Repopulation of the brain with microglia-like cells following intraperitoneal bone marrow cell transfer in microglia-deficient mice

Repopulation of the brain with microglia-like cells following intraperitoneal bone marrow cell transfer in microglia-deficient mice | 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 Repopulation of the brain with microglia-like cells following intraperitoneal bone marrow cell transfer in microglia-deficient mice Isis Taylor , Omkar L. Patkar , Yajun Liu , Sebastien Jacquelin , Ginell Ranpura , Dylan Carter-Cusack , View ORCID Profile Adam Ewing , Nyoman D. Kurniawan , Mosi Li , Deepali Vasoya , Xin He , View ORCID Profile Owen R. Dando , Peter Kind , Giles E. Hardingham , View ORCID Profile Barry M. Bradford , View ORCID Profile Neil A. Mabbott , Lucas LeFevre , Clare Pridans , Kim M. Summers , Katharine M. Irvine , David A. Hume doi: https://doi.org/10.1101/2025.01.16.633478 Isis Taylor 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Omkar L. Patkar 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yajun Liu 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sebastien Jacquelin 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ginell Ranpura 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dylan Carter-Cusack 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Adam Ewing 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Adam Ewing Nyoman D. Kurniawan 2 Australian Institute for Bioengineering and Nanotechnology, Centre for Advanced Imaging, The University of Queensland , St. Lucia, Qld 4072, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mosi Li 3 UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, Edinburgh Medical School , EH16 4SB, UK 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Deepali Vasoya 3 UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, Edinburgh Medical School , EH16 4SB, UK 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Xin He 3 UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, Edinburgh Medical School , EH16 4SB, UK 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK 5 Simons Initiative for the Developing Brain, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Owen R. Dando 3 UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, Edinburgh Medical School , EH16 4SB, UK 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK 5 Simons Initiative for the Developing Brain, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Owen R. Dando Peter Kind 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK 5 Simons Initiative for the Developing Brain, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Giles E. Hardingham 3 UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, Edinburgh Medical School , EH16 4SB, UK 4 Centre for Discovery Brain Sciences, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK 5 Simons Initiative for the Developing Brain, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Barry M. Bradford 6 The Roslin Institute, University of Edinburgh , Easter Bush, Midlothian, EH25 9RG, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Barry M. Bradford Neil A. Mabbott 6 The Roslin Institute, University of Edinburgh , Easter Bush, Midlothian, EH25 9RG, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Neil A. Mabbott Lucas LeFevre 7 Centre for Inflammation Research, Institute for Regeneration and Repair. University of Edinburgh , Edinburgh, EH16 4TJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Clare Pridans 5 Simons Initiative for the Developing Brain, University of Edinburgh , Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK 7 Centre for Inflammation Research, Institute for Regeneration and Repair. University of Edinburgh , Edinburgh, EH16 4TJ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kim M. Summers 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Katharine M. Irvine 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: David.Hume{at}uq.edu.au Katharine.Irvine{at}uq.edu.au David A. Hume 1 Mater Research Institute-University of Queensland, Translational Research Institute , Woolloongabba, Brisbane, Qld 4102, Australia Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: David.Hume{at}uq.edu.au Katharine.Irvine{at}uq.edu.au Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Germ-line deletion of a conserved enhancer (the Fms intrinsic regulatory element, FIRE) in the mouse Csf1r locus causes congenital absence of microglia. Homozygous FIRE deletion on a C57BL/6J background leads to perinatal lethality and hydrocephalus (HC) in surviving pups. We developed a congenic C57BL/6J line with defined regions of non-C57BL/6J genomic DNA, increased postnatal viability and reduced incidence of HC. Both perinatal lethality and HC were eliminated in F2 mice following outcross of the congenic line to CBA/J or BALBc/J backgrounds. To assess the impacts of microglial deficiency in postnatal neurodevelopment we analyzed deep total RNA-seq data from multiple brain regions of wild-type and Csf1r ΔFIRE/ΔFIRE mice. Aside from the loss of microglial-specific transcripts, we found no significant alterations in relative abundance of any cell-type or region-specific transcriptomic signature. Transcripts associated with endosome/lysosome function, which are enriched in microglia, were not affected, suggesting compensatory expression by other cell types. On the C57BL/6J x CBA/J F2 background, congenital absence of microglia did not affect motor activity, behavior or myelination up to 7 months of age but was associated with astrocytosis and calcification in the thalamus. In the congenic C57BL/6J Csf1r ΔFIRE/ΔFIRE mouse line, intraperitoneal transfer of wild-type bone marrow cells (BMT) at weaning led to complete repopulation of the brain with microglia-like cells without giving rise to monocytic intermediates. Our results suggest novel strategies for treatment of microglial deficiency. Introduction Early in vertebrate development, the brain is populated by phagocytes derived from the yolk sac and fetal liver, which eventually give rise to multiple populations of tissue resident macrophages including microglia and brain-associated or border macrophage populations ( Prinz et al., 2021 ; Van Hove et al., 2019 ). In the postnatal period, microglia and a further wave of recruited monocytes are actively involved in phagocytic clearance of excess neurons and synapses. Together, these populations are proposed to support or modify neurogenesis, oligodendrocyte function and myelination, and astrocyte function ( Askew et al., 2017 ; Carrier et al., 2024 ; Chen et al., 2020 ; Leong and Ling, 1992 ; Mehl et al., 2022 ; Paolicelli et al., 2022 ; Perry et al., 1985 ; Prinz et al., 2021 ; You et al., 2024 ). Compared to other cells of the mononuclear phagocyte system, microglia have a distinct gene expression profile ( Summers et al., 2020 ). Their clearance and trophic functions are believed to be mediated by a wide range of secreted factors and receptors including IGF1, BDNF, C1Q, CX3CR1, TREM2, MARCO and P2RY12 ( Paolicelli et al., 2022 ; You et al., 2024 ). The evidence supporting an essential role for microglia in development depends largely upon ablation of the cells or conditional deletion of genes encoding specific effectors via cre-mediated recombination ( Faust et al., 2023 ). The differentiation, proliferation and survival of tissue macrophage populations depends upon signals from the CSF1R tyrosine kinase receptor ( Hume et al., 2020 ). CSF1R-deficient mice and rats lack microglia and brain-associated macrophages ( Erblich et al., 2011 ; Patkar et al., 2021 ). The Csf1r locus contains an intronic super-enhancer (Fms intronic regulatory element; FIRE) that is conserved from reptiles to humans ( Hume et al., 2017 ). Deletion of this element from the mouse genome produced a surprising outcome. Unlike Csf1r -/- mice, which are severely osteopetrotic and growth-restricted, Csf1r ΔFIRE/ΔFIRE mice grew normally and were long-lived and fertile ( Rojo et al., 2019 ). They lack yolk sac macrophages, are almost entirely macrophage deficient in the embryo ( Munro et al., 2020 ) and lack microglia and specific tissue macrophages populations in the adult ( Rojo et al., 2019 ). Csf1r ΔFIRE/ΔFIRE mice have been used as a model to explore the roles of microglia in models of neurodegeneration, with results suggesting their function is primarily neuroprotective ( Bradford et al., 2022 ; Chadarevian et al., 2024 ; Kiani Shabestari et al., 2022 ; Munro et al., 2024 ). A recent study found microglia were not required in postnatal oligodendrocyte development and myelination but contributed to myelin maintenance with age ( McNamara et al., 2023 ). Although synaptic pruning is said to be necessary for normal brain development, the original descriptions of this function found only a small delay in response to microglial dysfunction ( Paolicelli et al., 2011 ; Schafer et al., 2012 ). We ( O’Keeffe et al., 2024 ) and others (Surala-M et al., 2024) found no detectable effect of the lack of microglia on synaptic maturation in multiple brain regions in microglia-deficient Csf1r ΔFIRE/ΔFIRE mice suggesting functional redundancy. Csf1r -/- and Csf1r ΔFIRE/ΔFIRE mice were each originally generated and analyzed on a mixed genetic background ( Dai et al., 2002 ; Rojo et al., 2019 ). Homozygous Csf1r mutation on inbred C57BL/6J background produces perinatal lethality ( Chitu et al., 2016 ; Percin et al., 2018 ), whereas on a FVB/J background, Csf1r -/- mice develop severe hydrocephalus (HC) and few survive to weaning ( Erblich et al., 2011 ). HC is also a feature of homozygous recessive CSF1R mutation in rats ( Pridans et al., 2018 ) and humans ( Dulski et al., 2023 ). Csf1r ΔFIRE/ΔFIRE mice have also been analysed as a model for microglial deficiency in patients. McNamara et al . ( McNamara et al., 2023 ) reported age-dependent impacts on myelin integrity and two recent studies described calcification and neuronal loss in the thalamus that could be prevented by microglial transplantation ( Chadarevian et al., 2024 ; Munro et al., 2024 ). Here we examine the effect of the congenital absence of microglia on gene expression, development, function and pathology in the mouse brain as a model for human microglial deficiency, the interaction between Csf1r ΔFIRE/ΔFIRE mutation and mouse genetic background and repopulation of the vacant brain niche by wild-type bone marrow cells. Results Csf1r ΔFIRE/ΔFIRE mutation leads to selective loss of microglial-specific transcripts throughout the brain There have been a number of studies claiming that Csf1r is expressed by neurons (reviewed in Chitu et al., 2022 ). To address the issue, we crossed the Csf1r -FusionRed knock-in transgenic reporter which reports CSF1R protein synthesis ( Grabert et al., 2020 ) to the widely used Cx3cr1- EGFP microglia-specific reporter. We found complete overlap of the two reporters with each other and with the microglial marker IBA1 in all brain regions, including the hippocampal dentate gyrus ( Figure 1A ) and cortex ( Figure 1B ). There was no evidence of expression of either reporter in neurons. Figure 1B also confirms the complete overlap between the Csf1r- EGFP transgenic reporter ( Sasmono et al., 2003 ) and IBA1 as reported by others ( Askew et al., 2017 ; Erblich et al., 2011 ). Figure 