High-parameter cytometry unmasks microglial cell spatio-temporal response kinetics in severe neuroinflammatory disease

Background Differentiating infiltrating myeloid cells from resident microglia in neuroinflammatory disease is challenging, because bone marrow-derived inflammatory monocytes infiltrating the inflamed brain adopt a ‘microglia-like’ phenotype. This precludes the accurate identification of either cell type without genetic manipulation, which is important to understand their temporal contribution to disease and inform effective intervention in its pathogenesis. During West Nile virus (WNV) encephalitis, widespread neuronal infection drives substantial CNS infiltration of inflammatory monocytes, causing severe immunopathology and/or death, but the role of microglia in this remains unclear. Methods Using high-parameter cytometry and dimensionality-reduction, we devised a simple, novel gating strategy to identify microglia and infiltrating myeloid cells during WNV-infection. Validating our strategy, we (1) blocked the entry of infiltrating myeloid populations from peripheral blood using monoclonal blocking antibodies, (2) adoptively transferred BM-derived monocytes and tracked their phenotypic changes after infiltration and (3) labelled peripheral leukocytes that infiltrate into the brain with an intravenous dye. We demonstrated that myeloid immigrants populated only the identified macrophage gates, while PLX5622 depletion reduced all 4 subsets defined by the microglial gates. Results Using this gating approach, we identified four consistent microglia subsets in the homeostatic and WNV-infected brain. These were P2RY12hi CD86−, P2RY12hi CD86+ and P2RY12lo CD86− P2RY12lo CD86+. During infection, 2 further populations were identified as 'inflammatory' and 'microglia-like' macrophages, recruited from the bone marrow. Detailed kinetic analysis showed significant increases in the proportions of both P2RY12lo microglia subsets in all anatomical areas, largely at the expense of the P2RY12hi CD86− subset, with the latter undergoing compensatory proliferation, suggesting replenishment of, and differentiation from this subset in response to infection. Microglia altered their morphology early in infection, with all cells adopting temporal and regional disease-specific phenotypes. Late in disease, microglia produced IL-12, downregulated CX3CR1, F4/80 and TMEM119 and underwent apoptosis. Infiltrating macrophages expressed both TMEM119 and P2RY12 de novo, with the microglia-like subset notably exhibiting the highest proportional myeloid population death. Conclusions Our approach enables detailed kinetic analysis of resident vs infiltrating myeloid cells in a wide range of neuroinflammatory models without non-physiological manipulation. This will more clearly inform potential therapeutic approaches that specifically modulate these cells. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-021-02214-y.

therapeutic intervention have yet to be elucidated. One of the unresolved questions surrounding the in ux of myeloid cells in the CNS during this disease, is how their role differs from the resident microglia.
Some of these studies implicate a role for microglia in effective T cell responses (24,25,27), crosspresentation to cytotoxic T cells (29), monocyte recruitment and maturation (22,25,27), and phagocytosis of infected neurons (22). On the other hand, microglia have been implicated in hippocampal-dependent learning and memory de cits after recovery from neuroinvasive Zika and WNV infection (30,31). However, to our knowledge, no studies have attempted to identify and immunophenotype microglia or examine their behavior in any detail in the intact brain over the course of lethal viral encephalitic infection.
We report a novel ow cytometric gating strategy to identify and characterize in ltrating macrophages and microglia in homoeostasis and severe neuroin ammation. During WNE, in ltrating macrophage populations expressed standard myeloid and even 'microglia-speci c' markers. In contrast, four distinct microglial phenotypes, distinguishable by their CD86 and P2RY12 expression, were found in both homeostasis and disease. Microglia proliferated early in infection, but by day 7 had decreased in number, signi cantly altering their phenotypic, morphological and cytokine status. Further immunophenotypic analysis showed that microglia and macrophages exhibit spatial and temporal disease-speci c phenotypes during infection.

Mice
Female 9-10-week-old C57BL/6 mice were obtained from the Animal Resource Centre (ARC) (Western Australia, Australia) and kept in individually ventilated cages under speci c pathogen-free conditions with access to food and water ad libitum -in accordance with National Health and Medical Research Council's ethical guidelines. All experiments were completed with animal ethics approval number K20/05-2016/976 approved by the University of Sydney Animal Ethics Committee.
