris clearance and delayed resolution of tissue damage in vivo . Discussion This work supports a model that IL10 signaling promotes microglial death. This process is essential for maintaining a healthy, functional population of microglia capable of responding effectively to injury and clearing debris. The longer-lived microglia when IL10 signaling is disrupted are functionally compromised under conditions of high phagocytic demand, exhibiting characteristics of resolution failure due to impaired lysosomal function. This further supports the model that the IL10/necroptosis paradigm is a quality control mechanism designed to eliminate stressed, defective phagocytes to ensure optimal tissue repair and remodeling. Overall, we hypothesize that during periods of intense phagocytic demand in early brain development, IL10 signaling functions as a direct mechanism to refine the microglia population of phagocytically burdened cells. Following IL10 binding, JAK/STAT3 signaling is initiated. Although not directly linked to IL10 as the signal initiator, work has found that activated STAT3 translocates to the phagolysosome membrane and physically associates with the V-ATPASE complex, directly promoting rapid acidification 52 . While initially protective and helpful for cargo degradation, we suspect the chronic demand leads to the hyper-activation of this STAT3-mediated acidification. Mechanistically, we propose this sustained hyper-acidification, combined with the accumulation of debris, could compromise lysosomal membrane integrity, triggering LMP, which is a known driver of necroptosis 69 . This catastrophic failure releases lysosomal contents into the cytosol, which could initiate the observed necroptotic cell death pathway in microglia 38 . Our finding that il10rb knockdown reduces microglial death is therefore consistent with removing the signal that actively drives the lysosomal system towards necroptosis. IL10 Signaling Governs Microglial Turnover via a Lysosomal Quality Control Mechanism In this study, we utilized a high-throughput CRISPR-Cas9 screen and single-cell in vivo tracking in the larval zebrafish to identify the molecular mechanisms regulating microglial turnover during development. Our key findings establish a signaling cascade wherein the cytokine IL10 acts as a pro-death signal through its accessory receptor, IL10RB, to actively promote the necroptosis of phagocytic microglia. Mechanistically, we demonstrate that this effect is mediated through the canonical JAK/STAT3 axis, and that IL10 signaling is essential for maintaining lysosomal acidification. Building on previous literature that establishes that STAT3 physically associates with and regulates the v-ATPase proton pump 52 , we hypothesize that this is the direct molecular link by which the axis control lysosomal pH. By tuning this critical pH checkpoint, the IL10-IL10RB-JAK-STAT3 axis links the stress of intense efferocytosis to a regulated cell death decision, resulting in the cannibalistic clearance of necroptotic microglia. We propose that this IL10-driven necroptosis process functions as a self-limiting quality control mechanism to ensure the developing brain maintains a population of healthy, functional phagocytes. IL10-STAT3 Axis as a Core Regulator of Lysosomal Integrity and Cell Fate Our work provides a crucial mechanistic link between a major inflammatory signaling pathway and the ultimate decision of cell death. The convergence of IL10/STAT3 signaling on lysosomal function is particularly compelling. Canonical STAT3 activity is generally associated with cell survival and proliferation 70 , 71 , yet we found that inhibiting STAT3 rescued microglial lifespan ( Fig. 5 ). This seemingly contradictory role is resolved by our discovery that the IL10-IL10RB-JAK-STAT3 signaling axis is required to maintain the proper acidic environment (pH) of the lysosome ( Fig. 7 ). This finding strongly supports a mechanism, established in previous literature, which shows that STAT3 directly associates with the v-ATPase proton pump and increases its activity 52 . In the context of the highly burdened phagocytic microglia, we hypothesize that IL10-mediated acidification is a double-edged sword: it is required for successful debris degradation, but in the face of continuous, high-volume