1C shows FACS analysis of the two transgenes in isolated microglia and brain-associated macrophages (BAM) defined by expression of CD45 and CD11b. Consistent with their high expression of Csf1r mRNA, Cx3cr1 -EGFP + microglia uniformly express high levels of FusionRed (FRed) and F4/80. The non-microglial CD11b low /CD45 high population likely includes Cx3cr1 -EGFP high BAM and Cx3cr1 -EGFP high monocytes, both retained in Csf1r ΔFIRE/ΔFIRE mice ( Rojo et al., 2019 ). Download figure Open in new tab Figure 1. Csf1r expression in the brain is restricted to microglia. Hippocampus (A) and cortex (B) from Cx3cr1 -EGFP x Csf1r- FusionRed mice were stained for IBA1 and counterstained with DAPI. Note the complete overlap of the three markers. The FusionRed reporter (FRed) is detected primarily in the cell body of individual microglia. Lower panel in B shows cortex of Csf1r -EGFP mouse also stained for IBA1, providing a negative control for FusionRed. (C). Flow cytometry profile of brain cells isolated from Cx3cr1 -EGFP x Csf1r- FusionRed mice. Scale bars in (A) and (B) = 100 µm. We used bulk RNA sequencing to compare gene expression in cortex, hippocampus and striatum at two weeks of age, and cortex, hippocampus, striatum, olfactory bulb and cerebellum of male and female Csf1r ΔFIRE/ΔFIRE mice and litter mate controls at six weeks of age. This analysis was carried out on the original mixed genetic background (25% CBA/75% C57BL/6J) and the mutant mice selected showed no evidence of ventricular enlargement. The full datasets for the two- and six-week cohorts are provided in Table S1 and S2 , respectively, with conventional differential expression analysis for each region. As in our previous analysis in Csf1r -/- rats ( Patkar et al., 2021 ) the RNA-seq data were also analyzed using the network analysis tool BioLayout and the clusters and their average expression profiles are provided in Table S3. Figure 2 shows selected profiles of co-expressed transcripts and highlights of index genes. Clusters 1, 4, 7 and 13 are enriched in specific brain regions and are unaffected by Csf1r genotype. The only clusters influenced by Csf1r genotype contain known microglia-specific genes. Cluster 11 contains around 250 transcripts, including Csf1r, and overlaps with the smaller set identified in adult hippocampus using microarrays ( Rojo et al., 2019 ) and RNA-seq analysis in juvenile Csf1r -/- rats ( Patkar et al., 2021 ). Cluster 30 shows a similar pattern, except that these transcripts are less dependent upon Csf1r , suggesting they may also be expressed by other cell types especially in olfactory bulb. Download figure Open in new tab Figure 2. Network analysis of gene expression in brain regions of juvenile WT and Csf1r ΔFIRE/ΔFIRE mice. RNA-seq data generated from five brain regions of six-week-old mice ( Table S1 ) were clustered using the network analysis software Biolayout. The complete output is provided in Table S2 . Each graph shows the average expression of all genes within the cluster, an indication of the shared pattern. Each bar is an individual mouse. Selected examples of transcripts within each cluster are shown. The color code below each graph indicates WT (blue) and Csf1r ΔFIRE/ΔFIRE (green) mouse genotype, and the brain regions, cortex (red), hippocampus (yellow), striatum (pink), cerebellum (light blue) and olfactory bulb (beige). Genetic background profoundly influences Csf1r ΔFIRE/ΔFIRE phenotype The Csf1r ΔFIRE mutation was generated in F1 C57BL/6J x CBA/J (BCBF1) mice to mitigate the perinatal and pre-weaning lethality observed in Csf1r -/- mice on an inbred C57BL/6J or FVB/J background ( Chitu et al., 2016 ; Erblich et al., 2011 ; Percin et al., 2018 ). Phenotypic analysis, including evidence of white matter pathology ( McNamara et al., 2023 ), thalamic calcification ( Chadarevian et al., 2024 ; Munro et al., 2024 ), impacts on neurodegeneration models ( Bradford et al., 2022 ; Kiani Shabestari et al., 2022 ), behavioral analysis ( McNamara et al., 2023 ) and the gene expression profiling described above were all performed on mice of mixed genetic background with varying contributions of C57BL/6J genetics. The Csf1r ΔFIRE mutation was crossed 10x to C57BL/6J and the inbred line was transferred to Australia and crossed to the Csf1r- EGFP reporter line ( Sasmono et al., 2003 ), also generated originally in BCBF1 and then backcrossed to C57BL/6J. Subsequent analysis in Edinburgh revealed extreme loss of Csf1r ΔFIRE/ΔFIRE pups on the pure C57BL/6J background. Of the few Csf1r ΔFIRE/ΔFIRE pups identified by genotyping, 100% developed HC. By contrast, some Csf1r ΔFIRE/ΔFIRE mice generated by crossing to the Csf1r- EGFP reporter line survived to adults and were long-lived and fertile, despite the absence of microglia in every brain region in neonates and adults. Figure 3A shows representative images of the hippocampus of inbred adult WT and Csf1r ΔFIRE/ΔFIRE mice stained for IBA1, GFAP and TMEM119. In the mice that did not develop HC, classical microglia were undetectable but IBA1 + macrophages lining parenchymal vessels ( Drieu et al., 2022 ) and associated with meningeal surfaces were retained ( Figure 3B ), as reported previously in outbred lines (Kiani Shabestari et al., 2022 ; McNamara et al., 2023 ; Rojo et al., 2019 ) The abundance, morphology and location of GFAP-positive astrocytes was not affected. Download figure Open in new tab Figure 3. Selective loss of microglia in adult Csf1r ΔFIRE/ΔFIRE mice on a congenic C57BL/6J background. Free-floating sections from WT (+/+) or Csf1r ΔFIRE/ΔFIRE (Δ/Δ) hippocampus (A) or cortex (B) were stained to detect GFAP, IBA1 and TMEM119 as indicated. Lower panels in (A) highlight the presence of IBA1 + macrophages associated with parenchymal vessels lined with astrocytes. In (B) IBA1 + meningeal and perivascular macrophages are detected in both WT and Csf1r ΔFIRE/ΔFIRE tissue (white arrows) whereas microglia (yellow arrow) are absent in Csf1r ΔFIRE/ΔFIRE mice. Scale bars = 100 µm. Table 1 shows the genotype frequency at weaning from Csf1r ΔFIRE/+ matings on the C57BL/6J-( Csf1r -EGFP) background. Csf1r ΔFIRE/ΔFIRE mice were detected at 59% of the expected frequency whereas the relative incidence of surviving Csf1r ΔFIRE/+ progeny was consistent with Mendelian expectation. Of the Csf1r ΔFIRE/ΔFIRE pups identified, 13/39 developed severe ventricular enlargement and HC ( Figure S1A, B ). To understand the nature of HC, we injected Evans Blue into the ventricles of affected mice. By contrast to normal brains, in mice with HC the dye was excluded from the third and fourth ventricles and the cerebellum ( Figure S1C, D ). suggesting occlusion of the foramina of Monro, the fine slit-like channel linking the lateral ventricles and third ventricle. On the C57BL/6J-( Csf1r -EGFP) genetic background Csf1r ΔFIRE/ΔFIRE mice that did not succumb to HC did not subsequently show any evidence of ventricular enlargement. To confirm the effect of genetic background, Csf1r ΔFIRE/+ C57BL/6J-( Csf1r -EGFP) mice were bred with WT CBA and BALB/c mice and Csf1r ΔFIRE/+ F1 progeny were intercrossed to generate F2 mice of all genotypes ( Table 1 ). In the F2 generation on the two mixed genetic backgrounds there was no longer any significant pre-weaning loss. HC was observed in only 3/83 C57BL/6J x CBA homozygotes and 0/163 C57BL/6J x BALB/c homozygotes. Although both the Csf1r ΔFIRE and Csf1r- EGFP alleles had been bred extensively to C57BL/6J, we speculated that either the cross bred line per se or the long-term survivors might be enriched for residual non-C57BL/6J alleles that mitigate perinatal loss or the development of HC. To test this possibility, we isolated DNA from eight Csf1r ΔFIRE/ΔFIRE / Csf1r -EGFP + long term survivors and eight pups with definitive HC. Whole genome sequencing was performed on pools of four mice each. Inter alia, the genomic DNA sequence revealed that the Csf1r ΔFIRE allele on chromosome 18 was on the C57BL/6J background (there was no enrichment of non-C57BL/6J sequence around the Csf1r locus). Figure S2 shows that pools of mice with HC and long-term non-HC survivors shared defined regions with a high frequency of alternate alleles (compared to the C57BL/6J reference) on multiple chromosomes, in particular 3, 8, 13 and 16, but there was no difference in the location of the non-C57BL/6J regions that distinguished the two groups. In each pool, the number of reads mapping over the promoter of the Csf1r gene was about 10-fold that of the median level, consistent with the insertion of multiple copies (between 10 and 20) of the Csf1r- EGFP reporter transgene. Chromosome 16 had two regions of dense non-reference variants. One of these is the likely location of the Csf1r -EGFP transgene. An apparent breakpoint at 16:91,207,427 joins to Csf1r sequence and a second at 16:91,183,085 (GRCm38) joins to vector sequence. This is located around 20kb from the Olig2 gene. The enrichment for non-reference sequences around the putative insertion indicates that the original transgene insertion was on the CBA chromosome in the BCBF1 founder. Deficient microglial and macrophage populations in neonatal Csf1r ΔFIRE/ΔFIRE mice As a possible explanation of HC we considered the possibility that neonatal macrophage deficiency reported previously in Csf1r ΔFIRE/ΔFIRE mice ( Munro et al., 2020 ) is more penetrant on the C57BL/6J background. IBA1 staining of coronal sections through the whole brain of Csf1r ΔFIRE/ΔFIRE neonates on the C57BL/6J background revealed the complete absence of microglia (including monocyte-derived amoeboid microglia) in the parenchyma in any brain region. IBA1 + BAM were detected on meningeal surfaces and in the choroid plexus but greatly reduced compared to controls ( Figure 4 ). Perivascular macrophages in the parenchyma develop from the perinatal meningeal population in the postnatal period ( Goldmann et al., 2016 ; Masuda et al., 2022a ; Utz et al., 2020 ). By contrast to adult brain ( Figure 3 ), no parenchymal IBA1 + cells were detected in neonatal Csf1r ΔFIRE/ΔFIRE mice ( Figure 4 ). Aside from the parenchymal microglia and macrophages, the ventricles contain a population of supraependymal macrophages including a subpopulation associated with the choroid plexus (epiplexus cells). Epiplexus macrophages were undetectable in brains of neonatal Csf1r ΔFIRE/ΔFIRE / Csf1r -EGFP mice (Yellow arrowheads; Figure 4B ), consistent with previous reports of embryonic and adult Csf1r ΔFIRE/ΔFIRE mice ( Munro et al., 2020 ). By contrast, stromal choroid plexus macrophages were present but reduced compared to WT mice (Red arrowheads, Figure 4B ). In summary, in terms of brain myeloid populations at birth, the impact of the Csf1r ΔFIRE/ΔFIRE mutation in our mice mirrors the previous analysis on the mixed C57BL/6J x CBA background ( Munro et al., 2020 ). There is no clear difference that could contribute to increased HC susceptibility. Download figure Open in new tab Figure 4. Selective loss of microglia and macrophages in the brain of neonatal Csf1r ΔFIRE/ΔFIRE mice. Cryosections from neonatal WT (+/+) or Csf1r ΔFIRE/ΔFIRE (Δ/Δ) mice on the C57BL/6J background were stained to detect IBA1 and GFAP as indicated, and co-stained with DAPI. Representative images are shown. Panels to the right of (A) show cortex (CORT) and