Mitochondria are absent from microglial processes performing surveillance, chemotaxis, and phagocytic engulfment

Domain: biology
Published: 2025-12-12
Editorial outcome: major_revision

Abstract
Microglia continually surveil the brain allowing for rapid detection of tissue damage or infection. Microglial metabolism is linked to tissue homeostasis, yet how mitochondria are subcellularly partitioned in microglia and dynamically reorganized during surveillance, injury responses, and phagocytic engulfment in the intact brain are not known. Here, we performed intravital imaging and ultrastructural analyses of microglia mitochondria in mice and human tissue, revealing that microglial processes diverge in their mitochondrial content, with some containing multiple mitochondria while others are completely void. Microtubules and hexokinase 2 mirror this uneven mitochondrial distribution indicating that these cytoskeletal and metabolic components are linked to mitochondrial organization in microglia. Microglial processes that engage in minute-to-minute surveillance typically do not have mitochondria. Moreover, unlike process surveillance, mitochondrial motility does not change with animal anesthesia. Likewise, the processes that acutely chemoattract to a lesion site or initially engage with a neuron undergoing programmed cell death do not contain mitochondria. Rather, microglia mitochondria have a delayed arrival into the responding cell processes. Thus, there is subcellular heterogeneity of mitochondrial partitioning. Moreover, microglial processes that surveil and acutely respond to damage do not contain mitochondria.

Introduction
Microglia serve as the resident phagocyte of the central nervous system. They are a highly dynamic, innate immune cells capable of functions that span tissue surveillance to pathological responses1,2. They do this by continually extending and retracting their extensively branched processes to probe the environment for infection or injury. In the case of a focal injury, microglia display immediate process chemotaxis, effectively barricading the injury site to prevent further damage to the parenchyma3,4. Subsequent microglial phagocytosis mediates engulfment and clearance of cellular debris, ultimately facilitating a return to homeostasis from this inflammatory injury. Microglia also perform phagocytosis without inflammatory stimuli via specialized phagocytic receptors that recognize damaged or dying cells or cell compartments (efferocytosis)5–9. Together, surveillance, chemotaxis, and phagocytosis involve radical morphological changes in microglia, but our understanding of how the internal cellular architecture changes alongside these cell behaviors is incomplete.

Mitochondria are signaling hubs involved in many processes ranging from cell metabolism, calcium handling, cell death and proliferation, and the generation of reactive oxygen species (ROS)10,11. Mitochondrial subcellular localization influences these multifunctional roles and their proximity to other organelles or positioning near cell-cell contacts enhances their ability to integrate and respond to intracellular and extracellular stimuli10. Mitochondria are also dynamic organelles capable of transport throughout the cell mediated by the cytoskeleton, and changing shape through fission and fusion events, each of which have been linked to the metabolic state of the cell10,12–14.

In aging and neurodegeneration, microglial function is dysregulated, potentially contributing to the pathology rather than helping the system return to homeostasis2,15–24. In this state, microglia exhibit mitochondrial dysregulation shown by increased ROS emission, mitochondrial DNA damage, and metabolic dysfunction24–27. Additionally, inflammatory environments alter mitochondrial shape in microglia in vitro, which coincides with a microglial bioenergetic shift and an increase in pro-inflammatory cytokine release28–31. Moreover, targeted manipulation of distinct mitochondrial genes such as uncoupling protein 2 and hexokinase 2 within microglia has revealed diverse roles for mitochondria in microglial physiology and pathology32–36. However, it remains to be explored how mitochondrial shape and motility change as microglia perform surveillance, phagocytosis, and respond to injury in the healthy brain.

In this study, we define the microglia mitochondrial dynamics at homeostasis to provide a baseline of the mitochondrial phenotype as microglia carry out their multifaceted functions. To investigate microglia mitochondria, we generated a triple transgenic mouse with microglia and their mitochondria endogenously labeled with separate fluorescent markers. This enables us to study mitochondrial morphology and motility in live animals while maintaining microglia in their native microenvironment. Together, our data establish the dynamics and morphometrics of microglia mitochondria in vivo, and indicate heterogeneity of process function within a single microglial cell.