efferocytosis, this intense v-ATPase activity also drives the lysosome toward a state of fatal stress, leading to eventual lysosomal membrane permeabilization (LMP) and the initiation of RIPK1-dependent necroptosis 72 , 73 . This is strongly supported by our finding that the microglia death effect of exogenous IL10 is abrogated by Nec−1 treatment, a specific pharmacological inhibitor of RIPK1 ( Fig 4 ). Therefore, IL10 does not promote death directly, but rather tunes the lysosome to a high-activity state that is necessary for function but predisposes the cell to death under overwhelming stress. The demonstration that BafA1 (a v-ATPase inhibitor) completely phenocopied the survival effect of il10rb knockdown ( Fig. 5 ), and that it eliminated the microglia death effect of exogenous IL10, strongly supports the lysosomal pH as a critical execution point of this developmental mechanism. The IL10 signal, therefore, acts as a systemic regulator of phagocytic efficiency and risk, essentially setting the threshold for resolution failure. Linking Developmental Turnover to Disease Resolution Our finding that il10rb -deficient microglia, while longer-lived, exhibit severe morphological dysfunction and a highly vacuolated phenotype following injury ( Fig. 8 ) has significant implications for our understanding of neuroimmune cell longevity in disease. This phenotype is indicative of a stalled clearance state or phagocytic overload, where the microglia survive the initial death signal but are functionally incapable of resolving their internalized cargo. The failure of phagocytes to die and be replaced is increasingly recognized as a major driver of chronic, non-resolving inflammation in pathologies such as atherosclerosis 26 , 28 , 35 , 37 and advanced aging 74 , 75 . Our model suggests that the IL10-driven necroptosis is a developmentally conserved mechanism to prevent the accumulation of these dysfunctional, "resolution-failed" phagocytes. By rapidly eliminating the damaged cells, the genetic pathway ensures the tissue is populated by a new, high-functioning cohort of microglia capable of responding effectively to subsequent challenges. This paradigm moves beyond viewing IL−10 simply as an anti-inflammatory agent, revealing its capacity to orchestrate the strategic removal of immune cells as a prerequisite for tissue-level resolution. Limitations and Future Directions While this work establishes a clear signal-to-fate pathway, several questions remain. Our study focuses on the IL10RB subunit, which pairs with IL10Rα to form the functional receptor; future work should explore the specific role of IL10RA and the full heterodimer complex. Furthermore, although we demonstrated a strong link between IL10 and lysosome acidification, the precise molecular nature of their interaction within microglia will need to be tested in future publications. Future studies should also confirm that STAT3 physically associates with the v-ATPase complex in microglia. Finally, given that IL10 is broadly expressed, it will be crucial to distinguish the contributions of the microglial cell-autonomous IL10 signal from potential signals originating from neurons, glia, or other cell types, especially under conditions of injury. Ultimately, translating this developmental mechanism to adult disease models will determine whether pharmacologically targeting the IL10/STAT3/v-ATPase axis can be used to promote the necessary turnover and rejuvenation of phagocyte populations in chronic inflammatory conditions. Author Contribution HG, JD, AD, ZMK, RAA, KC, CC, and CH performed experimentation. HG and DG performed the analysis. HG, JD, AD, and CJS supervised the project. HG and CJS conceived, wrote, and edited the manuscript and funded the project. Competing Interest Statement The authors declare no competing interests. Methods Ethics Statement Experimental procedures followed the NIH guide for the care and use of laboratory animals. The University of Notre Dame IACUC, which is guided by the United States Department of Agriculture, the Animal Welfare Fact (USA), and the Assessment and Accreditation of Laboratory Animal Care International approved all animal studies under protocol 22-07-7322 and 25-05-9326 to Cody J. Smith. Contact for Reagent and Resource Sharing All