highlight meningeal macrophages. (B) shows the choroid plexus (CP), and red arrows indicate stromal macrophages while yellow arrows indicate epiplexus macrophages which were not detectable in Csf1r ΔFIRE/ΔFIRE mice. Scale bars = 100 µm. The absence of microglia in Csf1r ΔFIRE/ΔFIRE mice does not affect motor or cognitive function Previous studies of microglia-deficient adult and aged Csf1r ΔFIRE/ΔFIRE mice ( McNamara et al., 2023 ) found no evidence of the severe cognitive or motor dysfunction and early mortality seen in patients with dominant or homozygous recessive CSF1R mutations ( Dulski et al., 2023 ; Papapetropoulos et al., 2021 ). Figure S3 shows a time course of motor function and coordination in mice on the original mixed C57BL/6J/CBA background assessed using the CatWalk assay, which has been applied to evaluate phenotypes in many rodent neuropathology models ( Garrick et al., 2021 ). In this longitudinal study, each mouse was analyzed weekly from 10-40 weeks of age. On all measured parameters, Csf1r ΔFIRE/ΔFIRE mice remained indistinguishable from WT and showed no evidence of age-related decline. We also repeated standard behavioral assays in WT, Csf1r ΔFIRE/+ and Csf1r ΔFIRE/ΔFIRE mice on our defined F2 intercross with CBA/J (BCBF2) at 30 weeks of age. Consistent with previous analysis ( McNamara et al., 2023 ) and analysis of mice depleted of microglia ( Elmore et al., 2014 ), we found no significant differences amongst the groups in the open field/locomotor test, marble burying test or elevated plus maze, commonly-applied tests of anxiety-like behavior ( Chen et al., 2024 ) nor in the Morris water maze, a demanding test of motor function and memory (data not shown). Brain histopathology in aged microglia-deficient mice A previous study ( McNamara et al., 2023 ) described age-dependent alterations in myelin integrity in mixed-background Csf1r ΔFIRE/ΔFIRE mice associated with disruption of TGFB1:TGFBR1 signaling. Tgfb1 and Tgfbr1 mRNA were both reduced in all brain regions in juvenile Csf1r ΔFIRE/ΔFIRE mice ( Table S1/2 ). The authors described “patchy demyelination” at six months of age that was not associated with detectable loss of immunoreactive myelin proteins in the corpus callosum. We performed Magnetic Resonance Imaging (MRI) experiments consisting of susceptibility weighted imaging (SWI) and diffusion tensor imaging (DTI) on a comparable 30-week-old cohort of WT, Csf1r ΔFIRE/+ and Csf1r ΔFIRE/ΔFIRE mice. SWI is commonly used to detect cerebral microbleeds, whereas DTI detects white matter pathology, as previously described in an analysis of demyelination in experimental autoimmune encephalitis ( Althobity et al., 2023 ). Figure 5A and 5B show representative images of SWI and DTI, respectively, comparing BCBF2 WT, Csf1r ΔFIRE/+ , and Csf1r ΔFIRE/ΔFIRE brains at 30 weeks of age. There was no evidence of hyperintense deep white matter diffusion dots, cortical atrophy or ventricular enlargement, features observed in clinical imaging of human CSF1R-associated disease ( Dulski et al., 2023 ; Konno et al., 2018 ; Lakshmanan et al., 2017 ). Deficient neuronal apoptosis in mice with a CD11b deficiency ( Itgam -/- ) was associated with increased cortical thickness ( Deivasigamani et al., 2023 ) but this was also not observed in Csf1r ΔFIRE/ΔFIRE mice. The diagnostic hallmark of CSF1R-related leukoencephalopathy in humans is thinning of the corpus callosum, which is even more severe in homozygous recessive CSF1R mutation where there can be callosal agenesis ( Chitu et al., 2015 ; Dulski et al., 2023 ; Kinoshita et al., 2021 ). Thinning of the corpus callosum was reported in aged Csf1r +/- mice ( Chitu et al., 2015 ). However, we found no significant quantitative difference in fractional anisotropy (FA) in the corpus callosum, anterior or hippocampal commissure or internal capsule, nor in the total volume or distribution of these fiber tracts. Replicates and quantitative analyses are shown in Figure S4. Consistent with this view, immunolocalization of myelin basic protein (MBP) did not indicate significant demyelination in the corpus callosum, cortex, striatum or hippocampus in the Csf1r ΔFIRE/ΔFIRE mice at this age ( Figure 5C ). Download figure Open in new tab Figure 5. Magnetic resonance imaging (MRI) tractography of white matter fibres, susceptibility weighted imaging (SWI) and myelination in WT (+/+), Csf1r ΔFIRE/+ (+/Δ) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ) mice at 30 weeks. (A) Representative coronal images of SWI showing cortex (CTX), hippocampus (HIPP), and thalamus (TH) in WT (+/+), Csf1r ΔFIRE/+ (+/Δ) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ) mice. Inset of thalamus (box and arrow) is shown in higher resolution. (B) Representative images of white matter tracts in the corpus callosum, anterior commissure and hippocampal commissure in +/+, +/Δ and Δ/Δ mice. Scale bar = 50 mm. (C) Representative images of cortex (scale bar = 100 μm) corpus callosum, hippocampus and striatum (scale bars = 200 μm) stained with anti-myelin basic protein antibody (MBP, magenta). Graphs show mean ± SEM of three mice per genotype, and p values were determined using two-way ANOVA followed by Sidak’s multiple comparison test. ns, not significant. Perineuronal nets (PNNs) are brain extracellular matrix structures that regulate synaptic functions and protect neurons from stress. In the cortex, they are commonly associated with inhibitory parvalbumin (PV) interneurons ( Reichelt et al., 2019 ). Chronic microglial depletion using a CSF1R kinase inhibitor led to an increase in cortical PNN and a small increase in PV neurons ( Barahona et al., 2022 ; Liu et al., 2021 ). Subsequently, the same group reported a reduction in PNN in aged Csf1r +/- mice, attributed to microglial dyshomeostasis. These changes were detected by staining with the lectin, Wisteria floribunda agglutinin (WFA) which binds to specific matrix glycans, or by immunolocalization of the protein core (aggrecan) encoded by Acan ( Arreola et al., 2021 ). There was no significant difference in WFA or PV staining in the cortex of BCBF2 WT, Csf1r ΔFIRE /+ and Csf1r ΔFIRE/ΔFIRE at 30 weeks of age ( Figure 6A, B ). One notable feature of the SWI in Figure 5A is the detection of hypointensities in the thalamus of Csf1r ΔFIRE/ΔFIRE mice. Consistent with previous reports of age-dependent thalamic calcification in Csf1r ΔFIRE/ΔFIRE mice on various mixed genetic backgrounds ( Bradford et al., 2022 ; Chadarevian et al., 2024 ; Kiani Shabestari et al., 2022 ; Munro et al., 2024 ), we detected extensive calcification in the thalamus in our BCBF2 Csf1r ΔFIRE/ΔFIRE mice at 30 weeks, detected with Alizarin Red or AF647-risedronate. There was an intimate association between increased GFAP-positive astrocytes and calcium deposits ( Figure 6C, D ). On the original mixed background, re-analysis of the uninfected control cohort for the prion disease study ( Bradford et al., 2022 ), revealed the accumulation of GFAP-positive astrocytes in the thalamus in a subset of Csf1r ΔFIRE/ΔFIRE mice as early as three months of age, before any calcification was detectable by Alizarin Red staining in the same animals ( Figure S5 ). Download figure Open in new tab Figure 6. Perineuronal nets and thalamic calcification in WT (+/+), Csf1r ΔFIRE/+ (+/Δ) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ) mice at 30 weeks. (A) Representative images of sagittal brain sections stained with Wisteria floribunda agglutinin (WFA) to detect perineuronal nets (PNN; green), and antibody against parvalbumin (PV; magenta). PNNs are detected in the somatosensory cortex (SSC), the entorhinal cortex (ERC) and the dentate gyrus of the hippocampus (HIPP). Lower panels of (A) show detection of both markers in the SSC at higher resolution. Scale bar = 100 μm. (B) Percentage of WFA (upper) and PV (lower) area coverage in SSC was calculated using ImageJ. Graphs show mean ± SEM of two quantified regions per mouse, from three mice per genotype. (C) Representative sagittal brain sections stained with Alizarin Red (upper panels) or with antibody against GFAP (green) in combination with AF647-risedronate (RIS; magenta) (lower panels). (ST = striatum, THAL = thalamus, HIPP = hippocampus). Scale bars = 100 μm. (D) Percentage of GFAP and RIS coverage in thalamus was calculated using ImageJ. Graphs show mean ± SEM from three mice per genotype, and p values were determined using two-way ANOVA followed by Sidak’s multiple comparison test. *, p < 0.05. Repopulation of the brain of Csf1r ΔFIRE/ΔFIRE mice with bone marrow-derived macrophages In both mice and rats with homozygous Csf1r mutations, the brain can be repopulated with donor-derived cells following injection of WT bone marrow into the peritoneal cavity without conditioning ( Bennett et al., 2018 ; Keshvari et al., 2021 ; Sehgal et al., 2023 ). This finding suggests that the vacant cavity provides a trophic niche for progenitor cells. Since Csf1r ΔFIRE/ΔFIRE mice also lack peritoneal macrophages ( Rojo et al., 2019 ), we took advantage of our generation of an inbred line to determine whether intraperitoneal (IP) WT bone marrow cell transfer (BMT) at weaning without conditioning would enable repopulation of the brain. For this purpose, we used Csf1r- FusionRed mice ( Grabert et al., 2020 ) as donors and Csf1r ΔFIRE/ΔFIRE / Csf1r- EGFP mice as recipients. BMT at weaning did not alter the rate of HC development in this line, but non-HC BMT recipients grew normally and showed no evidence of pathology. In Csf1r ΔFIRE/ΔFIRE BMT recipients the peritoneal macrophage population was completely repopulated by FRed + donor-derived cells by 12 weeks post-BMT ( Figure 7A ). There were detectable FRed + donor cells in the cavity in heterozygous recipients, suggesting a competitive advantage, whereas in WT recipients peritoneal cells remained entirely FRed -ve indicating an absolute requirement for a vacant niche. The F4/80 low small peritoneal macrophages, which are retained in Csf1r ΔFIRE/ΔFIRE mice and are reported to be CSF1-independent and replenished by monocytes ( Bain et al., 2020 ; Bain et al., 2022 ) were nevertheless also replaced by cells of donor origin. Despite the extensive population of the peritoneal cavity, FRed + donor cells made no detectable contribution to the blood monocyte, bone marrow or splenic cell population even 12 weeks post transfer ( Figure S6A ). Download figure Open in new tab Figure 7. Repopulation of the brain of Csf1r ΔFIRE/ΔFIRE mice with WT donor cells from bone marrow transfer (BMT). Csf1r ΔFIRE/ΔFIRE / Csf1r- EGFP mice were injected intraperitoneally (IP) with Csf1r- FusionRed (FRed) donor bone marrow cells at weaning (3 weeks) and engraftment was analyzed 12 weeks post transplant. (A) shows representative flow cytometry profiles of peritoneal cells harvested from WT (+/+), Csf1r ΔFIRE/+ (+/Δ) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ) recipients. (B) shows representative flow cytometry profiles of myeloid cells harvested from +/+, +/Δ and Δ/Δ recipients. The dotted line in the CD45/CD11b profile highlights the shift in location of the microglial gate from +/+ to Δ/Δ. Proportion of FRed+ cells are quantified on right hand side. Graph shows mean ± SEM from at least three mice per genotype, and p values were determined using two-way ANOVA