Mice were anesthetised before they were infected intranasally (i.n.) with 1.2 x 10 5 plaque-forming units (PFU) of WNV delivered in 10 µL (a dose of WNV that is lethal in 100% of mice (lethal dose 100%, LD 100 )) of sterile phosphate-buffered saline (PBS) (as previously described (1)). The original stock acquired from The John Curtin School of Medical Research (ACT, Australia) was propagated alternately in C57BL/6 suckling mouse brains and in vitro in Vero cells (3). Mice were sacri ced no later than day post infection (dpi) 7. Intravenous leukocyte staining. PKH67 cell-linker was mixed with diluent C (Sigma-Aldrich -MO, USA) as per the manufacturer's instructions prior to use. PKH67 cell-linker was used at a 10-fold higher concentration than recommended and injected intravenously 3 hours prior to tissue collection.
Anti-BrdU (3D4 or Bu20a, Biolegend) was stained intranuclearly as previously described (32 The bone marrow from dpi 5 WNV-infected mice were isolated from femurs, tibias and humeri. Two donors were used per recipient. Red blood cells (RBC) were lysed using RBC lysis buffer (Biolegend). Single cell suspensions were then incubated with anti-CD16/32 and LIVE/DEAD Blue (UVLD) (Invitrogen) before being incubated with uorescently-labelled antibodies against CD45, CD115, CD11b, Ly6C, Ly6G and B220. Ly6C hi monocytes were sorted on an In ux cell sorter using the FACSDiva Programme (Becton Dickinson). The gating strategy used is shown in Niewold et al. (2018). The purity of the sorted cells was > 90% and ~ 3 × 10 5 cells were transferred to each recipient. These cells were labelled with carboxy uorescein succinimidyl ester (CFSE) (Sigma-Aldrich -MO, USA) to the manufacturers' instructions and injected intravenously into matched WNV dpi 5 recipients in 200 µL sterile PBS. Recipients were sacri ced on dpi 7 and brains were isolated and processed for ow cytometry, as described above.

Imaging mass cytometry
Brains were isolated from mice perfused transcardially with PBS and 2% PFA. Brains were cut sagittally and placed in 2% PFA overnight, subsequent to being placed in a gradient of sucrose solutions (10%, 20%, and 30%). Murine brains were frozen in optimal cutting temperature (O.C.T.) compound (Tissue-Tek, Tokyo Japan) in hexane pre-chilled in liquid nitrogen. Frozen brain sections (8-9 µm) were xed in methanol, rinsed in tris-buffered saline with 0.05% Tween 20 (TBST) and blocked with 10% FCS. Excess solution was shaken off before primary uorophore-conjugated antibodies  Biolegend)). Iridium DNA intercalator (Fluidigm, 1:2000 in TBST) was applied to brain sections, prior to sections were rinsed in UltraPure water and left to air dry. If slides were not immediately ablated on the Hyperion, they were stored at 4°C until use.

Image generation
Once slides were imaged on the Hyperion, mass cytometry data (MCD) les were exported from the Hyperion acquisition software. For image generation, MCD les were imported into HistoCAT + + where false colour was applied to relevant channels.

RNAse Protection Assay
The RNAse protection assay (RPA) was performed for IL-12 (p35), IL-23 (p19), IL-12/IL-23 (p40), TNF, IL-6, IFN-γ, and IL-17A. The genomic clone RPL32-4A, a probe for the ribosomal protein L32 (provided by M. Hobbs, The Scripps Research Institute, San Diego, CA), was used as an internal control for RNA loading during RPA analysis. Brie y, total RNA was extracted from perfused brains using TRIzol reagent (Sigma Aldrich) according to the manufacturer's instructions. For each RPA analysis, 5 µg of RNA was used.

Statistical analysis
Non-parametric statistical tests were applied to data in GraphPad Prism 8.4.3 (GraphPad Software, La Jolla, CA). Comparison of two groups was conducted using Mann-Whitney test, and three or more groups were compared using a Kruskal-Wallis test with a Dunn's multiple comparison test. When two independent variables and three or more groups were being compared a Two-way ANOVA and a Šídák's or Tukey's multiple comparisons test was used. P-values of < 0.05 were regarded as signi cant and designated in gures as *P < 0.0332, **P < 0.0021, ***P < 0.0002, ****P < 0.0001. Error bars are shown as standard error of the mean (SEM).