Results
Mitochondrial morphometrics in mouse neocortical microglia
Inflammatory stimuli shift the bioenergetics of cultured microglia which coincides with a morphological change of mitochondria in microglia28–31. However, mitochondrial morphometrics (content, shape, and subcellular distribution) and motility have not been characterized in microglia in the healthy, live, and intact brain. To visualize mitochondria specifically within microglia, we generated a triple transgenic mouse line, Cx3cr1-creER:Ai9:PhAM, enabling dual fluorophore expression in the cell cytoplasm (Ai9) and mitochondrial matrix (Dendra2) driven by tamoxifen-inducible Cre recombination (Fig. 1a, Supplementary Fig. 1a,b, and Supplementary Movie 1). We confirmed that Dendra2 reliably labeled the mitochondria in the cell by quantifying the overlap of Dendra2 and another mitochondrial marker, TOMM20 (95% overlap from 80 spots from 16 cells from 4 mice; Supplementary Fig. 2). These results are consistent with past reports of reliable labeling of mitochondria with this mouse line32,37,38. To make the brain optically accessible for intravital imaging, cranial window surgeries were performed over the somatosensory cortex (Supplementary Fig. 1a). Immediately after the surgery, high resolution optical images were taken, then the microglia cytoplasm and mitochondria were 3 dimensionally (3D) segmented (Supplementary Fig. 1c). Using the volumes extracted from the 3D segmentations, we found the mitochondrial to cytoplasmic volume fraction in the whole cell and the compartments: soma and processes to be respectively ~10%, 17%, and ~8% (Fig. 1b). The soma contained relatively few but large mitochondrial networks by volume while the mitochondria occupying the processes were smaller in volume but greater in number (Fig. 1a, c). Mitochondrial shape was also determined within these cellular compartments with circularity and aspect ratio measurements as mitochondrial morphology has been correlated to metabolic fitness13,39. The circularity of the soma and process mitochondria showed no difference; however, the aspect ratio showed that the process mitochondria were more elongated than the soma mitochondria (Fig. 1f).

To determine where mitochondria reside within microglia, Sholl analysis was done on the cytoplasmic and mitochondrial segmentations. The microglia branching complexity increased as the density of branching increased (peaking at ~20um away from the cell center) and then dropped when moving to the tips of the processes, as expected40,41. However, this peak increase in complexity was not observed with the mitochondrial Sholl analysis, which linearly decreased when radiating away from the cell center to the tips of the processes (Fig. 1d). To measure this in a more detailed way, the mitochondrial occupancy in individual primary processes was determined. A primary process was identified from the branch shooting off from the soma and all connected branches (see primary processes labeled in different colors in Fig. 1e). Like the Sholl analysis, mitochondrial occupancy linearly decreased moving from the soma to the tips of the primary processes (Fig. 1e). Therefore, the complexity of the microglia cytoplasm does not dictate where there will be an increase in mitochondria presence. These analyses establish the baseline for mitochondrial morphometrics in the healthy intact brain, and can serve as a reference as to how mitochondrial morphometrics may change in neuroinflammatory and neurodegenerative states.

Mitochondrial morphometrics in human neocortical microglia
To determine if the microglial mitochondrial morphometrics were consistent across species, we used a publicly available human electron microscopy dataset (H01) that was collected from 1 mm3 of the temporal cortex42. We selected 6 microglia to segment, and confirmed their identity based on nuclear ultrastructure and cell cytoplasmic morphology43. We then created 3D segmentations of the cytoplasm, nucleus, and mitochondria (Fig. 2a, Supplementary Fig. 7 and Supplementary Movie 2). The mitochondria to cytoplasmic volume fraction in the whole cell, soma, and processes was between 2.5% and 3.5% (Fig. 2a,d). We also found that the mitochondria in the soma were larger in volume but fewer in quantity, whereas the mitochondria in the processes were smaller in volume but greater in quantity (Fig. 2b,c, e). Moreover, the Sholl analysis showed that mitochondria are more abundant at the cell center and linearly decrease to less abundant at the process tips (Fig. 2f). Not only are these findings consistent with the mouse mitochondrial morphometrics, but this electron microscopy dataset also provides the resolution to distinguish individual mitochondria and validates our findings made with the resolution capabilities of fluorescence microscopy.