data collected for the study are included in the figures and supplemental data. Reagent requests can be directed to the corresponding author. Custom Code Custom code used to generate the figures can be found at https://github.com/RavenGan/Microglia . Experimental Model and Subject Details Zebrafish strains in this study include: AB (wild-type), Tg(pu1:Eos) nt20076 , Tg(pu1:GAL4, UAS:GFP) zf1496 , and Tg(nbt:dsRed) zf1486 . Only stable transgenic lines were used in this study. To produce embryos, pairwise matings were used. Animals were raised at 28 °C in egg water in constant darkness and staged by hours or days post fertilization (hpf and dpf), confirmed by observation of developmental milestones 77 . Embryos were raised in 0.003% phenylthiourea (PTU) egg water from 24 hpf – 4 dpf to prevent pigment development. Embryos were used for all experiments. Method Details scRNAseq Analysis The microglia scRNAseq data were downloaded from GSE121654 32 . Pre-processing, normalization, and clustering were performed using Seurat as described previously 78 . In Vivo Imaging Animals were anesthetized using 3-aminobenzoic acid ester (Tricaine), and submerged in 0.8% low-melting point agarose, and mounted dorsally in glass-bottomed 35 mm Petri dishes as previously described 79 . Custom confocal microscopes, built by 3i technology (Denver, Colorado, United States of America) was used for all imaging. All mounted animals were imaged with a 40X (1.1NA) objective. Images were processed with Adobe Illustrator, ImageJ, and IMARIS. Only brightness and contrast were adjusted and enhanced for images represented in this study. Screening Robot Imaging A robot equipped with a Vast BIOImager (Union Biometrica) and a custom built confocal microscope from 3i technology (Denver, Colorado) was used for high-throughput screening 78 . The microscope includes: Zeiss Axio Examiner Z1, CSU-W1 T1 Spinning Disk Confocal (50 μm disk) equipped with mSwitcher, dichroics and lasers for 405/488/561/640 and a 95B Back Illuminated Scientific CMOS. Animals were anesthetized and placed in a 96-well plate prior to imaging. Immunohistochemistry and Hybridization Chain Reaction (HCR)-Fluorescence In Situ Hybridization (FISH) The primary antibodies used were anti-4C4 (1:50, mouse 65 ) and anti-cleaved Caspase3 (1:700, rabbit, BD Biosciences). The secondary antibodies used were Alexa Fluor 647 goat anti-mouse (1:600, Thermo Fisher, A-21235) and Alexa Fluor 647 goat anti-rabbit (1:600, Thermo Fisher, A-21245). Animals were fixed at 4 dpf and 5 dpf in 4% paraformaldehyde in 0.1% PBS Triton-X. HCR-FISH was used in combination with IHC and was performed using the standard protocol (Molecular Instruments, HCR RNA-FISH v3.0 protocol for whole-mount zebrafish larvae) on 4 dpf fixed animals to detect irf8 , clic1 , nfe2l2 , arpc4 , mef2ca/b , il10 , and il10rb expression. Probes targeting these genes were custom designed. CRISPR-Cas9 Screen and Knockdown Targeted CRISPR-Cas9 Mutagenesis for Screen CRISPR-Cas9 mutagenesis was performed by co-injecting a pool of 3-4 guide RNAs (gRNAs) targeting a single gene and 2 μM EnGen Spy Cas9 NLS (New England Biolabs) into Tg(pu1:Eos) embryos at the 1-cell stage. Candidate genes for knockdown were chosen from a re-analysis of a published scRNA-seq dataset of E14.5 mouse microglia 41 . gRNAs were made using the online program CHOPCHOP. The following parameters were used: gRNAs are be 20 bp in length, begin with GA, and have no off targets with fewer than 3 bp matches. Screen Workflow After gRNA and Cas9 injection, injected embryos were grown to 12 hours post fertilization (hpf). To allow for mosaic labeling of microglia, at 12 hpf, embryos were exposed to 405 nm light using two, 5 second pulses of light from an LED flood system (Loctite 97070). After photoconversion, animals were grown to 4 dpf in PTU egg water. The 4 dpf animals were randomly selected and imaged on a custom-built robot. Hits were validated using the same CRISPR-Cas9 protocol with individual gRNA pools. Targeted CRISPR-Cas9 Mutagenesis for il10 and il10rb CRISPR-Cas9 mutagenesis was performed by co-injecting two guide RNAs (gRNAs) targeting a single exon within each gene and Alt-R S.p. Cas9 Nuclease V3 protein (Integrated DNA Technologies, 1081058) into Tg(pu1:Eos) embryos at the 