Results
Classic ow cytometric gating fails to discriminate resident from in ltrating myeloid cells during severe in ammation During viral encephalitis, the overlapping expression of cell surface markers makes the identi cation of resident and in ltrating myeloid cells in the CNS di cult by standard gating approaches. We therefore set out to identify the minimum parameters required to delineate these populations accurately. Cells were dissociated from murine brains at various timepoints in the progression of lethal WNE. Figure 1a-c shows a clear CD45 lo , CD11b hi microglial cell population which expresses low levels of Ly6C in the brain parenchyma of dpi 0 mice. However, from dpi 3 onwards this discrete microglial cell population became progressively obscured by the overlapping antigen expression of increasing numbers of CD45 hi , CD11b hi , Ly6C hi in ltrating BM-derived monocytes. From dpi 5-7 these monocytes showed further CD45 and CD11b upregulation with some downregulation of Ly6C ( Fig. 1a-d). Compounding this, by dpi 5, microglia had also upregulated CD45 and Ly6C (Fig. 1a, b), making it impossible to separate these populations accurately by standard gating during WNE.
To resolve this, we used the 'microglia-speci c' markers, Transmembrane Protein 119 (TMEM119) (36) and purinergic receptor P2Y12 (P2RY12) (10). However, while collagenase/DNase treatment substantially increases leukocyte yields and live:dead cell ratios during preparation of single cell suspensions (Additional le 1), TMEM119 did not label cells prepared this way (Fig. 1e, f). This has not previously been reported, to our knowledge. Ironically, without enzyme treatment, TMEM119 was downregulated on microglia at dpi 7, precluding the use of this microglia-speci c marker to distinguish between resident and in ltrating myeloid cells (Fig. 1g). On the other hand, P2RY12 was unaffected by enzyme treatment, but was expressed both by a discrete CD45 int/lo population at day 0 and on different populations of CD45 int/hi cells at dpi 7 (Fig. 1h). Thus, it was also unclear whether this purinergic receptor, putatively expressed only by microglia, was also expressed by an in ltrating CD45 hi macrophage population. It should be noted that collagenase/DNase was used in the remainder of this study for optimal brain cell preparation, except where TMEM119 was measured.
High parameter cytometry and dimensionality-reduction can delineate resident and in ltrating myeloid cells As shown above, the discrimination of microglia from in ltrating myeloid cells in severe neuroin ammatory conditions is unreliable, even with the use of 'microglia-speci c' markers. Other groups have distinguished microglia from macrophages based on the higher macrophage expression of CD44 (37, 38), VLA-4 (39), CD11a (40), CCR2 and Ly6C. In WNE, the expression pro le of these markers on some in ltrating myeloid cells, viz., Ly6C hi CD45 int and Ly6C int CD45 int was similar to microglia in the infected brain (Additional le 2). Thus, we were also unable to distinguish these populations using these markers. To address this issue, we labelled cells for myeloid cell markers (CD45, CD11b, F4/80), 'activation/functional' myeloid markers (CD11c, MerTK, CD64, CD68 CD86, MHC-II), 'in ltrating/in ammatory macrophage' markers (CCR2, Ly6C) and markers 'speci c' for and/or highly expressed on microglia (P2RY12, TMEM119, CX3CR1) and analysed them by uorescence ow cytometry. We visualized the acquired high parameter data on a 2D plot after subjecting it to T-distributed Stochastic Neighbor Embedding (tSNE), which clusters cell populations based on similarity of marker expression (41). We then generated a series of gating strategies to identify discrete populations clustered on the tSNE plot.
We therefore generated and compared further gating strategies to determine the feasibility of more accurately distinguishing resident from in ltrating myeloid populations (Fig. 2). Microglia were identi ed as Ly6G − CX3CR1 + CD45 lo/int CD11b + Ly6C −/lo (Gating strategy 2, Fig. 2j, k), Ly6G − , CX3CR1 + CD45 lo/int CD11b + P2RY12 + Ly6C −/lo (Gating strategy 3, Fig. 2l, m) and Ly6G − , CD45 int/lo , PR2Y12 + , CX3CR1 hi − lo , CD11b + (Gating strategy 4, Fig. 2o, p). Strategies 2 and 3 resulted in the inclusion of various populations outside of the putative microglial cluster in the tSNE plot, while strategy 4 identi ed a single microglial cluster with very little contamination from other cells. Strategy 4 used the fewest markers and gates, the simplest gating, and was thus least susceptible to error. We employed gating strategy 4 to further investigate the identities and change kinetics of these populations during WNE. Nevertheless, since strategies 2 and 4 gave putative microglial numbers that were not statistically different (Figs. 2q, r), previous data using standard markers prior to the availability of P2RY12 could be re-analysed more accurately using strategy 2.