followed by Sidak’s multiple comparison test. ****, p < 0.0001. Inset panel shows typical histogram of F4/80 staining on microglial cells isolated from BMT recipients. (C) Representative sections of brain cortex from +/+ and Δ/Δ BMT recipients show the repopulation of the cortex with donor (FRed+ cells). Scale bar = 100 µm. (D) Representative images of sections of brain cortex from +/+ and Δ/Δ BMT recipients stained for IBA1 (magenta), TMEM119 (yellow), and P2RY12 (teal). Scale bars = 100 µm. (E) Representative images of sections of brain cortex (left) and hippocampus (right) stained with IBA1 (magenta) and co-stained with DAPI. Highlighted regions (white square + arrow) are shown at higher resolution to the right to highlight the morphological difference between +/+ to Δ/Δ. Microglial ramification was quantified in ImageJ. Graphs shows mean ± SEM three mice per genotype, and p values were determined using two-way ANOVA followed by Sidak’s multiple comparison test. *, p < 0.05; **, p < 0.01. Scale bars = 100 µm We observed complete repopulation of the brain of Csf1r ΔFIRE/ΔFIRE mice with FRed + donor-derived cells 12 weeks post-BMT ( Figure 7B, C , Figure S6B) . No donor cells were detected in WT or heterozygous BMT recipients ( Figure 7B ). At this age, we did not detect astrocytosis or calcification in the thalamus of Csf1r ΔFIRE/ΔFIRE mice or the BMT recipients. Consistent with previous evidence that bone marrow-derived microglia-like cells do not fully recapitulate homeostatic gene expression ( Bennett et al., 2018 ; Carter-Cusack et al., 2024 ; Cronk et al., 2018 ; Lund et al., 2018 ; Shemer et al., 2018 ; Shibuya et al., 2022 ), Figure 7B shows a phenotypic distinction between FRed + donor-derived cells and WT microglia, with relatively increased CD45 and decreased CD11b detected by Flow Cytometry on donor-derived cells. These cells were also distinguished from WT microglia by increased expression of the F4/80 antigen. The absence of Csf1r -EGFP + cells in the meninges and parenchyma of BMT recipients indicates that BAM are also replaced by donor FRed + cells. Residual Csf1r -EGFP + cells in the BAM gate in the BMT recipients are likely monocytes (see Figure 1 ) which are not donor-derived. Donor-derived FRed + cells achieved a similar density and regular distribution to WT microglia but did not replicate the extensive ramification characteristic of normal microglia ( Figure 7C ) and the homeostatic microglia markers P2RY12 and TMEM119 were barely detectable in the donor-derived cells ( Figure 7D ). The difference in morphology between resident and BM-derived cells in cortex and hippocampus is shown in more detail by IBA1 staining and quantitative image analysis in Figure 7E . To gain insight into the mechanism of repopulation, we examined brains at three- and five-weeks post BMT. Within individual brains we observed multiple large clusters of IBA1 + cells with a concentrated “wave front” similar to the pattern detected following microglial transplantation ( Chadarevian et al., 2024 ) ( Figure S7 ). DISCUSSION Csf1r is expressed exclusively in microglia and macrophages In this study we have analyzed the impact of a mutation in the Csf1r locus. Our interpretation of the brain phenotype is based upon the premise that CSF1R is expressed only in mononuclear phagocytes. However, there have been several reports claiming that CSF1R is expressed by neurons ( Biundo et al., 2021 ; Chitu et al., 2016 ; Clare et al., 2018 ; Luo et al., 2013 ; Murase and Hayashi, 1998 ; Nandi et al., 2012 ). This view continues to be widely cited ( Hu et al., 2021 ; Johnson et al., 2023 ; Stanley et al., 2023 ). By contrast, Csf1r mRNA is restricted to myeloid cells in the embryo ( Lichanska et al., 1999 ) and strongly correlated with other macrophage markers in a developmental time course ( Summers and Hume, 2017 ). Others ( Askew et al., 2017 ; Erblich et al., 2011 ; Hawley et al., 2018 ; Hume et al., 2020 ; Kana et al., 2019 ; Kiani Shabestari et al., 2022 ; Petit et al., 2024 ) have concluded that Csf1r mRNA and the Csf1r- reporter transgenes are expressed exclusively in microglia in adult mice. The Csf1r -FusionRed transgene reports CSF1R protein expression, and detection provides a marker for tissue resident macrophages ( Grabert et al., 2020 ). Our analysis using this marker in the brain contradicts reported expression of CSF1R protein in Purkinje cells ( Murase and Hayashi, 1998 ), layer 5 cortical neurons ( Clare et al., 2018 ) and the dentate gyrus in the hippocampus ( Luo et al., 2013 ). Incidentally, both the localization of Cx3cr1 -EGFP ( Figure 1 ) and the absolute CSF1R-dependence of Cx3cr1 mRNA expression ( Table S2 ) are incompatible with reported expression in hippocampal neurons ( Meucci et al., 2000 ). In summary, the phenotypes that arise in Csf1r ΔFIRE/ΔFIRE mice can be ascribed exclusively to effects on mononuclear phagocytes. Whilst Csf1r ΔFIRE/ΔFIRE mice are not osteopetrotic and retain some tissue macrophages that are absent in a knockout, they are unresponsive to CSF1 in bone marrow and lack multiple macrophage populations in the periphery ( Rojo et al., 2019 ). We cannot eliminate the possibility that peripheral macrophage dysfunction/deficiency contributes to brain pathology. Microglial function in postnatal brain development is redundant This study uses the Csf1r ΔFIRE/ΔFIRE mouse to address the roles of microglia in postnatal development and neuropathology in the mouse, and the impact of genetic background. In view of the extensive literature on microglial contributions to functional maturation of the central nervous system, including regulation of myelination, neurogenesis and neuronal guidance, elimination of excess neurons and synapses, long term potentiation and neurotransmitter homeostasis ( Paolicelli et al., 2022 ; Schafer et al., 2024 ) the lack of overt phenotype in young microglia-deficient mice was unexpected. Detailed analysis in a separate study indicated that microglial contributions to synaptic pruning and maturation in the hippocampus, synaptic maturation and excitation-inhibition balance in the somatosensory cortex, eye-specific segregation of inputs into the lateral geniculate nucleus, and circuit-level connectivity that regulates inter-brain region coherence were redundant ( O’Keeffe et al., 2024 ). Similarly, contrary to conclusions based upon microglial depletion, microglia deficiency did not alter postnatal development of white matter ( McNamara et al., 2023 ) and there was no evidence of dysregulated expression of oligodendrocyte/myelination related transcripts in any brain region in juvenile mice ( Table S1/S2 ). The conclusion that microglia are redundant for many developmental functions does not necessarily invalidate previous studies. Interpretation of microglial depletion models is compromised by the effect of microglial cell corpses which are themselves taken up by astrocytes ( Zhou et al., 2022 ). Hence, the effect of microglial depletion with CSF1R kinase inhibitor PLX5622 on feedback control of neuronal activity and susceptibility to seizures ( Badimon et al., 2020 ) was not replicated in Csf1r ΔFIRE/ΔFIRE mice ( O’Keeffe et al., 2024 ). On the other hand, mutations in specific microglia effectors/receptors such as CX3CR1, CR3/CD11B, C1Q and TREM2 produce functionally defective microglia that fail to properly remove apoptotic cells or prune synapses, but nevertheless occupy space and may interfere with potential compensation by other cell types. Each of these effectors is entirely absent in the brain of Csf1r ΔFIRE/ΔFIRE mice, indicating that they are not the only mechanisms available for removal of debris. By contrast, Sirpa, Cd36, Megf10 and Mertk, which encode proteins that mediate recognition by astrocytes ( Chung et al., 2013 ; Damisah et al., 2020 ; Konishi et al., 2020 ; Lee et al., 2021 ) were unaffected by microglial deficiency although each is also highly-expressed by microglia ( Summers et al., 2020 ). In older Csf1r ΔFIRE/ΔFIRE mice, we did not replicate the increase in perineuronal nets associated with microglial depletion using CSF1R kinase inhibitors ( Arreola et al., 2021 ; Crapser et al., 2020 ; Liu et al., 2021 ). Perineuronal nets contribute to many aspects of neuronal function. Most of the literature is focussed on the consequences of their loss ( Crapser et al., 2021 ; Reichelt et al., 2019 ). However, Liu et al . ( Liu et al., 2021 ) reported enhanced neural activities of both excitatory neurons and parvalbumin-expressing interneurons in the visual cortex following microglia depletion. The increase in perineuronal nets following depletion could be a consequence of altered astrocyte function ( Crapser et al., 2021 ; Tewari et al., 2022 ). The complex impact of genetic background on viability and development of HC In the initial characterization of the mutation on the mixed C57BL/6J/CBA (75%/25%) background, the reported frequencies of WT, Csf1r ΔFIRE/+ and Csf1r ΔFIRE/ΔFIRE mice at weaning indicated around 30% loss of homozygotes ( Rojo et al., 2019 ). Homozygous frequency was reduced by 41% relative to Mendelian expectation in our novel congenic C57BL/6J line whereas we had no surviving mice on the pure C57BL/6J background. Loss prior to genotyping was no longer observed in CBA or BALB/c F2 mice ( Table 1 ). Like Csf1r -/- mice, Csf1r ΔFIRE/ΔFIRE mice are entirely deficient in yolk sac-derived embryonic macrophages ( Munro et al., 2020 ). Csf1r -/- mice are reported to die perinatally (E18-P2) on the C57BL/6J background ( Chitu et al., 2016 ) and homozygous kinase-dead Csf1r mutation ( Csf1r E631K/E631K ) is also lethal on a C57BL/6J background ( Stables et al., 2022 ). Perinatal lethality in Csf1r E631K/E631K mice is overcome in the F2 generation following cross to BALB/c, allowing the generation of homozygotes that are viable and long-lived, albeit growth-retarded and osteopetrotic (Ms in preparation) like the original Csf1r knockout ( Dai et al., 2002 ). Mutation in the Spi1 gene encoding PU.1 also produces embryonic lethality on the C57BL/6J background ( Hume, 2023 ). Hence, C57BL/6J mice appear uniquely unable to compensate for macrophage deficiency during embryonic development. Brain ventricular enlargement is a feature of homozygous recessive Csf1r mutations in FVB/NJ mice ( Erblich et al., 2011 ) and in rats and humans ( Dulski et al., 2023 ; Hume et al., 2020 ; Papapetropoulos et al., 2021 ). Lateral ventricular enlargement is also a defining feature of human CSF1R-related leukoencephalopathy ( Konno et al., 2018 ; Papapetropoulos et al., 2021 ) but was not observed in a mouse model with a disease-associated CSF1R mutation ( Stables et al., 2022 ; Stables et al., 2024 ). More generally, HC is one of the most common human birth defects ( Kahle et al., 2016 ). Our analysis indicates that there are epistatic modifiers on the C57BL/6J background that interact with the Csf1r ΔFIRE/ΔFIRE mutation to increase the incidence of postnatal HC. C57BL/6J mice are intrinsically susceptible to HC, and many other mutations cause HC specifically on this genetic background ( Gografe et al., 2003 ; Goto et al., 2008 ; Matsumoto et al., 2020 ; Tapanes-Castillo et al., 2010 ; Wyss et al., 2012 ). HC in Csf1r ΔFIRE/ΔFIRE mice is an all-or-nothing phenotype apparently arising from a block to