1-cell stage. Crispants were confirmed with T7 endonuclease assay. T7 Endonuclease Assay A T7 endonuclease I (New England Biolabs, M0302SVIAL) assay was performed to determine if an indel was created at or near the exon of interest and to determine guide efficiency. The assay was carried out according to New England Biolabs protocol instructions. Only animals with digested PCR product (indicating an indel) were kept in for analysis. Six-cell Photoconversions and Survival Tracking Tg(pu1:Eos) embryos at 4 dpf were used. Six individual microglia in the midbrain were selected and photoconverted using a 5-ms 405-nm-laser pulse with the mVector system (3i). Pre- and post-conversion images were taken in the 488 nm and 561 nm channels. Survival was assessed by tracking the persistence of the 561-Eos cells and by the presence of cannibal microglia at 5 dpf. Drug Treatments Chemical Bath Treatments Working solutions were administered by diluting the drug in PTU egg water at 4 dpf immediately after photoconversion. Signaling Inhibitors: A pan JAK inhibitor (JAKi; CAS 457081-03-7; Sigma-Aldrich, Cat# CC1000) was used at 1 μM 80 . A STAT3 inhibitor (STAT3i; S31-201; Sigma-Aldrich, Cat# 573130) was used at 400 μM 80 . Cell Death Inhibitors: Necrostatin-1 (Nec-1; RIPK1 inhibitor; MedChemExpress LLC, HY-15760) was used at 10 μM 38 . Lysosome acidification inhibitor: the selective inhibitor of the vacuolar-type H + -ATPase, Bafilomycin A1 (BafA1;Sigma-Aldrich, SML1661) was used at 25 nM 81 . Phagocytosis Inhibitor: O-Phospho-L-serine (L-SOP; Sigma, Sigma, P0878-10MG) was used at 1 μM 38 . All embryos were incubated in egg water until 24 hpf and incubated with PTU until desired treatment time. Fish were treated at 4 dpf, immediately after photoconversions and/or injections. Control fish were incubated with 0.1% DMSO in PTU or H 2 O in PTU. rhIL10 Injection Following the photoconversion protocol, embryos were carefully unmounted from their dorsal position. They were then briefly re-anesthetized using Tricaine in PTU egg water and remounted ventrally (head facing up) in a glass-bottom dish with a small amount of low-melt agarose to stabilize the head and expose the brain ventricle. Recombinant human IL10 (rhIL10; R&D Systems; 217-IL-005/CF) was injected into the brain ventricle at 25 μg/ml using a glass micro-injection needle connected to a micro-injector. Vehicle control injections consisted of PBS. Following injection, embryos were immediately unmounted and placed in PTU egg water or the appropriate bath treatment (e.g., Nec-1, BafA1, etc.) to recover until 5 dpf imaging. Lysosomal Acidification and Vacuole Quantification LysoTracker Staining Lysosomal acidification was assessed by bathing 4 dpf animals in LysoTracker Red DND-99 (Thermo Fisher; L7528) at 1 μM for 1 hour prior to imaging. Embryos were rinsed three times with PTU egg water prior to mounting. LysoTracker-positive puncta within individual microglia were manually counted across the z-stack. Vacuole Quantification Vacuole number and size were quantified in Tg(pu1:GAL4; UAS:GFP) fish at 4 dpf. Vacuoles were defined as GFP - inclusions fully contained within the GFP + cytoplasm of the microglia. Laser Ablation Injury Focal brain injury was induced in Tg(pu1:Eos) 4 dpf animals using the Ablate! Photoablation System (532 nm pulsed laser) in the midbrain 40 μm below the skin surface as previously described 38 . Sham-injured fish followed the same mounting procedure but received only a 561 nm laser exposure. Quantification and Statistics Statistical Analysis Microglia z-stack images were generated using 3i Slidebook software. Three-dimensional surface renderings of microglia were created using IMARIS (Notre Dame Imaging Core). All quantifications were executed using various plug-ins available in FIJI (ImageJ) and Microsoft Excel. Statistical analyses were performed using GraphPad Prism (version 8) software. All graphical data represent both the mean and individual values unless otherwise noted. No statistical methods were used to predetermine sample sizes; sample sizes were informed by previous publications. All statistical tests were run using biological replicates, not technical replicates. Healthy animals were randomly selected for inclusion, and no data points were excluded from analysis. Data