Modulating CNS in ltration veri es non-microglial populations in Gating strategy 4.
In order to con rm that Gating strategy 4 was accurately distinguishing resident from in ltrating myeloid populations during WNE, we employed 3 approaches. We 1) blocked the entry of myeloid populations in ltrating into the brain from peripheral blood, 2) adoptively transferred BM-derived monocytes and tracked their phenotypic changes after in ltration and 3) injected intravenous dye to label peripheral leukocytes that in ltrate into the brain.
In ltration of cells into the brain parenchyma was blocked using an antibody cocktail made up of of anti-VLA-4 (3), CCL2 (1) and Ly6C (45) (Fig. 3a) at dpi 5 and 6. This resulted in a 90-95% reduction in the number of in ltrating Ly6C hi in ammatory and a population of 'microglia-like' macrophages (i.e., nonmicroglial myeloid cells present in the infected brain with a CD45 + , CX3CR1 + and CD11b + pro le similar to microglia, but absent in the homeostatic brain). This was associated with a commensurate depletion in the corresponding areas of the tSNE plot. Importantly, the antibody cocktail did not reduce numbers of putative microglia in animals treated with blocking antibodies, compared to untreated animals ( Fig. 3b-d).
This suggests that Gating strategy 4 identi es microglia, even during highly in ammatory conditions.
Unexpectedly, the use of the isotype control antibody cocktail increased the number of microglia and in ltrating macrophages compared to untreated mice (Fig. 3d), raising the question of whether some of the in ltrating cells were falling into the putative microglia gate. To investigate this, we adoptively transferred CFSE + BM-derived CD115 + , CD45 + , CD11b + , Ly6C hi , Ly6G − , B220 − monocytes from dpi 5 WNVinfected mice, into recipient age-, sex-and time-matched WNV-infected animals and harvested the recipient brains on dpi 7 (Fig. 3e). Analysis shows that all of the transferred cells fell outside the identi ed putative resident microglia tSNE cluster (Fig. 3f-h) and appeared in both the in ltrating Ly6C hi in ammatory and 'microglia-like' macrophage gates (Fig. 3i).
Considering only a small number of transferred cells could be tracked via adoptive transfer, we also injected mice with PKH67 three hours prior to collecting brain tissue, to de nitively distinguish in ltrating from resident myeloid populations (Fig. 3j, k). At dpi 5, 6 and 7, the majority of PKH67 + cells in ltrating WNV-infected brains were in ltrating monocytes or lymphocytes, while cells in the putative microglial cluster showed no staining. Taken together, the data strongly suggests that this cluster only represents the resident microglia.
Microglia adopt 'disease-speci c' immunophenotypes in WNE Using Gating strategy 4, we then proceeded to investigate the immunophenotypic heterogeneity and response of microglia during WNE. We pre-gated live, CD11b + , CD45 + myeloid cell populations and ran tSNE analysis on the concatenated dpi 7 WNV-infected and mock-infected populations (Fig. 4a-c).
Strikingly, the microglial cluster in the homeostatic brain was in a different position on the tSNE plot from that in the infected brain. This indicates a substantial phenotypic change in microglia during infection ( Fig. 4a-c). Consistent with this, at dpi 7 all microglia phenotypes had downregulated TMEM119, CX3CR1, F4/80 and CD68 and upregulated CD45 and CD64. (Fig. 4d-f and Additional le 5). However, in contrast to the signi cant downregulation of TMEM119, P2RY12 expression was relatively stable from dpi 0 to 7 ( Fig. 4d-h). Notwithstanding these phenotypic changes, the same four distinct subsets could be identi ed throughout the disease course.