cerebrospinal fluid (CSF) flow. A similar pattern of obstruction leading to lateral ventricle enlargement was reported in C57BL/6J Tal2 -/- mice ( Bucher et al., 2000 ). Similarly, in Apaf1 -/- mice on a C57BL/6J background HC develops in 40-50% of pups, whereas others survive to adulthood ( Matsumoto et al., 2020 ). The mechanisms linking Csf1r mutations and postnatal microglial/macrophage deficiency to HC are not clear. Microglia are required for brain morphogenesis and their absence in the embryo gives rise to cavitation lesions at the cortico-striatal-amygdalar and cortico-septal boundaries that resolve in the postnatal period. These lesions were identified in Csf1r ΔFIRE/ΔFIRE mice on both C57BL/6J and the original mixed genetic background but the effect of genetic background on postnatal repair could not be assessed in C57BL/6J mice ( Lawrence et al., 2024 ). It is possible that HC on the C57BL/6J background is related to delayed repair at the cortico-septal boundary or more subtle structural anomalies predisposing to obstruction of the foramena of Monro. HC may also involve an effect on CSF dynamics. Mutations impacting genes required for ependymal motile cilia, including Ccdc39, Ccdc88c, Cfap221, Cfap54 and Spef2, also lead to reduced CSF flow and postnatal HC that is C57BL/6J strain dependent ( Abdelhamed et al., 2018 ; McKenzie et al., 2018 ; Takagishi et al., 2017 ). Drieu et al . ( Drieu et al., 2022 ) reported that parenchymal perivascular macrophages are required for homeostatic control of CSF flow. Perivascular macrophages develop from leptomeningeal macrophages in the postnatal period ( Masuda et al., 2022b ) and these precursors are partly deficient in neonatal Csf1r ΔFIRE/ΔFIRE mice. Epiplexus and intraventricular macrophages were also greatly reduced in Csf1r ΔFIRE/ΔFIRE neonates and may also contribute to CSF homeostasis ( Mildenberger et al., 2022 ). In the RNA-seq analysis of Csf1r ΔFIRE/ΔFIRE pups at two weeks of age, detectable transcripts encoding BAM markers ( Drieu et al., 2022 ; Van Hove et al., 2019 ) ( Ctsc, Lyve1, Cd38, Mafb, Mrc1, CD163, Siglec1, Cd74/H2-Aa ) approached WT levels and by six weeks detection of these markers confirmed evidence that the Csf1r ΔFIRE/ΔFIRE mouse is no longer deficient in BAM populations (see Figure 3 ;( McNamara et al., 2023 ; Rojo et al., 2019 )). Hence, there is a narrow window of embryonic and postnatal macrophage insufficiency in the Csf1r ΔFIRE/ΔFIRE mice that correlates with the timing of HC. Given the probabilistic nature of HC, it is not surprising that long term survivors were not distinguished genetically from those mice that succumbed to HC ( Figure S2 ). We identified several genomic regions in our Csf1r ΔFIRE/ΔFIRE / Csf1r -EGFP mice that were clearly derived from a non-C57BL/6J strain, mostly CBA. Quantitative trait loci (QTL) on chromosomes 3, 4, 7 and 8 associated with increased ventricular volume in C57BL/6J were previously mapped in a series of recombinant inbred strains derived from C57BL/6J x A/J cross ( Zygourakis and Rosen, 2003 ). Similarly, a modifier locus on chromosome 5 was linked to susceptibility to HC in C57BL/6J mice with L1Cam mutation ( Tapanes-Castillo et al., 2010 ). None of these loci overlap with the regions identified herein. A block of non-reference sequence surrounds the site of the Csf1r- EGFP transgene insertion on chromosome 16, indicating that in the original line generated on a C57BL/6 x CBA F1 background ( Sasmono et al., 2003 ) the CBA chromosome was targeted and a linkage block has been retained as a consequence of selection for the transgene marker. The linkage block contains the Down’s syndrome critical region, including Dscam . Knockout of Dscam causes postnatal lethality and HC in C57BL/6J mice that was mitigated in a C57/BALB/c congenic line ( Xu et al., 2011 ). However, the transgene alone is neither necessary nor sufficient to prevent HC. The incidence of HC in Csf1r ΔFIRE/ΔFIRE mice was reduced to almost zero in F2 mice from both CBA and BALB/c intercross, which is incompatible with a simple Mendelian trait. Of course, these genomic regions must also contribute to preventing the perinatal lethality of Csf1r ΔFIRE/ΔFIRE mice on the C57BL/6J background; survival is a necessary precondition to development of HC. The effect of microglial deficiency on the brain transcriptome in juvenile mice Compared to total or single cell (sc) RNA-seq analysis of isolated microglia, total RNA-seq of whole brain regions avoids incomplete and unrepresentative recovery, activation during isolation and contamination with mRNA from unrelated cells ( Hume et al., 2023 ; Millard et al., 2021 ). Network analysis enables deconvolution of cell-type specific signatures. We did not identify an astrocyte-specific cluster, but markers suggestive of reactive astrocytes, including Gfap, were increased in hippocampus and cortex and are highlighted in Table S2. This was not associated with detectable changes in location, morphology or abundance of GFAP-positive cells in hippocampus. The most elevated gene, C4b , encodes a key effector of astrocyte-mediated clearance function ( Zhou et al., 2022 ). Network analysis of RNA-seq data from five brain regions in six week-old mice was consistent with the loss of microglia as the only deficiency ( O’Keeffe et al., 2024 ). All of the genes in Clusters 11 and 30 (Table S3) are expressed in isolated mouse microglia ( Summers et al., 2020 ; Van Hove et al., 2019 ) and the signature largely overlaps the outcome of similar multi-region analysis in juvenile Csf1r -/- rats ( Patkar et al., 2021 ). Table S4 compares the set of CSF1R-dependent transcripts identified in hippocampus in Csf1r ΔFIRE/ΔFIRE mice and Csf1r -/- rats. The set of rat-specific markers including Cd163, Mrc1 and Lyve1 , can be attributed to the fact that BAM are retained in the mouse model. One feature that is shared is the absolute CSF1R-dependent expression of a set of transcripts associated with the generation of vasoactive arachidonic acid metabolites, including Lpcat2, Plcg2, Alox5 , Alox5ap, Ptgs1, Ltc4s and Hpgds, that likely contributes to the reported regulation of cerebral vascular flow by microglia ( Csaszar et al., 2022 ). As in the Csf1r -/- rat ( Patkar et al., 2021 ), the network analysis identified brain region-specific co-expression clusters that provide a signature of the lack of effect of microglial deficiency on relative abundance and differentiation status of specific neuronal and glial cell types. Cluster 1, strongly enriched in the cerebellum relative to all other brain regions contains known transcriptional regulators of cerebellar differentiation (e.g. Zic1,Zic2,Zic4,Zic5; En1, En2 ) and growth factors, as well as markers of cerebellar cell types (e.g. Calb1, Cbln1, Cbln3 ), none of which was significantly altered in expression in the microglia-deficient cerebellum ( Table S2 ). This observation contradicts the view that microglia are essential for development of the cerebellum. Conditional depletion of Csf1 and consequent loss of cerebellar microglia in mice led to defects in Purkinje cell differentiation and motor skills ( Kana et al., 2019 ). No motor deficit was identified in our cohorts using the Catwalk assay, nor in previous analysis ( Munro et al., 2024 ). However, in the CSF1 deficiency model microglia were only partly depleted and the residual microglia exhibited a damage-associated transcriptomic profile which could contribute to pathology. Cluster 4 , enriched in olfactory bulb (OB), including regulators of adult neurogenesis ( Dcx, Dlx1, Dlx2, Dlx5, Tbx21, Sall3, Lgr5, Lgr6, Sp8 ) ( Tepe et al., 2018 ) was expressed equally in WT and Csf1r ΔFIRE/ΔFIRE mice, arguing against an essential regulatory function of microglia in neurogenesis in the subventricular zone ( Morton et al., 2018 ; Ribeiro Xavier et al., 2015 ). Transcripts in Cluster 7 ,strongly enriched in striatum relative to other brain regions, included genes for transcription factors involved in differentiation of this brain region (e.g. Foxp1, Gli3, Gsx2, Isl1, Klf5, Lhx8, Pou3f4, Six3, Sox6 etc, ( Knowles et al., 2021 )) as well as the key growth factor, Gdnf ( Kholodilov et al., 2011 ). The absence of microglia had no effect on expression of these genes. Importantly, given the ability of donor-derived cells to repopulate the vacant brain niche, we found no significant effect of microglial deficiency on expression of transcripts associated with the vasculature or blood brain barrier (BBB) in any brain region. This is consistent with evidence that microglia are not required to maintain BBB integrity ( Profaci et al., 2024 ). Similarly, network analysis grouped a set of transcripts with the ependymal cell marker, transthyretin ( Ttr ) ( Cluster 24, Figure 2 ). This cluster was highly variable between samples, due to differences in contribution of ependymal cells to the mRNA pool, but unrelated to Csf1r genotype. Compensatory changes in gene expression in microglia deficient mice O’Keeffe et al . (2024) reported minor changes in astrocyte gene expression detectable by single cell RNA-seq in juvenile Csf1r ΔFIRE/ΔFIRE mice compared to WT. However, in the total RNA-seq data, the detection of some transcripts that are highly expressed by isolated microglia was not affected by the Csf1r mutation at either two weeks or six weeks. Nrros, a leukocyte-specific transcript, relatively low-expressed in brain (see BioGPS.org ) but highly-expressed in microglia ( Summers et al., 2020 ; Van Hove et al., 2019 ) was unchanged and similarly unaffected in brains of Csf1r -/- rats ( Patkar et al., 2021 ). Bi-allelic mutations in NRROS in humans are associated with an early onset neurodegenerative disease ( Dong et al., 2020 ). Nrros -/- mice develop abnormal microglia, astrocytosis and age-dependent motor deficiencies ( Wong et al., 2017 ). NRROS, also known as LRRC33, is required for latent TGFB1 activation which in turn regulates microglial and astrocyte homeostasis. Consistent with recent analysis of conditional Tgfb1 deletion in microglia ( Bedolla et al., 2024 ), Tgfb1 and Tgfbr1 were reduced in all brain areas in Csf1r ΔFIRE/ΔFIRE mice ( Table S1/2 ). Presumably in the absence of microglia, the Nrros gene is upregulated in other cell types, possibly astrocytes ( Bedolla et al., 2024 ; Hasel et al., 2021 ). Similarly, microglia in the brain are the main source of insulin-like growth factor 1 (IGF1) which is essential for postnatal neurodevelopment ( Hammond et al., 2019 ; Rusin et al., 2024 ) but Igf1 mRNA was unchanged in any brain region in Csf1r ΔFIRE/ΔFIRE mice (or Csf1r -/- rats) compared to WT at either time point. Development and survival of layer 5 cortical neurons was reported to be dependent on microglial IGF1 ( Ueno et al., 2013 ) but markers of this population ( Bcl11b, Satb2 ) were unaffected at either age. Hexb is another microglia-enriched gene in mice, purported to distinguish microglia from BAM ( Masuda et al., 2020 ). Hexb encodes one of the subunits of beta-hexosaminidase and is mutated in the lysosomal storage disease (LSD), Sandhoff disease. Hexb knockout mice exhibit many of the neuropathologies of the human disease ( Sango et al., 1996 ; Sango et al., 1995 ; Tsourmas et al., 2024 ). A recent study described the mitigation of pathology in Hexb - /- mice