Mitochondria are heterogeneously partitioned throughout microglia processes
By qualitative observation it was apparent that some processes had little to no mitochondria, while other processes had many mitochondria in both mouse and human neocortical microglia (Fig. 3a, b and Supplementary Fig. 8a). To represent this quantitatively, the mitochondrial volume in each primary process was plotted against the primary process length, and indeed, primary processes from the same cell had similar lengths, but varied in their total mitochondrial volume (Fig. 3c). To determine if the mitochondrial shape differed in these primary processes, we used the mitochondrial volume to separate the primary processes in two groups, designating primary processes as having high (>67.1μm3) or low (<67.1m3) mitochondrial volume (Fig. 3d). We then compared the shape of the mitochondria in each group. This analysis revealed that the primary processes with low mitochondrial volume had more circular mitochondria compared to processes with high mitochondrial volume that had more elongated mitochondria (Fig. 3e and Supplementary Fig. 8b). Given these data, mitochondria are not uniformly distributed in mouse or human microglia, raising the question of whether there are other structural differences between these processes.

To further analyze the heterogeneity of microglia processes, we used the H01 dataset to look at the proximity of microglia processes to other structures in the parenchyma. We focused on microglia process tips as reference points for distance measurements and discrete regions for comparison to mitochondrial content. Vasculature in the parenchyma is a prominent source of nutrients and energetic fuel. However, we found no correlation between mitochondrial content and distance to blood vessels (Fig. 4a,b). Neurons are also key communication partners for microglia44,45. Most of the microglia analyzed here formed soma-soma contacts with neurons, while those without soma-soma contacts were close to a neuron soma (Fig. 4c). We found no correlation between the distance from microglia soma to neuron soma and whole-cell mitochondrial content (Fig. 4d). Similarly, focusing on microglia process tips, no correlation was found between distance to neighboring neuron soma and mitochondrial content (Fig. 4c, d). While this analysis only begins to address the extensive array of contacts between microglia and other cells (Fig. 4e), these data suggest that proximity to blood vessels or neuronal somas does not relate to the uneven partitioning of mitochondria in microglia.

Given the heterogeneous partitioning of mitochondria in microglial processes, we next hypothesized that mitochondria would be near microtubules (MTs) since they are involved in mitochondrial anchoring, transport, and function13,46–48. To visualize MTs in parallel with the cytoplasm and mitochondria, we generated a triple transgenic mouse line, Cx3cr1-creER: Ai9: Kaleidoscope, enabling triple fluorophore expression in the microglial cytoplasm (Ai9), mitochondrial matrix (mKate2), and MTs (eGFP) (Fig. 5a). Intravital 2-photon imaging showed that MT and mitochondrial localization in microglia was comparable with some microglial processes containing a robust MT network and others completely lacking microtubules and mitochondria (Fig. 5). Quantification revealed that MTs were more likely to be present in microglial processes that contained mitochondria (Fig. 5e). These findings reveal that MTs likely influence how mitochondria are heterogeneously partitioned in some microglial processes and not in others.

Hexokinase 2, but not hexokinase 3, localizes to mitochondria in microglia
Having established that cytoskeletal differences underly the asymmetric distribution of mitochondria, we next considered the role of metabolic proteins. Specifically, we determined the distribution of hexokinase 2 (HK2) and 3 (HK3) in microglia. Hexokinase is required for the first step of glycolysis, and the HK2 isoform has been gaining traction in the microglia field due to its relevancy in neuroinflammation and neurodegeneration33,49–55. HK2 and HK3 are two isoforms of hexokinase family that are highly expressed by microglia relative to other cells in the mouse CNS; human microglia are also selective expressors of HK2, but not HK356,57; therefore, these were ideal candidates to begin understanding what metabolic components may be connected to heterogenous partitioning of mitochondria in microglia.