At dpi 7, the P2RY12 hi microglia subsets in both mock-infected and infected brain had higher expression of all measured markers, compared to the P2RY12 lo subsets (Fig. 4f- (Fig. 4e). Both populations had varied expression of MerTK, CD86, CD11c, MHC-II and CCR2, as well as TMEM119 and P2RY12. Since peripheral myeloid populations in the blood and bone marrow expressed neither TMEM119 nor P2RY12 (Additional le 6 and 7), this indicates that myeloid cells upregulated these 'microglia-speci c' markers, de novo after CNS in ltration.
Microglial phenotypes depleted by PLX5622 are not brain region-speci c Abrogating myeloid and lymphoid cell in ltration using systemic antibody blockade, did not reduce microglial numbers (Fig. 3d, 5a, b). In contrast, the 4 phenotypes de ned by CD86 and P2RY12 expression were substantially and proportionally decreased in animals treated with chow containing CSF1R inhibitor, PLX5622. (Fig. 5c, d). Taken together, these data strongly suggest that these cells are resident microglia.
There have been limited reports of a CD86-expressing microglial population in the homoeostatic or infected brain. Therefore, we rst established that the expression of CD86 was not a result of the reported non-speci c binding of cyanine dyes (APC-Cy7 - Fig. 4) to macrophages (Additional le 8). To further con rm this, we examined brain sections for a CD86 + microglia using metal-labelled antibodies in imaging mass cytometry (IMC). At dpi 5 with minimal myeloid cell in ltration, microglia were readily identi able by their rami ed morphology and Iba1 + and Ly6C − expression pro le. These cells were CD86 + in various regions of the brain (Fig. 5e, f).
In dissecting the brain into 5 separate regions, viz., olfactory bulb, frontal cortex, posterior cortex, pons/medulla and cerebellum, the 4 identi ed microglial phenotypes were found in all areas by ow cytometry (Fig. 5g). This indicates that these phenotypes are not region-speci c and supports the IMC data. Nevertheless, there was signi cant variation in the proportion of each microglial subset between these anatomical areas, both under homeostatic conditions and in response to WNV infection (Fig. 5h, I,   6b). Under homeostatic conditions, the largest group was the CD86 − microglia, with the P2RY12 hi subset comprising 68-80% and the P2RY12 lo subset, 13-28%. The CD86 + subsets together comprised less than 5% of microglia. In response to WNV, there was an increase in the proportions of both P2RY12 lo subsets in all anatomical areas by dpi 7, principally at the expense of the P2RY12 hi CD86 − (Fig. 5h, i).
Microglia in the olfactory bulbs had the highest expression of CX3CR1, F4/80, CD68 and MHC-II in both the homeostatic and infected brain. However, in WNV-infected brains they had the lowest expression of CD11b, TMEM119 and P2RY12 of all the anatomical sites ( Fig. 6a-b). Considering WNV enters the olfactory bulb and remains there over the course of infection, downregulation of these markers in this model could be a result of prolonged neuronal infection and exposure to neuroin ammation.
Downregulation of TMEM119 and P2RY12 has been reported in a number of chronic neuroin ammatory models (46-48).
Considering the demonstrable progression of infection from rostral to caudal over time, it was of interest to determine changes in marker expression on microglia in the cerebellum. The cerebellum shows limited neuronal infection at dpi 7, despite a broad interferon-stimulated gene response (49). Cerebellar microglia had a higher CD11b and MerTK expression and lower CX3CR1, F4/80, CD68 and MHC-II expression than the olfactory bulb. Nevertheless, proportions of both P2RY12 lo subsets were similarly increased in response to WNE in both regions (Fig. 5h, i).
More striking was the differential pro le of Ly6C hi macrophages in these brain regions at WNV dpi 7 (Fig. 6c, d). From caudal to rostral, in ltrating Ly6C hi macrophages had progressively downregulated Ly6C and upregulated CX3CR1, TMEM119, P2RY12, CD64, CD68 and MHC-II. Resident and in ltrating cells in all regions remained distinct, clustering in separate groups on the tSNE plot. However, they were clustered more closely together rostrally, indicating a phenotype closer to microglia in the olfactory bulb (Fig. 5g, 6c).

Temporal changes in microglial phenotypes during WNE
The microglial phenotypes we identi ed in the naïve and WNV dpi 7 brain were also present at dpi 4-6 of WNE. With increasing infection in the brain, all microglia showed signi cant temporal phenotypic changes ( Fig. 7a-e). Measured markers were progressively a) upregulated, b) downregulated or c) upregulated and then downregulated, indicating changes in potential activity and functions at different disease stages (Fig. 7a, c-e).