distribution was assumed to be normal, but this was not formally tested. Data collection and analysis were performed blind to the experimental conditions unless otherwise indicated. Each experiment was repeated at least twice with similar results. Softwares ImageJ and Slidebook were used to produce and process confocal images. IMARIS was used to generate 3D surface renderings. Graphpad prism was used to generate all graphs and statistical analysis. Adobe Illustrator was used to compile the figures. Gemini was used for editing of the manuscript. All text in the manuscript has been reviewed by the authors for accuracy after Gemini edits. Acknowledgements We thank Beth Stevens, Jordan Doman, Anna Kane and members of the Stevens’ lab for their thoughtful comments. We also thank current and previous members of the Smith Lab for insightful discussions. Thanks to 3i for aiding with imaging related questions, Sara Cole of the Notre Dame Integrated Imaging Facility for assisting with IMARIS, and Deborah Bang for zebrafish housing and upkeep. This work was supported by the University of Notre Dame, the Elizabeth and Michael Gallagher Family, Centers for Zebrafish Research and Stem Cells and Regenerative Medicine at the University of Notre Dame, the SMART foundation (CJS), NIH (DP2NS117177) and Chan Zuckerberg Initiative (CP-2-1-Smith). Funder Information Declared Smart Foundation Chan Zuckerberg Initiative (United States), https://ror.org/02qenvm24 , CP-2-1-Smith NIH , DP2NS117177 REFERENCES 1. ↵ Paolicelli , R. C. et al. Microglia states and nomenclature: A field at its crossroads . Neuron 110 , 3458 – 3483 ( 2022 ). OpenUrl CrossRef PubMed 2. ↵ Hong , S. & Stevens , B . Microglia: Phagocytosing to Clear, Sculpt, and Eliminate . Dev Cell 38 , 126 – 128 ( 2016 ). OpenUrl CrossRef PubMed 3. ↵ Márquez-Ropero , M. , Benito , E. , Plaza-Zabala , A. & Sierra , A . Microglial Corpse Clearance: Lessons From Macrophages . Front Immunol 11 , 522783 ( 2020 ). 4. ↵ VanRyzin , J. W. et al. Erratum: Microglial Phagocytosis of Newborn Cells Is Induced by Endocannabinoids and Sculpts Sex Differences in Juvenile Rat Social Play (Neuron (2019) 102(2) (435–449.e6), (S0896627319301151) , ( doi: 10.1016/j.neuron.2019.02.006 )). Neuron 110 , 1271 ( 2022 ). OpenUrl CrossRef PubMed 5. Cunningham , C. L. , Martínez-Cerdeño , V. & Noctor , S. C . Microglia Regulate the Number of Neural Precursor Cells in the Developing Cerebral Cortex . Journal of Neuroscience 33 , 4216 – 4233 ( 2013 ). OpenUrl Abstract / FREE Full Text 6. Peri , F. & Nüsslein-Volhard , C . Live Imaging of Neuronal Degradation by Microglia Reveals a Role for v0-ATPase a1 in Phagosomal Fusion In Vivo . Cell 133 , 916 – 927 ( 2008 ). OpenUrl CrossRef PubMed Web of Science 7. Ashwell , K . Microglia and cell death in the developing mouse cerebellum . Brain Res Dev Brain Res 55 , 219 – 230 ( 1990 ). OpenUrl CrossRef PubMed 8. ↵ Zhao , J. et al. Efferocytosis in the Central Nervous System . Front Cell Dev Biol 9 , 773344 ( 2021 ). 9. Möller , K. et al. A role for the centrosome in regulating the rate of neuronal efferocytosis by microglia in vivo . Elife 11 , ( 2022 ). 10. Xiao , Y. et al. The reduction of microglial efferocytosis is concomitant with depressive-like behavior in CUMS-treated mice . J Affect Disord 352 , 76 – 86 ( 2024 ). OpenUrl PubMed 11. ↵ Hamilton , N. et al. The failure of microglia to digest developmental apoptotic cells contributes to the pathology of RNASET2-deficient leukoencephalopathy . Glia 68 , 1531 ( 2020 ). OpenUrl CrossRef PubMed 12. ↵ Boada-Romero , E. , Martinez , J. , Heckmann , B. L. & Green , D. R . The clearance of dead cells by efferocytosis . Nature Reviews Molecular Cell Biology 2020 21:7 21 , 398 – 414 ( 2020 ). OpenUrl PubMed 13. ↵ Doran , A. C. , Yurdagul , A. & Tabas , I. Efferocytosis in health and disease . Nature Reviews Immunology 2019 20:4 20 , 254 – 267 ( 2019 ). OpenUrl PubMed 14. ↵ Cunningham , C. L. , Martínez-Cerdeño , V. & Noctor , S. C . Microglia Regulate the Number of Neural Precursor Cells in the Developing Cerebral Cortex . Journal of Neuroscience 33 , 4216 – 4233 ( 2013 ). OpenUrl Abstract / FREE Full Text 15. ↵ Szondy , Z. , Garabuczi , É. , Joós , G. , Tsay , G. J. & Sarang , Z . Impaired clearance of apoptotic cells in chronic inflammatory diseases: therapeutic implications . Front Immunol 5 , ( 2014 ). 