following repopulation of the brain by donor-derived myeloid cells ( Tsourmas et al., 2024 ) implying that microglia-derived HEXB is essential for neuronal health. The lack of neuropathology in microglia-deficient mice suggests that pathology in Hexb - /- mice is actually due to microglial dysfunction. In juvenile Csf1r ΔFIRE/ΔFIRE mice, Hexb mRNA was reduced to around 10-15% of WT in all brain regions ( Table S1/S2 ), whereas Hexa encoding the other subunit, was unaffected. The expression of Hexb is only reduced by 50% in Csf1r -/- rats ( Patkar et al., 2021 ). Presumably, Hexb can be expressed in other cell types in the microglia-deficient animals. Other lysosomal enzymes (e.g. Gla, Gba, Galc, Lipa, Gusb, Naga, Naglu, Sumf1 ) and lysosomal structural genes ( Schroder et al., 2010 ) associated with multiple rare LSD ( Akhter et al., 2019 ) are selectively expressed in microglia at levels at least 10-fold higher than total brain or other brain cell types (( Zhang et al., 2014 ), see also BioGPS.org ). Yet, of these transcripts only Gusb was significantly reduced in microglia-deficient mice suggesting they are also up-regulated in other cells to compensate. Indeed, Berdowski et al. ( Berdowski et al., 2022 ) reported an increase in lysosomal markers in astrocytes of microglia-deficient csf1r mutant zebrafish. Taken together, the data indicate that endosome/lysosome function in the brain is regulated to meet increased demand when microglia are absent. Microglial deficiency and neuropathology Csf1r ΔFIRE/ΔFIRE mice have been considered a model for dominant CSF1R-related leukoencephalopathy ( Chadarevian et al., 2024 ; McNamara et al., 2023 ; Munro et al., 2024 ) but the complete microglial deficiency in these animals has more in common with homozygous recessive CSF1R mutations ( Guo et al., 2019 ; Oosterhof et al., 2019 ) than the partial microglial depletion in patients and animal models with dominant mutations ( Berdowski et al., 2022 ; Papapetropoulos et al., 2021 ; Stables et al., 2022 ; Stables et al., 2024 ). Outbred Csf1r ΔFIRE/ΔFIRE mice do not develop the severe cognitive/motor functional deficits seen in patients with dominant mutations ( Dulski et al., 2023 ; Konno et al., 2018 ; Papapetropoulos et al., 2021 ). Patients with homozygous recessive CSF1R mutation and microglial deficiency have major structural abnormalities in the brain including callosal agenesis ( Guo et al., 2019 ; Oosterhof et al., 2019 ) whereas the white matter in Csf1r ΔFIRE/ΔFIRE mice develops normally ( Figure 5 ). Previous studies have reported evidence of patchy demyelination in the brains of Csf1r ΔFIRE/ΔFIRE mice evident at six months of age and more prevalent at 12-18 months ( McNamara et al., 2023 ; Munro et al., 2024 ). This pathology was not evident in our cohort of Csf1r ΔFIRE/ΔFIRE C57BL/6J x CBA F2 mice (50:50) at 30 weeks of age (seven months) based upon tractography or immunolocalization of MBP. It is possible that pathology would be detectable with more refined analysis or at a later age. However, the inbred C57BL/6J background likely also contributes to neuropathology ( Soni et al., 2024 ). The original studies were performed on a mixed 75% C57BL/6J x 25% CBA/J background ( McNamara et al., 2023 ; Munro et al., 2024 ). We have now shown that the ΔFIRE allele was generated on the C57BL/6J chromosome in the F1 founder. Hence, the WT controls in the original cohort must be divergent from Csf1r ΔFIRE/ΔFIRE for much of chromosome 18, which has the potential to impact neuropathology. Genetic heterogeneity may explain why a subset of the Csf1r ΔFIRE/ΔFIRE mice on the original 75% C57BL/6J mixed background showed early mortality ( Munro et al., 2024 ). In our defined F2 cohort we did confirm the striking vascular calcification in the thalamus reported previously ( Chadarevian et al., 2024 ; Munro et al., 2024 ). Calcification, which is also a feature of human CSF1R-associated leukoencephalopathy ( Dulski et al., 2023 ; Konno et al., 2018 ; Papapetropoulos et al., 2021 ) represents an exacerbation/acceleration of a process that occurs normally in aged mice ( Maheshwari et al., 2022 ; Wang et al., 2023 ). In the 5xFAD model of Alzheimer’s disease, accelerated calcification in Csf1r ΔFIRE/ΔFIRE mice was associated with dysregulation of the Pdgf/Pdgfrb axis (Kiani Shabestari et al., 2022 ). Mutations affecting this axis are associated with primary familial brain calcification (PFBC) ( Maheshwari et al., 2022 ; Maheshwari et al., 2023 ; Zarb et al., 2019 ). Elevated circulating PDGF-BB arising from osteoclast activity promotes age-dependent thalamic calcification ( Wang et al., 2023 ), so this CSF1R-related pathology may not be entirely autonomous to the brain. Indeed, Pdgfb is also involved in postnatal development of the glymphatic system ( Munk et al., 2019 ) so a link between delayed CSF1R-dependent osteoclastogenesis ( Stables et al., 2022 ) and HC is also possible. Many of the genes implicated in PFBC are expressed by astrocytes ( Maheshwari et al., 2022 ; Maheshwari et al., 2023 ; Zarb et al., 2019 ). In a mouse model of PFBC, Pdgfb ret/ret , calcifications were associated with astrocytes expressing markers associated with neurotoxicity ( Zarb et al., 2019 ). A subsequent study ( Zarb et al., 2021 ) demonstrated that microglial depletion using PLX5622 or mutation of Trem2 aggravated vessel calcification in this model. In the thalamus of Csf1r ΔFIRE/ΔFIRE mice, astrocytosis appears to precede detectable calcification ( Figure S5 ). Hence, as in the prion disease model ( Bradford et al., 2022 ) microglia likely act to constrain astrocyte-mediated pathology. Microglial repopulation by bone marrow progenitors Allogeneic bone marrow transplantation has been tested as a treatment in CSF1R-related leukoencephalopathy with varying outcomes ( Dulski et al., 2022 ) but the efficacy in terms of engraftment of the brain is not known. Repopulation of microglia in Csf1r ΔFIRE/ΔFIRE mice can be achieved by intracerebral injection of isolated microglia, or microglia generated from induced pluripotent stem cells ( Chadarevian et al., 2024 ; Kiani Shabestari et al., 2022 ; Munro et al., 2024 ). Microglial replacement prevents neuropathology in this model. Here we have shown that donor bone marrow cells can repopulate the vacant brain niche in Csf1r ΔFIRE/ΔFIRE mice without conditioning. In other studies, microglial replacement has been dependent on a vacant niche achieved by conditional deletion or treatment with a CSF1R kinase inhibitor. In different protocols, the transplanted cells include blood or bone marrow monocytes or differentiated microglia injected IV or directly into the brain ( Aisenberg, 2024 ; Bastos-J, 2024; Lund et al., 2018 ; Shibuya et al., 2022 ; Tsourmas et al., 2024 ; Xu et al., 2020 ). Our study is unique in that BMT is delivered IP and donor cells make no contribution to the bone marrow or blood monocyte population. We reported a similar outcome in Csf1r -/- rats receiving IP BMT at weaning ( Carter-Cusack et al., 2024 ; Keshvari et al., 2021 ; Sehgal et al., 2023 ) enabling complete phenotypic reversal and long-term survival. Csf1r ΔFIRE/ΔFIRE mice are not monocyte-deficient so the vascular niche is not vacant. However, the monocytes in these mice lack expression of CSF1R ( Rojo et al., 2019 ) which likely explains their failure to populate the brain and the lack of monocyte-derived amoeboid microglia in neonates. The pattern of repopulation of microglia in both mouse and rat suggests trafficking from the peritoneum and infiltration of the brain by a hematopoietic stem cell (HSC) or a committed progenitor population. Intraperitoneal transfer is a practical alternative to intravenous injection in juvenile mice and rats ( Bennett et al., 2018 ; Sehgal et al., 2023 ). It is not yet clear whether the cavity provides an essential trophic environment and whether this approach might be applicable in patients as opposed to the normal intravenous route. The poor survival of Csf1r ΔFIRE/ΔFIRE mice on the C57BL/6J background compromises generation of large cohorts for more detailed studies of aging and the possibility of preventing or reversing the pathology using BMT in older mice. To explore this possibility, we are currently generating a Csf1r ΔFIRE BALB/c line to enable homozygous breeding. A Csf1r ΔFIRE CBA/J congenic line has been deposited with Jackson Labs (Cat#032783). In summary, detailed analysis of microglia-deficient mice extends the evidence ( O’Keeffe et al., 2024 ) that microglial functions in postnatal development of the brain in mice are largely redundant and indicates compensatory regulation of endocytic function in other cell types. Microglial absence in mice leads to age-dependent pathology consistent with a primary neuroprotective function and a constraint on astrocyte activation. Adoptive transfer of WT bone marrow cells completely repopulates the vacant brain niche without contributing to blood monocytes. Future studies focus on the therapeutic potential of bone marrow-derived microglia replacement in human CSF1R-related leukoencephalopathy. Methods and Materials Animals All animal experiments in Australia were approved by The University of Queensland Health and Sciences Ethics Committee and performed in accordance with the Australian Code of Practice for the Care and Use of Animals for Scientific Purposes and Queensland Animal Care and Protection Act (2001). All experiments in Edinburgh were performed under licenses approved by the UK Home Office according to the Animals (Scientific Procedures) Act having been approved by the University of Edinburgh Local Ethical Review Board. Animals were housed in individually ventilated cages with a 12 h light/dark cycle, and food and water available ad libitum. The generation and characterisation of Csf1r ΔFIRE/ΔFIRE mice on a mixed C57BL/6J x CBA/J background (75%:25%) was described previously ( Rojo et al., 2019 ). Gene expression profiling was performed in Edinburgh on the original genetic background. Prior to import into Australia, the Csf1r ΔFIRE allele was backcrossed 10x to C57BL/6J. To enable visualisation of myeloid populations in tissues, the imported Csf1r ΔFIRE line was bred to the Csf1r -EGFP reporter transgenic line ( Sasmono et al., 2003 ) also backcrossed >10 times to the C57BL/6J genetic background. For the generation of F2 intercross lines, CBA/J and BALB/cJ mice were obtained from the Animal Resource Centre, Western Australia. The Csf1r -FusionRed reporter transgenic line generated on the C57BL/6J background was described previously ( Grabert et al., 2020 ). Cx3cr1- EGFP mice ( Jung et al., 2000 ) were provided by Dr. Liviu Bodea (University of Queensland). Specifics of mice group size and age for each experiment are provided in respective figure legends. Genomic Sequencing Adult mice were euthanised using carbon dioxide before DNA was extracted from tail or ear clips or from kidney tissue, using the Qiagen DNeasy Blood and Tissue kit. DNA was supplied to Australian Genome Research Facility (AGRF) sequencing facility, Melbourne, Australia. Pools of DNA from four Csf1r ΔFIRE/ΔFIRE mice each contained 50 ng of DNA, two pools generated from long term survivors and two from mice that succumbed to HC. DNA libraries were prepared for sequencing using the DNA PCR-Free (Tagmentation) kit (Illumina) and sequenced using the NovaSeq 150 bp PE (Illumina) at approximately 100 Gb per sample. Median autosomal coverage ranged from 31X to 54X. AGRF mapped against the mouse reference sequence GRCm38, and results were provided as variant call format (.vcf) and variant effect prediction (.vep) files. The output files were used to identify regions where there was a high density of positions which were different from the C57BL/6J reference sequence for at least some reads. The position of all non-reference reads (where total reads was ≥ 10) was plotted against read depth. This output shows the density of non-variant reads across the genome (indicated by the X axis) and of positions where copy number variation was likely (Y axis). Transcriptomic profiling Bulk tissue RNA was isolated from three brain regions at two weeks of age, and five brain regions at six weeks of age from WT and Csf1r ΔFIRE/ΔFIRE mice as described previously ( Rojo et al., 2019 ). Briefly, brains from saline perfused mice were dissected, snap frozen, and subsequently disrupted in the Precellys24 Homogenizer® (Bertin Instruments). RNA isolation was performed using the RNeasy Plus Mini kit (QIAGEN). Library preparation and paired-end RNA sequencing was performed by Edinburgh Genomics. The average read depth per sample was 54.0 million reads (median 53.3M), with a minimum of 32.3M and a maximum of 93.1M. RNA-sequencing reads were mapped to the mouse reference genome using the STAR RNA-seq aligner ( Dobin et al., 2013 ). Tables of per-gene read counts were generated using featureCounts ( Liao et al., 2014 ). Further details and primary data are available at ( https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-14156 ). Tissue collection for flow cytometry Peripheral blood was collected via cardiac puncture into EDTA-coated tubes and analysed using an automated hematology analyser, Mindray BC5000 Haematology Analyser (TRI Flow Cytometry Facility). Blood was then subjected to red blood cell lysis for 2 min in lysis buffer (150 mM NH 4 Cl, 10 mM KHCO 3 , 0.1 mM EDTA, pH 7.4), followed by two PBS washes and resuspension in FACS buffer (1x PBS with 2% FBS) for staining. Peritoneal cells were collected by lavage with 5 mL of PBS, centrifuged at 400 g for 5 min at 4°C, and resuspended in 1 mL of FACS buffer for staining. Bone marrow was prepared by flushing cells from femurs and tibias with 10 mL of PBS into a tube on ice, then centrifuging at 400 g for 5 min at 4°C. The pellet was resuspended in 1 mL of FACS buffer for staining. Brain tissues were processed using enzymatic digestion and density gradient centrifugation. Collagenase Type IV (10 mg) was prepared in 10 mL HBSS (1 mL 10× HBSS diluted in 9 mL RO water), supplemented with 20 µL DNase I (10 mg/mL) and 1 mg dispase per 10 mg collagenase. Isotonic Percoll gradient was prepared by combining 8.44 mL Percoll, 0.94 mL 10× PBS, and 15.63 mL 1× PBS. Mice were euthanized, and brains were dissected, halved sagittally, weighed, and minced using a scalpel in a Petri dish containing collagenase solution. The tissue was transferred to a Falcon tube and incubated on a rocking platform at 37°C for 45 min. The digested tissue was filtered through a 70 µm strainer into a 50 mL tube using a syringe plunger and brought to 25 mL with PBS. After centrifugation at 500 g for 5 min at 4°C, the pellet was resuspended in 12.5 mL isotonic Percoll and centrifuged at 800 g for 45 min at 4°C (no brake). The myelin layer and supernatant were removed, and the pellet was washed twice with 20 mL FACS buffer. The final pellet was resuspended in FACS buffer. Spleens were dissected and transferred to 50 mL Falcon tubes containing 5 mL of FACS buffer. Each spleen was mechanically dissociated by gently pressing it through a 40 µm cell strainer using the plunger of a 5 mL syringe. The cell suspension was collected into a 50 mL Falcon tube, and the strainer was rinsed with an additional 10 mL of FACS buffer. After centrifugation at 400 g for 5 min at 4°C, the supernatant was discarded, and the pellet was washed twice with PBS. The final cell pellet was resuspended in 1 mL of FACS buffer. Flow cytometry Cell preparations were incubated for 45 min on ice in 2.4.G2 hybridoma supernatant to block Fc receptor binding. Cells were stained using antibody mixtures comprising combinations of CD45-BV395 (BD Biosciences), CD11b-BV510, Ly6G-BV785 and F4/80-AF647 (Biolegend). Csf1r -FusionRed signal was acquired by PE channel, and Csf1r -EGFP was acquired by FITC channel. After washing, cells were resuspended in 100 μL FACS buffer. 10 min before analysis, 5 μg/mL 7-AAD (Thermo Scientific) was added for dead cell exclusion. Cells were examined on an LSMFortessaTM X-20 (BD Biosciences) and analysed using FlowJo v.10, focusing on live cells after exclusion of scatter and doublets. Immunohistochemistry, immunofluorescence, and imaging For free-floating sections, adult mice were euthanised, brains were dissected from the skull and immersion fixed in 4% PFA for 5 hours at room temperature (RT), washed once in PBS and stored in PBS with 0.1% Sodium Azide. Brains were serially sectioned at 30 μm in the sagittal plane using a Leica VT1200S vibratome, and sections were transferred to a 24-well-plate and washed in PBS before staining. Sections were incubated in permeabilization buffer (1% Triton-X, 0.1% Tween-20 in PBS) for 1 h at RT, followed by blocking buffer (4% serum, 0.3% Triton-X, 0.05% Tween-20 in PBS) for 1 h at RT then primary antibody diluted in blocking buffer overnight at 4◦C on a rocking platform. Primary antibodies included rabbit anti-IBA1 (1:500, Novachem, 019-19741), chicken anti-IBA1 (1:500, Synaptic Systems, 234 009), rabbit anti-GFAP (1:500, Dako, Z0334), chicken anti-GFAP (1:500, Invitrogen, PA1-10004), guinea pig anti-TMEM (1:500, Synaptic Systems, 400 004), rat anti-MBP (1:500, abcam, ab7349), rabbit anti-RFP (0.5ug/ml, abcam ab62341), rabbit anti-P2RY12 (1:500, Alomone Labs, APR-012), guinea pig anti-parvalbumin (1:500, Synaptic Systems, 195 004). To label perineuronal nets, brain sections were co-stained with Wisteria floribunda agglutinin (WFA; Merck, L1516) diluted 1:500 in blocking buffer. To label thalamic calcification, brain sections were co-stained with AF647-RIS Imaging Reagent (BioVinc LLC, BV500101) diluted 1:500 in blocking buffer. After overnight incubation, brain sections were washed 3 x 5 min with PBS then incubated for at least 2 h in appropriate fluorophore-labelled secondary antibodies (Donkey anti-rabbit AF647 (1:500, Invitrogen, A31573); goat anti-chicken AF594 (1:500, Invitrogen, A32759); donkey anti-rabbit AF488 (1:500, Invitrogen, A21206); goat anti-rat AF647 (1:500, Invitrogen, A48265); goat anti-chicken AF488 (1:500, Invitrogen, A32931); goat anti-rabbit AF594 (1:500, Invitrogen, A32740); donkey anti-rabbit CF633 (1:500, Merck, SAB4600129)) diluted in blocking buffer. Sections were once again washed 3 x 5 min with PBS before nuclei were stained with DAPI (1:5000, Thermo Scientific, 62248) for 5 min. Sections were washed a final time and mounted onto glass slides with Fluorescence Mounting Medium (Dako). Slides were stored at 4◦C in the dark. Free floating sections were also incubated in 1% w/v Alizarin Red S (1% Alizarin Red S Sigma Cat# A5533 in RO water, pH 5.5) with orbital agitation for 10 min at RT. Sections were washed with PBS 3 x 5 min and mounted using Dako fluorescence mounting media. For paraffin-embedded sections, brains were sectioned at 6 µm using a Leica RM2245 microtome. After dewaxing and rehydrating the tissues, endogenous peroxidases were quenched by immersion in 4% H 2 O 2 in methanol for 5 min. For detection of astrocytes, sections were incubated overnight with primary antibody rabbit polyclonal anti-GFAP (Dako, Glostrup, Denmark) diluted 1:2000. Primary antibody binding was detected using biotinylated goat anti species-specific antibodies (Jackson Immunoresearch, Cambridge, UK) and visualised using the Elite ABC/HRP kit (Vector Laboratories, Peterborough, UK) and diaminobenzidine (DAB) (Merck, Glasgow, UK) between stringent washing steps. Sections were lightly counterstained with hematoxylin. For the detection of endogenous calcium, deparaffinised sections were immersed in 2% Alizarin Red S solution in water (pH 4.1) for 5 min followed by quick rinses in acetone, 50:50 acetone-xylene and finally clarified in xylene. Neonatal mice were euthanised by decapitation before their brains were dissected out of skulls and fixed in 4% PFA overnight at RT. Brains were washed once in PBS before cryoprotection in 30% sucrose solution for 48 hours, frozen in OCT and stored at -80℃ until sectioning. Brains were sectioned coronally at 40 μm using a cryostat. Sections were fixed again in 4% PFA for 10 min, before immersed in ice-cold methanol for 10 min. Blocking buffer (4% serum, 0.3% Triton-X, 0.05% Tween-20 in PBS) was applied for 2 hours before sections were incubated in primary antibodies rabbit anti-IBA1 (1:500, Novachem, 019-19741) and chicken anti-GFAP (1:500, Invitrogen, PA1-10004) diluted in blocking buffer overnight at 4℃. Primary antibodies were then discarded, and sections were washed 3 x 5 min with PBST before incubation in secondary antibodies Donkey anti-rabbit AF647 (1:500, Invitrogen, A31573); goat anti-chicken AF594 (1:500, Invitrogen, A32759) diluted in blocking buffer for 2 hours at RT. Sections were washed 3 x 5 min again and DAPI stained before they were cover-slipped. Evans Blue intracerebroventricular injection To investigate the nature of HC, mice were anaesthetised using isoflurane and the superior side of the skull was exposed. Mice then received intracerebroventricular injection of Evans Blue dye. Mice were kept anaesthetised for 10 min to allow the flow of cerebrospinal fluid before euthanasia, extraction of the brain and visualisation of dye within the ventricular system. Gait analysis The gait of unforced moving mice was analysed with the CatWalk TM XT system (Noldus Information Technology, Wageningen, The Netherlands). The CatWalk XT system involves a 1.3 m black corridor on a green-lit (default intensity 16.5 volts, intensity threshold 0.10) glass plate, covered by a red ceiling light (default intensity 17.7 volts) and detection by a high-speed camera (100 frames per second, default camera gain 20). CatWalk XT was operated in a dedicated dark and quiet room and habituation and experimental procedures were performed during the same period between 9am and 3pm. Compliant runs were between 1.5 and 6 seconds. Mouse brain magnetic resonance imaging (MRI) 30-week-old mice were perfuse-fixed with 0.1M Phosphate Buffer with 1% EM-grade glutaraldehyde. Brains were subsequently fixed for 3h at RT then transferred to PBS with 0.01% sodium azide until magnetic resonance imaging (MRI). Fixed brains were washed in PBS with 0.2% v/v gadopentetate dimeglumine (Magnevist, Bayer, Leverkusen, Germany) for 4 days to shorten the T 1 relaxation and enhance MRI contrast ( Kurniawan, 2018 ). MRI data were acquired using a 16.4 T vertical bore microimaging system (Bruker Biospin, Rheinstetten, Germany; ParaVision v6.01) equipped with Micro2.5 imaging gradient and a 15 mm linear surface acoustic wave coil (M2M, Brisbane, Australia). Three-dimensional (3D) T 1 /T 2 *-weighted gradient echo images were acquired with