To determine hexokinase subcellular localization in microglia we immunostained for HK2 and HK3 in fixed brain tissue (Fig. 6a,b). First, the mitochondrial to cytoplasmic area fraction confirmed there was heterogenous distribution of mitochondria in microglia (Fig. 6c), corroborating our previous findings that were obtained from intravital optical imaging immediately after the cranial window surgery (Fig. 3). Visually, it was apparent that HK2 specifically localized to microglia, while HK3 expression is more widespread (Fig. 6a,b). Quantitatively, we found that HK2, but not HK3, had significantly more signal localized to microglial processes with high mitochondrial occupancy (Fig. 6a,b, d). Moreover, 75% of mitochondria co-localized with HK2, while only 7% of mitochondria co-localized with HK3 (Fig. 6a,b, e). These data show that HK2 localizes to mitochondria in microglia while HK3 is more widely expressed by other cells in the CNS and lacks specificity within the microglial cytoplasm. Thus, cytoskeletal and metabolic components also have heterogenous partitioning in microglia, supporting the notion that microglial processes of the same cell may carry out different functions simultaneously.

Microglial branches and process tips lacking mitochondria are more motile
To investigate mitochondrial localization and microglial process behavior, we next assessed mitochondrial positioning and motility as microglia carry out their canonical surveillance behavior. To do this, mice were imaged every 1 min for 30 min to enable minute-to-minute tracking of mitochondria in microglia (Fig. 7). First, the stability of 100 branches across 25 cells was assessed. A tracked branch defined as “stable” was present at 0 min and 30 min, and a “lost” branch was present at 0 min, but gone at 30 min. Twenty-eight percent of branches were lost, and 72% were stable (Fig. 7a). Of all branches assessed at 0 min, half contained mitochondria (Fig. 7a). Notably, there was a greater percentage of lost branches that did not have mitochondria (Fig. 7a, Supplementary Movie 3), suggesting that processes lacking mitochondria are more motile. Since much of the surveillant motility occurs at the tips of processes1,58 we quantified the number of tips that contain mitochondria and found that only 18% have mitochondria, supporting the idea that mitochondria are less likely to be present in motile processes (Fig. 7b). In support of this, quantification of the total distance traveled and instantaneous velocity for a subset of microglial process tips showed that processes without mitochondria moved more (Fig. 7c). Process tips that did have mitochondria were either stable for the entirety of the imaging session or retracted, but were never observed to extend (Fig. 7c).

Next, to further determine overall mitochondrial motility vs. rearrangement of the microglial cytoplasm, we quantified the percent increase in area taken up by the cytoplasm and mitochondria at 0 min and in a temporal projection containing all 30 time points (seen as 0→30 min in Fig. 7d). The mitochondria to cytoplasmic fraction significantly decreased in the temporal projection compared to 0 min (Fig. 7d,e). Comparably, the percent change in area fraction of only the cytoplasm (60%) is significantly greater than the mitochondrial percent change in area fraction (37%) (Fig. 7d,f). Together, mitochondrial motility does not match the microglia process motility, suggesting that mitochondria are not often associated with processes that are performing tissue surveillance, particularly with regards to process extension.

Mitochondrial motility in microglia is not altered by animal anesthesia
Past work has shown that microglia surveillance behavior changes under different physiological states59,60. Based on this, we reasoned that if mitochondrial motility is associated with microglial process motility, then a change in mitochondrial motility would be correlated with a change in brain physiological state. Thus, we next determined if different physiological states also alter mitochondrial motility in microglia. To do this, we imaged mitochondrial motility in the same microglia as mice transitioned from awake to anesthetized conditions. Animals were first imaged awake for 30 min, then switched to isoflurane anesthesia and imaged for another 30 min (Fig. 8a, c). The change in process area fraction showed that microglia were significantly less motile during wakefulness compared to when the mice were under isoflurane anesthesia (Fig. 8a, b and Supplementary Fig. 9), consistent with previous reports59,60. However, mitochondrial tracking showed that the mitochondrial displacement and percentage of motile mitochondria were both unchanged in the awake and anesthetized conditions (Fig. 8d and Supplementary Movie 4). Thus, arousal state does not affect mitochondrial motility, again suggesting a disconnect between microglial process surveillance and mitochondrial motility.