16. ↵ Kawano , M. & Nagata , S. Efferocytosis and autoimmune disease . Int Immunol 30 , 551 – 558 ( 2018 ). OpenUrl CrossRef PubMed 17. ↵ Abiega , O. et al. Neuronal Hyperactivity Disturbs ATP Microgradients, Impairs Microglial Motility, and Reduces Phagocytic Receptor Expression Triggering Apoptosis/Microglial Phagocytosis Uncoupling . PLoS Biol 14 , e1002466 ( 2016 ). OpenUrl CrossRef PubMed 18. ↵ Sierra-Torre , V. et al. Microglial phagocytosis dysfunction in the dentate gyrus is related to local neuronal activity in a genetic model of epilepsy . Epilepsia 61 , 2593 – 2608 ( 2020 ). OpenUrl CrossRef PubMed 19. ↵ Mehrotra , P. & Ravichandran , K. S . Drugging the efferocytosis process: concepts and opportunities . Nature Reviews Drug Discovery 2022 21:8 21 , 601 – 620 ( 2022 ). OpenUrl CrossRef PubMed 20. ↵ Medina , C. B. et al. Metabolites released from apoptotic cells act as tissue messengers . Nature 580 , 130 – 135 ( 2020 ). OpenUrl CrossRef PubMed 21. Yan , Q. et al. Metabolic reprogramming in efferocytosis . Front Cell Dev Biol 13 , 1677028 ( 2025 ). 22. ↵ Yurdagul , A . Metabolic Consequences of Efferocytosis and its Impact on Atherosclerosis . Immunometabolism 3 , e210017 ( 2021 ). OpenUrl 23. ↵ Scott , O. , Saran , E. & Freeman , S. A . The spectrum of lysosomal stress and damage responses: from mechanosensing to inflammation . EMBO Rep 26 , 1425 – 1439 ( 2025 ). OpenUrl CrossRef PubMed 24. Becker , L. et al. A macrophage sterol-responsive network linked to atherogenesis . Cell Metab 11 , 125 – 135 ( 2010 ). OpenUrl CrossRef PubMed Web of Science 25. ↵ Zhu , S. yu , et al. Lysosomal quality control of cell fate: a novel therapeutic target for human diseases . Cell Death Dis 11 , 817 ( 2020 ). OpenUrl CrossRef PubMed 26. ↵ Tabas , I . Apoptosis and plaque destabilization in atherosclerosis: The role of macrophage apoptosis induced by cholesterol . Cell Death Differ 11 , ( 2004 ). 27. Makuch , M. , Stepanechko , M. & Bzowska , M . The dance of macrophage death: the interplay between the inevitable and the microenvironment . Front Immunol 15 , 1330461 ( 2024 ). OpenUrl PubMed 28. ↵ De Meyer , G. R. Y. , Zurek , M. , Puylaert , P. & Martinet , W . Programmed death of macrophages in atherosclerosis: mechanisms and therapeutic targets . Nature Reviews Cardiology 2024 21:5 21 , 312 – 325 ( 2024 ). OpenUrl PubMed 29. ↵ Greenhalgh , A. D. & David , S . Differences in the Phagocytic Response of Microglia and Peripheral Macrophages after Spinal Cord Injury and Its Effects on Cell Death . Journal of Neuroscience 34 , 6316 – 6322 ( 2014 ). OpenUrl Abstract / FREE Full Text 30. ↵ Wang , B. et al. Disruption of USP9X in macrophages promotes foam cell formation and atherosclerosis . J Clin Invest 132 , ( 2022 ). 31. ↵ Yuan , Y. , Li , P. & Ye , J . Lipid homeostasis and the formation of macrophage-derived foam cells in atherosclerosis . Protein Cell 3 , 173 – 181 ( 2012 ). OpenUrl CrossRef PubMed 32. ↵ Li , W. et al. Defective macrophage efferocytosis in advanced atherosclerotic plaque and mitochondrial therapy . Life Sci 359 , 123204 ( 2024 ). OpenUrl PubMed 33. ↵ Poznyak , A. V. , Nikiforov , N. G. , Starodubova , A. V. , Popkova , T. V. & Orekhov , A. N . Macrophages and Foam Cells: Brief Overview of Their Role , Linkage, and Targeting Potential in Atherosclerosis. Biomedicines 9 , 1221 ( 2021 ). OpenUrl PubMed 34. ↵ Moore , K. J. & Tabas , I . Macrophages in the Pathogenesis of Atherosclerosis . Cell 145 , 341 – 355 ( 2011 ). OpenUrl CrossRef PubMed Web of Science 35. ↵ Li , H. et al. Macrophage Subsets and Death Are Responsible for Atherosclerotic Plaque Formation . Front Immunol 13 , 843712 ( 2022 ). OpenUrl PubMed 36. ↵ Erbay , E. et al. Reducing endoplasmic reticulum stress through a macrophage lipid chaperone alleviates atherosclerosis . Nat Med 15 , 1383 – 1391 ( 2009 ). OpenUrl CrossRef PubMed 37. ↵ Tabas , I . Macrophage death and defective inflammation resolution in atherosclerosis . Nature Reviews Immunology 2009 10:1 10 , 36 – 46 ( 2009 ). OpenUrl PubMed 38. ↵ Gordon , H. , Schafer , Z. T. & Smith , C. J . Microglia cannibalism and efferocytosis leads to shorter lifespans of developmental microglia . PLoS Biol 22 , e3002819 ( 2024 ). OpenUrl PubMed 39. ↵ Dhuriya , Y. K. & Sharma , D . Necroptosis: a regulated inflammatory mode of cell death . Journal of Neuroinflammation 2018 15:1 15 , 1 – 9 ( 2018 ). OpenUrl PubMed 40. ↵ Ye , K. , Chen , Z. & Xu , Y . The double-edged functions of necroptosis . Cell Death & Disease 2023 14:2 14 , 1 – 12 ( 2023 ). OpenUrl PubMed 41. ↵ Hammond , T. R. et al. Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes . Immunity 50 , 253 – 271 .e6 ( 2019 ). OpenUrl CrossRef PubMed 42. ↵ Verma , R. et al. A network map of Interleukin-10 signaling pathway . J Cell Commun Signal 10 , 61 ( 2015 ). OpenUrl PubMed 43. ↵ Riley , J. K. , Takeda , K. , Akira , S. & Schreiber , R. D . Interleukin-10 Receptor Signaling through the JAK-STAT Pathway . Journal of Biological Chemistry 274 , 16513 – 16521 ( 1999 ). OpenUrl Abstract / FREE Full Text 44. ↵ Shemer , A. et al. Interleukin-10 Prevents Pathological Microglia Hyperactivation following Peripheral Endotoxin Challenge . Immunity 53 , 1033 – 1049 .e7 ( 2020 ). OpenUrl CrossRef PubMed 45. ↵ Yogev , N. et al. CD4+ T-cell-derived IL-10 promotes CNS inflammation in mice by sustaining effector T cell survival . Cell Rep 38 , 110565 ( 2022 ). OpenUrl PubMed 46. ↵ Krishnamurthy , P. et al. Interleukin-10 deficiency impairs bone marrow-derived endothelial progenitor cell survival and function in ischemic myocardium . Circ Res 109 , 1280 – 1289 ( 2011 ). OpenUrl Abstract / FREE Full Text 47. ↵ Fluckiger , A.-C. , Durand , I. & Banchereau , J. Interleukin 10 Induces Apoptotic Cell Death of B-Chronic Lymphocytic Leukemia Cells . 48. Skrypnyk , M. et al. Interleukin-10 induces TNF-driven apoptosis and ROS production in salivary gland cancer cells . Heliyon 10 , e31777 ( 2024 ). OpenUrl 49. Ayala , A. , Chung , C. S. , Song , G. Y. & Chaudry , I. H . IL-10 MEDIATION OF ACTIVATION-INDUCED Th1CELL APOPTOSIS AND LYMPHOID DYSFUNCTION IN POLYMICROBIAL SEPSIS . Cytokine 14 , 37 – 48 ( 2001 ). OpenUrl CrossRef PubMed Web of Science 50. Tung , T. C. , Oshima , K. , Cui , G. , Laks , H. & Sen , L . Dual upregulation of Fas and Bax promotes alloreactive T cell apoptosis in IL-10 gene targeting of cardiac allografts . doi: 10.1152/ajpheart.00976.2002 285 , ( 2003 ). OpenUrl CrossRef PubMed Web of Science 51. ↵ Speiran , K. et al. Endogenous suppression of mast cell development and survival by IL-4 and IL-10 . J Leukoc Biol 85 , 826 – 836 ( 2009 ). OpenUrl CrossRef PubMed Web of Science 52. ↵ Liu , B. et al. STAT3 associates with vacuolar H+-ATPase and regulates cytosolic and lysosomal pH . Cell Res 28 , 996 ( 2018 ). OpenUrl CrossRef PubMed 53. ↵ Adeshakin , F. O. et al. Upregulation of V-ATPase by STAT3 Activation Promotes Anoikis Resistance and Tumor Metastasis . J Cancer 12 , 4819 ( 2021 ). OpenUrl PubMed 54. ↵ Song , Q. , Meng , B. , Xu , H. & Mao , Z . The emerging roles of vacuolar-type ATPase-dependent Lysosomal acidification in neurodegenerative diseases . Translational Neurodegeneration 2020 9:1 9 , 1 – 14 ( 2020 ). OpenUrl PubMed 55. ↵ Abu-Remaileh , M. et al. Lysosomal metabolomics reveals V-ATPase- and mTOR-dependent regulation of amino acid efflux from lysosomes . Science (1979) 358 , 807 – 813 ( 2017 ). OpenUrl Abstract / FREE Full Text 56. ↵ Wyczanska , M. et al. Interleukin-10 enhances recruitment of immune cells in the neonatal mouse model of obstructive nephropathy . Scientific Reports 2024 14:1 14 , 1 – 13 ( 2024 ). OpenUrl PubMed 57. ↵ Green , L. A. , O’Dea , M. R. , Hoover , C. A. , DeSantis , D. F. & Smith , C. J . The embryonic zebrafish brain is seeded by a lymphatic-dependent population of mrc1+ microglia precursors . Nature Neuroscience 2022 25:7 25 , 849 – 864 ( 2022 ). OpenUrl CrossRef PubMed 58. ↵ Wang , Y. et al. Essential Role of RIG-I in Hematopoietic Precursor Emergence in Primitive Hematopoiesis during Zebrafish Development . Immunohorizons 6 , 283 – 298 ( 2022 ). OpenUrl Abstract / FREE Full Text 59. ↵ Liu , Y. et al. Genetic Deletion of miR-430 Disrupts Maternal-Zygotic Transition and Embryonic Body Plan . Front Genet 11 , 568845 ( 2020 ). OpenUrl 60. ↵ Huang , M. et al. Negative Elongation Factor (NELF) Inhibits Premature Granulocytic Development in Zebrafish . Int J Mol Sci 23 , 3833 ( 2022 ). OpenUrl PubMed 61. ↵ Ginhoux , F. et al. Fate Mapping Analysis Reveals That Adult Microglia