the following parameters: repetition time (TR) = 50 ms, echo times (TE) = 12 ms, bandwidth = 50 KHz, field of view (FOV) = 19.6 × 12 × 9 mm and matrix size = 654 × 400 × 300, which resulted in 30 μm 3D isotropic image resolution and image acquisition time of 56 mins. 3D diffusion-weighted image (DWI) data were acquired using a Stejskal-Tanner DWI spin-echo sequence with TR = 200 ms, TE = 23 ms, δ/Δ = 2.5/12 ms, bandwidth = 50 KHz, FOV =19.6 × 12 × 9 mm and matrix size = 196 × 120 × 90, image resolution = 100 μm, 30 direction diffusion encoding with b-value = 5000 s/mm 2 , two b = 0 images, with the acquisition time of 16 h 2 min. Susceptibility-weighted imaging (SWI) was generated for the mouse brain data using Paravision 6.0.1. The anatomical images were constructed by combining multi-echo images to enhance image contrast. Images were registered into the Waxholm Space MRI/DTI template and the C57BL/6J mouse brain MRI atlas ( Ma et al., 2005 ) using ANTs diffeomorphic image registration ( Avants et al., 2011 ). The model-based segmentation of brain regions was performed on each sample and their image volumes and intensities were measured using ITK-SNAP. Bone marrow cell transfer Bone marrow cells were harvested from the tibia and femur of Csf1r -FusionRed ( Grabert et al., 2020 ) female mice. The bones were flushed with a solution containing 0.9% sodium chloride and 2% heat-inactivated foetal bovine serum (FBS). The cell suspension was then filtered through a 70µm cell strainer and centrifuged at 500 g for 5 min at 5°C. The pelleted cells were resuspended in 1x sterile PBS supplemented with 2% heat-inactivated FBS (10mL per bone) for cell counting using a haemocytometer (Reichert, U.S.A). Following counting, cells were centrifuged and resuspended in sterile Dulbecco’s phosphate-buffered saline (DPBS, Gibco, 10010-023) + 2% FBS. 2 × 10 7 Csf1r -FusionRed bone marrow cells in 100µl were administered intraperitoneally (i.p.) to 3 week old recipients. Mice were harvested 12 weeks post bone marrow transfer. Image quantification and analysis For confocal microscopy, a FV3000 confocal microscope was used to acquire images using 4x - 40x objectives. The percentage area of positive staining was calculated using the ‘ Measure ’ tool in (Fiji Is Just) ImageJ (Fiji; version 2.14.0), following adjustment of the brain region-specific threshold, which was kept consistent for all mice. For quantification of MBP a minimum of four images per brain region were analysed for each mouse, for three mice of each genotype. For quantification of GFAP and Risedronate, one region was analysed per section using colour thresholding with MaxEntropy method, with the same threshold used across three mice of each genotype. For quantification of PNNs and PV neurons, two regions of somatosensory cortex were analysed per mouse, for three mice of each genotype. For quantification of microglial ramification in Figure 7E , ImageJ Fiji was used to visualise individual colour channels. A bandpass filter ( Process > FFT > bandpass filter ) was applied before the image was converted to grayscale. The bandpass filter was used to remove noise (filtered up to 3 pixels, down to 200 pixels, no stripe suppression). Brightness and contrast were adjusted ( Image > Adjust > Brightness/Contrast) to visualise microglia processes. To further clarify image detail, an Unsharp Mask filter ( Process > Filters > Unsharp Mask) was used (pixel radius 3; mask weight 0.5). This mask can produce unwanted salt-and-pepper noise, which was removed with a subsequent despeckle step ( Process > Noise > Despeckle ). Images were then converted to binary ( Image > Adjust > Threshold ) before a second despeckle function was applied along with close-off ( Process > Binary > Close ) and remove outliers ( Process > Noise > Remove Outliers; pixel radius 3, threshold 50) functions. Next, images were skeletonised ( Process > Binary > Skeletonise ) and the AnalyseSkeleton(2D/3D) plugin was run ( Plugins > Skeleton > Analyse Skeleton ). Some analysed fragments were trimmed from the data (i.e. all fragments with only 2 endpoints). The number of branches and junctions was measured for 3-4 different cells per 20x image, for 2-3 biological replicates per genotype. MRI data analysis The FID of DWI datasets were zero-filled by a factor of 1.5 in all dimensions prior to Fourier transform to improve fibre tracking. DWI data were bias corrected using ANTs N4BiasFieldCorrection and processed using MRtrix3 software ( www.mrtrix.org ). Fiber orientation distribution (FOD) was reconstructed using constrained spherical deconvolution (CSD) method, and probabilistic tractography was performed using iFOD2 algorithm. Tractography was performed for specific major white matter (WM) tracts. Firstly, the seeding regions of interest (ROIs) were manually drawn in the midsagittal and coronal sections of the colour vector map, and fibre tracks were generated for the corpus callosum (CC), hippocampal commissure (HC), internal capsule (IC) and anterior commissure (AC) at 100 seeds per voxel. The volumes of the white matter tracts were measured from Tract Density Intensity maps (TDI) ( Calamante et al., 2012 ) with the intensity threshold set at 20% to remove background noise from probabilistic tracking. Data analysis Data analysis was performed using GraphPad Prism (V 10). For comparing two groups, an unpaired Student’s t-test or Mann-Whitney test was applied. For comparisons involving three or more groups, one-way or two-way ANOVA followed by Sidak’s multiple comparison test was utilized. Significance was determined at a 95% confidence interval with p values < 0.05. Resources View this table: View inline View popup Download powerpoint Legends to Figures Figure S1. Severe hydrocephalus in Csf1r ΔFIRE/ΔFIRE mice on the C57BL/6J background Coronal sections of brains from WT (A) and Csf1r ΔFIRE/ΔFIRE (B) mice highlight extreme enlargement of the lateral ventricles in mice with hydrocephalus. To dissect the mechanism, Evans Blue was injected as shown in (C). (D) shows dorsal, ventral, lateral, and medial views of the brain of WT (+/+, upper) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ, lower). Note the dilated lateral ventricle (LV) and exclusion of dye from the 3rd ventricle and dorsal 3 rd ventricle (3V, D3V), aqueduct (AQ), 4th ventricle (4V) and hindbrain in the mutant compared to the WT. Figure S2. Whole genomic sequencing of Csf1r ΔFIRE/ΔFIRE mice DNA was isolated from mutant mice that developed hydrocephalus and long-term survivors. Whole genome sequences were generated from two pools, each containing DNA from four mice. Sequences were mapped to the C57BL/6J reference genome. Images show the read count for non-reference sequences, highlighting blocks derived from non C57BL/6J origin. The block on distal Chr16 is the likely location of the Csf1r- EGFP transgene. Datapoints in red on Chr18 highlight an excess of non-reference reads mapped to the location of the Csf1r gene. The promoter used in the Csf1r -EGFP reporter is from a non-C57BL/6J source and also contains a mutated start codon. Figure S3. Catwalk analysis of motor function in Csf1r ΔFIRE/ΔFIRE mice Gait analysis as described in Materials and Methods was performed weekly on cages of mixed genotype mice of both sexes (n = 10) blinded to the operator. For the gait parameters, three compliant runs of each mouse made up the testing run. Following acquisition of the whole data set, runs were grouped by genotype and age. Two-way ANOVA was used to compare the average values of the three runs for each WT and Csf1r ΔFIRE/ΔFIRE mouse, with age and genotype as the two factors. Data presented as mean ± 95% confidence interval. No significant difference based upon genotype was detected. Figure S4. Lack of effect of Csf1r ΔFIRE/ΔFIRE mutation on white matter. Figure shows additional tractography images and quantitation related to analysis of the 30-week cohort in Figure 5 . Fractional anisotropy (FA) is defined as an index of the amount of anisotropy in white matter, often used as a quantitative biomarker of white matter integrity. Graphs show mean ± SEM from three mice of each genotype. *, p < 0.05, not significant if corrected for multiple testing. Figure S5. Astrocytosis precedes calcification in the thalamus in Csf1r ΔFIRE/ΔFIRE mice Figure shows representative images of the thalamus of Csf1r ΔFIRE/ΔFIRE mice on the original C57BL/6J/CBA (3:1) background stained as indicated. In a cohort of 15 mice at 3 months, 10 showed substantial astrocytosis detected with anti-GFAP without evident calcification. Figure S6. Detection of donor-derived cells in Csf1r ΔFIRE/ΔFIRE mice following bone marrow cell transfer (BMT). Csf1r ΔFIRE/ΔFIRE / Csf1r- EGFP mice were injected IP with Csf1r- FusionRed (FRed) donor bone marrow cells at weaning (3 weeks) and engraftment was analyzed 12 weeks later. (A) Representative flow cytometry profiles of blood, bone marrow and spleen cells harvested from Csf1r ΔFIRE/ΔFIRE recipients. (B) Representative images of detection of the two reporter transgenes in the dentate gyrus of the hippocampus from WT (+/+) and Csf1r ΔFIRE/ΔFIRE (Δ/Δ) recipients. Scale bar = 100 µm. Figure S7. Foci of microglial repopulation in Csf1r ΔFIRE/ΔFIRE mice following bone marrow cell transfer (BMT). Csf1r ΔFIRE/ΔFIRE mice were injected IP with wild-type donor bone marrow cells at weaning (3 weeks) and engraftment was analyzed 3 (A) and 5 (B) weeks post transfer by immunolocalisation of IBA1 (green) on free floating sections. Acknowledgments The Irvine, Hume and Summers laboratories gratefully acknowledge core funding from The Mater Foundation, Brisbane, Australia. The generation, breeding and analysis of the Csf1r ΔFIRE/ΔFIRE mice in Edinburgh was funded by a grant from the Medical Research Council (MRC) UK grant MR/M019969/1 to DAH. Additional support was provided by the Simons Initiative for the Developing Brain and by the UK Dementia Research Institute, which receives its funding from DRI Ltd, funded by the UK Medical Research Council, the Alzheimer’s Society and Alzheimer’s Research UK. The current work was supported by Australian National Health and Medical Research Council (NHMRC) Grant GNT1163981 awarded to DAH and KMS. DAH is supported by NHMRC (Australia) Investigator Grant 2009750. We thank Dr. Liviu Bodea for the Cx3cr1 GFP/+ mice. We acknowledge input and expertise from the Biological Resources facility and the Preclinical Imaging, Microscopy, Histology and Flow Cytometry facilities of the Translational Research Institute (TRI) and The Roslin Institute. TRI is supported by the Australian Government. 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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. You are going to email the following Repopulation of the brain with microglia-like cells following intraperitoneal bone marrow cell transfer in microglia-deficient mice Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Repopulation of the brain with microglia-like cells following intraperitoneal bone marrow cell transfer in microglia-deficient mice Isis Taylor , Omkar L. Patkar , Yajun Liu , Sebastien Jacquelin , Ginell Ranpura , Dylan Carter-Cusack , Adam Ewing , Nyoman D. Kurniawan , Mosi Li , Deepali Vasoya , Xin He , Owen R. 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