From dpi 4, the total microglia population upregulated CD45, increased their granularity (side scatter area -SSC-A) and progressively downregulated CX3CR1, F4/80 and CD68 over the course of infection. At dpi 5 and 6 microglia showed peak expression of several cell surface markers, including CD64, MerTK, CD86, MHC-II, CCR2 (low levels) and Ly6C, which were subsequently downregulated by dpi 7 (Fig. 7c-e). While P2RY12 was expressed by all microglial subsets, average expression was reduced on the total microglial population by dpi 7. This was due to a combination of P2RY12 down-regulation only on P2RY12 lo cells and an increase in the proportion of this subset over the course of infection.
Changes in microglial immunophenotypes correlated with monocyte in ltration and neuronal infection from dpi 4. Microglia also exhibited a reactive morphology by dpi 5, with hypertrophied cell somata and shortened cytoplasmic extensions (Fig. 7a, b). This was similar in other brain regions, irrespective of the presence of virus (data not shown).

Microglia proliferate early and die late in infection
Using Gating strategy 4, kinetic analysis revealed a decrease in the number of total microglia later in infection, with their proportions reducing dramatically due to the increasing numbers of other leukocytes immigrating into the brain (Fig. 8a, b). Within this population, the number and proportion of the P2RY12 hi CD86 − microglial subset decreased against an increase in the number and proportion of the other subsets from dpi 4-5 (Fig. 8c, d). Furthermore, notwithstanding the lack of signi cant change in microglial cell numbers early in infection, microglia proliferated from dpi 4, as shown by the incorporation of BrdU (Fig. 8e-i). At dpi 5, the peak of microglial cell proliferation, P2RY12 hi CD86 − microglia showed the greatest incorporation of BrdU (Fig. 8g). From dpi 5-7 microglial proliferation decreased (Fig. 8e-i), while the frequency of lymphocyte proliferation increased over this time, and MDM proliferation was minimal Coinciding with reduced microglial cell numbers by dpi 7, there was also an increased number and percentage of dead microglia (Annexin V + , Live/Dead stain + ) from dpi 6 onwards. However, the proportions of apoptotic microglia (Annexin V + only) were not signi cantly different over this time (Fig. 8jl). Strikingly, the population with the highest proportion of dead and dying cells at dpi 5, 6 and 7 were microglia-like macrophages (Fig. 8l). The increased number of dead microglia explains, at least in part, why proliferation of microglia at dpi 5 did not correspond to an increase in microglial numbers at dpi 6 or 7.
Microglia are the principal producers of IL-12 during lethal WNE To elucidate the function and contribution of microglia to protective or pathogenic responses in WNE, we stained for a series of intracellular cytokines readily detected without in-vitro stimulation, to minimise non-physiological conditions (Fig. 9). We formerly showed that IL-12, TNF, IFN-g, CCL2, IL-10, IL-1a/b and IL6 are upregulated in WNV-infected brains (1)(2)(3)50). Consistently with previously published work, Ly6C hi macrophages and T cells were the principal source of NO and IFN-g, respectively (Fig. 9a) (3,50). Ly6C hi macrophages also had the highest expression of CD206, con rming that macrophages can express both pro-and anti-in ammatory markers simultaneously. Microglia-like macrophages expressed NO and CD206 only marginally, suggesting a less in ammatory, alternative role for these cells. Of interest, was the primary production of IL-12/IL-23 p40 by microglia in the later phase of disease (Fig. 9a, d-i). Since IL-23 shares the p40 subunit with IL-12, we performed an ELISA (Fig. 9b) and RNAse protection assay (Fig. 9c) on total brain protein and RNA, respectively, to discriminate between these cytokines. Marginal to no IL-23 (p19/p40) protein or IL-23 (p35) RNA was found in WNV-infected brains, indicating that IL-12 and not IL-23 was most likely to be produced by microglia. Notably, while the P2RY12 hi CD86 + microglia subset had the highest frequency of IL-12/IL-23 p40 + cells (Fig. 9i), P2RY12 hi CD86 − microglia, as the largest subset, produced most of the IL-12 (Fig. 9h). This suggests that these cells have role in T cell activation.