Derive from Primitive Macrophages . Science (1979) 330 , 841 – 845 ( 2010 ). OpenUrl Abstract / FREE Full Text 62. ↵ Nguyen , C. et al. Transcriptional and epigenetic targets of MEF2C in human microglia contribute to cellular functions related to autism risk and age-related disease . Nat Immunol 26 , 1989 – 2003 ( 2025 ). OpenUrl PubMed 63. ↵ Laboy Cintron , D. , et al. A recurrent, de novo pathogenic variant in ARPC4 disrupts actin filament formation and causes microcephaly and speech delay . Human Genetics and Genomics Advances 3 , 100072 ( 2022 ). OpenUrl 64. ↵ Jiang , L. et al. Intracellular chloride channel protein CLIC1 regulates macrophage function through modulation of phagosomal acidification . J Cell Sci 125 , 5479 – 5488 ( 2012 ). OpenUrl Abstract / FREE Full Text 65. ↵ Mazzolini , J. et al. Gene expression profiling reveals a conserved microglia signature in larval zebrafish . Glia 68 , 298 – 315 ( 2020 ). OpenUrl CrossRef PubMed 66. ↵ Rovira , M. et al. Zebrafish Galectin 3 binding protein is the target antigen of the microglial 4C4 monoclonal antibody . Developmental Dynamics 252 , 400 – 414 ( 2023 ). OpenUrl CrossRef PubMed 67. ↵ Degterev , A. et al. Chemical inhibitor of nonapoptotic cell death with therapeutic potential for ischemic brain injury . Nat Chem Biol 1 , 112 – 119 ( 2005 ). OpenUrl CrossRef PubMed Web of Science 68. ↵ Mindell , J. A. Lysosomal acidification mechanisms . Annu Rev Physiol 74 , 69 – 86 ( 2012 ). OpenUrl CrossRef PubMed Web of Science 69. ↵ Wang , F. , Gómez-Sintes , R. & Boya , P . Lysosomal membrane permeabilization and cell death . Traffic 19 , 918 – 931 ( 2018 ). OpenUrl CrossRef PubMed 70. ↵ Ding , B. B. et al. Constitutively activated STAT3 promotes cell proliferation and survival in the activated B-cell subtype of diffuse large B-cell lymphomas . Blood 111 , 1515 – 1523 ( 2008 ). OpenUrl Abstract / FREE Full Text 71. ↵ Samad , M. A. et al. STAT3 Signaling Pathway in Health and Disease . MedComm (Beijing) 6 , e70152 ( 2025 ). OpenUrl 72. ↵ Zhu , S. yu , et al. Lysosomal quality control of cell fate: a novel therapeutic target for human diseases . Cell Death & Disease 2020 11:9 11 , 1 – 13 ( 2020 ). OpenUrl PubMed 73. ↵ Zou , J. et al. Poly IC Triggers a Cathepsin D- and IPS-1-Dependent Pathway to Enhance Cytokine Production and Mediate Dendritic Cell Necroptosis . Immunity 38 , 717 – 728 ( 2013 ). OpenUrl CrossRef PubMed Web of Science 74. ↵ Nwadiugwu , M . RNA-seq analysis of phagocytic cells from murine epididymal white adipose tissue shows immunosenescence and age-related phosphorus metabolism . Human Cell 2022 35:2 35 , 572 – 582 ( 2022 ). OpenUrl PubMed 75. ↵ Li , W . Phagocyte dysfunction, tissue aging and degeneration . Ageing Res Rev 12 , 1005 – 1012 ( 2013 ). OpenUrl CrossRef PubMed 76. Green , L. A. , O’Dea , M. R. , Hoover , C. A. , DeSantis , D. F. & Smith , C. J . The embryonic zebrafish brain is seeded by a lymphatic-dependent population of mrc1+ microglia precursors . Nature Neuroscience 2022 25:7 25 , 849 – 864 ( 2022 ). OpenUrl CrossRef PubMed 77. ↵ Kimmel , C. B. , Ballard , W. W. , Kimmel , S. R. , Ullmann , B. & Schilling , T. F . Stages of embryonic development of the zebrafish . Developmental Dynamics 203 , 253 – 310 ( 1995 ). OpenUrl CrossRef PubMed Web of Science 78. ↵ Hoover , C. A. , Dennen , J. , Gan , D. , Li , J. & Smith , C. J. sox17 mutagenesis reveals microglia can be impacted by genetic maternal effects . bioRxiv https://doi.org/10.1101/2025.07.30.667678 ( 2025 ) doi: 10.1101/2025.07.30.667678 . OpenUrl Abstract / FREE Full Text 79. ↵ Nichols , E. L. & Smith , C. J . Pioneer axons employ Cajal’s battering ram to enter the spinal cord . Nat Commun 10 , ( 2019 ). 80. ↵ Kikel-Coury , N. L. et al. Identification of astroglia-like cardiac nexus glia that are critical regulators of cardiac development and function . PLoS Biol 19 , e3001444 ( 2021 ). OpenUrl CrossRef PubMed 81. ↵ Khuansuwan , S. , Barnhill , L. M. , Cheng , S. & Bronstein , J. M . A novel transgenic zebrafish line allows for in vivo quantification of autophagic activity in neurons . Autophagy 15 , 1322 – 1332 ( 2019 ). OpenUrl CrossRef PubMed Back to top Previous Next Posted November 21, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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