Discussion
In the homeostatic CNS, multifarious gating strategies enable accurate identi cation of microglia by ow cytometry. However, under severe neuroin ammatory conditions, such as those induced by WNE, substantial numbers of in ltrating in ammatory monocytes adopt an activated microglial phenotype (1,44), precluding the use of standard gating strategies. Accurately distinguishing microglia from in ltrating MDMs in the in amed brain is required to determine their respective contribution to disease pathogenesis and/or recovery, potentially informing therapeutic approaches that target these cells. Here we report for the rst time, a simple, novel gating strategy to distinguish microglia from in ltrating myeloid cells under both homeostatic and extreme in ammatory conditions. This gating strategy minimizes user gating bias and maximizes accuracy of population analysis and sorting, and can be applied to a range of other neuroin ammatory models. Using this approach, we identi ed four consistent microglia subsets in the homeostatic and WNV-infected brain. These were P2RY12 hi CD86 − , P2RY12 hi CD86 + , and P2RY12 lo CD86 − P2RY12 lo CD86 + . The four subsets identi ed in the homeostatic brain were phenotypically distinct from those in the infected brain, suggesting a change in their function and activity. Indeed, microglia adopted spatial and temporal disease speci c signatures with increased neuronal infection. In stark contrast to the in ltrating myeloid population, microglia proliferated early in WNE, whilst late in disease they produced IL-12 and underwent apoptosis, indicating clear differential responses of each population.
To validate our gating strategy, we 1) blocked monocyte in ltration into the CNS, 2) adoptively transferred Thus, previously published approaches cannot readily discriminate between microglia and in ltrating myeloid cells in our model, although 4D4, another nominal microglia-speci c marker (56, 57), which was not used in this report, may be of value.
While we have not studied the detailed functions of the identi ed microglial subsets, kinetic analysis of cell surface expression strongly imply changes in function between these subsets over the course of disease. Indeed, signi cant increases in both P2RY12 lo microglial subsets occurred principally at the expense of the P2RY12 hi CD86 − subset, accompanied by a marked increase in BrdU incorporation in the latter, suggesting differentiation from the P2RY12 hi CD86 − subset with compensatory proliferation.
Microglia with a higher expression of P2RY12 may be more important in responding to virus infection. In PRV infection, P2RY12 was required for microglial migration and phagocytosis of virus-infected neurons (22). In contrast, this purinergic receptor may be less important in neurodegeneration, as it is consistently downregulated in AD, ALS and EAE, along with TMEM119 (46-48). On the other hand, the two CD86 + microglial cell populations are likely to be involved in antigen presentation and T cell activation. A CD86 + population has also been identi ed in the CNS in both homeostasis and EAE (39). Conversely, the CD86 − microglial subsets may have a role in chemotaxis, complement-mediated function and phagocytosis of iC3b or IgG/antigen complexes, based on their higher expression of CD11b, CD11c and CD64.
Over the course of infection, the total microglia population progressively downregulated CX3CR1, F4/80, TMEM119 and CD68, and progressively upregulated CD45. In contrast, expression of CD64, MerTK, CD86, MHC-II, CCR2 and Ly6C peaked at dpi 5 and 6, but decreased by dpi 7. Given the downregulation of these immunologically important markers, the role of microglia may be more critical early in disease, as Here, we also show the upregulation of 'microglia-speci c' markers on in ltrating Ly6C hi and microglialike macrophages, in particular, in the rostral parts of the brain. Similarly, in two stroke models, macrophages in ltrating the CNS (58) or ectopically placed in peri-infarct areas (59), became TMEM119 + and/or P2RY12 + and /or Sall1 + . The prolonged time spent in the CNS, may induce in ltrating cells to become more microglia-like, since the unique brain microenvironment shapes the identity of microglia (12). Microglia-like macrophages may represent a distinct subset arising from BM during infection, although they are likely to differentiate from Ly6C hi in ltrating macrophages, because their numbers are proportionately reduced when immigration of Ly6C hi monocytes is blocked with monoclonal antibodies.
The microglia-like macrophage population in WNE brains also had the greatest population of apoptotic and dead cells. Thus, once Ly6C hi macrophages enter the brain, they may acquire a microglia-like phenotype and eventually die after performing effector functions.
Alterations in the microglial cell immunophenotypic landscape from dpi 4 also correlated with their increased incorporation of BrdU, which increased further by dpi 5. The reduced proliferative capacity from dpi 6 onwards was accompanied by an increase in microglial cell death. It has previously been suggested that aviviral infection does not promote microglial proliferation (30,31) and that increased numbers of 'microglia' during WNE were due to the in ltration of BM-derived cells (1). Our study emphasizes the importance both of accurate microglial cell identi cation as well as detailed examination of kinetic changes during infection. Microglial cell proliferation has been well documented in JEV (60), TMEV (55, 61) and VSV infection (28), as well as in EAE (62). Furthermore, similar to our ndings, the frequency of proliferating microglia in EAE increased then decreased over the course of disease, with TUNNEL + apoptotic microglia detected in the later phases (39,46). Microglial proliferation and apoptosis is tightly coupled (9). We hypothesize that microglia proliferate early in infection to enhance the response against WNV, but further proliferation becomes redundant as increasing numbers of MDMs enter the brain parenchyma. The increased number of dying microglia in WNE brains presumably enable these cells to return to homeostatic numbers. This may also apply in EAE.
We found that microglia were responsible for the primary expression of IL-12 in the later phase of infection. Similarly, in TMEV-infection, microglia exclusively expressed Il12b and Il12rb1 (55). A previous report showed TLR7-IL-23-dependent homing of peripheral immune cells to the brain in WNV-infected mice (63). In contrast, we found limited IL-23. This could be due to differences in virus strain or inoculation routes.
The precise functions subserved by microglia and MDM subsets identi ed here remain to be fully determined. IL-12 production supports a role for microglia in enhancing NK and T cell responses to aid viral clearance. Consistent with this, recent studies showed ineffective CD4 + T cell (25) or CD8 + T cell (27) responses in viral infection following microglial depletion with PLX5622. However, it must be noted that, as well as causing mass microglial death, requiring yet unde ned processes to clear these cells, PLX5622 also modulates other myeloid cells dependent on CSF1R signaling (64). Thus, the non-physiological conditions imposed by PLX5622 may perturb normal immune responses, making it di cult to de ne the contributions of microglia to disease. This emphasizes the need to examine these cells without depletion. Using intravital imaging Moseman et al., 2020, con rmed the involvement of microglia to an effective T cell response in VSV encephalitis. Microglia were required for cross-presentation to CD8 + T cells, to contain and prevent the fatal spread of VSV (29). In WNE, since microglia produce IL-12 in the later phase of disease, production could also be a response to T cells producing large quantities of IFN-γ at dpi 7 (3), as IFN-γ can stimulate the production of either IL-12 subunit (65).

Conclusions
Historically, the convergence of resident and in ltrating myeloid cell phenotypes in the in amed brain has hindered our understanding of the function of microglia in disease. While new investigative tools have improved population resolution and analyses of these cells, these are unreliable in the in amed brain.
Microglia-speci c markers were downregulated by microglia and/or expressed de novo by peripherallyderived cells in WNV-infection, while microglial cell depletion with PLX5622 can target peripheral cells and create non-physiological conditions in the brain. Here, we devised a simple gating strategy to identify and track microglia during severe in ammatory changes in the CNS, while maintaining the natural immune status of the animal. Using this approach, we showed that resident microglia undergo unique temporal-and spatial-speci c alterations from MDMs. This approach can be applied to other neuroin ammatory models to understand the contribution of microglia to disease, as well as to inform therapeutics that can speci cally target and modulate these cells in WNE.

Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.  and with blockade treatment (c). d Number of microglia, Ly6Chi, Ly6Clo and microglia-like macrophages in WNV dpi 7 brains from non-treated animals and animals treated with isotype control antibodies or anti-VLA-4/Ly6C/CCL2 blocking mABs. Data is presented as mean ± SEM, with six mice per group,  Dimensionality-reduction analysis reveals four microglia subsets that adopt distinct phenotypes in WNE.
tSNE plots showing the relative intensity of selected markers/parameters in mock-infected (d) and The identi ed microglial subsets are not peripherally derived nor represent region-speci c phenotypes. a-d Microglia 'subsets' gated and overlaid onto tSNE plots representing WNV dpi 7 brains from animals treated with isotype (a) and VLA-4/CCL2/Ly6C blockade antibodies (b) and mock-infected brains from animals treated with (d) and without (c) PLX5622. e, f IMC images of the hippocampus (e) and mid-brain