Microglial processes acutely responding to a laser lesion do not contain mitochondria
Given that mitochondria were often not found in surveilling motile microglial processes, we next assessed mitochondrial motility in the context of microglial pathological response to acute tissue damage by a laser lesion. A 30 min time-series was acquired before the laser lesion, and immediately after the lesion a 45 min time-series was taken to capture the microglia and mitochondrial response to the lesion (Fig. 9). To quantify the response, the changes in fluorescence of the cytoplasmic and mitochondrial signals were measured in a region of interest (ROI) around the lesion site (Fig. 9a,b). As expected1,3, multiple microglial processes immediately responded to the laser lesion; these processes arrived around the lesion site within minutes and sustained their presence for hours (Fig. 9c–e and Supplementary Movie 5). Unexpectedly, mitochondria were not in the processes that responded to the lesion within the 45 min time frame (Fig. 9c–e and Supplementary Movie 5). To determine if mitochondria arrive later, an image was taken at 1 h and 6 h after the lesion. At 1 h, there were still little to no mitochondria at the lesion site (Supplementary Fig. 10), but at 6 h mitochondria occupied the processes extending to the lesion site (Fig. 9c–e). Therefore, microglial processes that immediately chemotax to the site of acute tissue damage do not have mitochondria, rather, the mitochondria have a delayed arrival into the processes responding to the lesion.

Mitochondria are delayed in their arrival to microglial processes engulfing dying neurons
Finally, we investigated the mitochondrial dynamics and subcellular localization when single microglia clear apoptotic neurons. Targeted two-photon chemical apoptotic ablation (2Phatal) involves photobleaching single nuclei to trigger apoptotic death of neurons (Fig. 10a)5. Nuclear condensation can be observed post-2Phatal (Fig. 10a), and the neuronal corpses are cleared by microglia within 24 h5,6. Therefore, 2Phatal serves as a valuable method to track mitochondria as microglia undergo the transition from recognition to early engagement engulfment of a targeted neuron. An example of individual microglia actively clearing neuronal corpses 6 h after 2Phatal can be seen alongside stable microglia that maintained their location and morphology in the parenchyma (Fig. 10a).

Stages of microglial engagement were tracked at 3, 6, and 24 h post-2Phatal and defined as (1) no engagement, (2) partial process cup formation, (3) process engulfment, and (4) soma engulfment (Fig. 10b). At 3 h, all nuclei were partially condensed with most microglia forming a partial process cup around the nucleus. Of the microglia processes surrounding the nucleus, half were lacking mitochondria, and half had less than 50% mitochondrial presence (Fig. 10b). As the microglia engagement increased to full process or soma engulfment at 6 and 24 h, there was also an increase in mitochondrial presence within the process or soma engulfing the corpse (Fig. 10b and Supplementary Fig. 11). Fluorescent intensity measurements showed that microglia engagement gradually increased as observed in Fig. 10b (Fig. 10c and Supplementary Fig. 11). However, mitochondrial presence in the cytoplasm surrounding the nucleus was not significantly increased until 6 h after 2Phatal (Fig. 10c). Overall, very few mitochondria are found in the engulfing microglial processes at 3 h post-2Phatal, but significant mitochondrial presence became evident only at 6 h and was sustained when microglia were fully engulfing the dying cell. These findings emphasize a lack of mitochondrial presence in microglia processes during the initial stages of phagocytic engulfment of dying neurons.

Methods
Animals
The triple transgenic mouse model used in this study, Cx3cr1-creER: Ai9: PhAM, was generated by breeding the following mouse lines together: Cx3cr1-creER (JAX strain #020940)80, floxed tdTomato (JAX strain #007909)81, and PhAM (JAX #018385)37. This line has conditional expression of cytoplasmic localized tdTomato (Ai9) and mitochondrial matrix localized Dendra2 (PhAM) to all CX3CR1+ cells, which are predominantly microglia in the central nervous system, but can also target border associated macrophages, therefore, no vascular associated macrophages were analyzed in this study. The other triple transgenic mouse model, Cx3cr1-creER: Ai9: Kaleidoscope, used in this study was generated by breeding the following mouse lines together: Cx3cr1-creER (JAX strain #020940)80, floxed tdTomato (JAX strain #007909)81, and Kaleidoscope (JAX strain #038639)82; enabling parallel imaging of microglial cytoplasm (tdTomato, Ai9), and their mitochondria (mKate2), microtubules (eGFP), and lysosomes (BFP). Of note, the lysosomes were not analyzed for the purposes of this study. All animals used were heterozygous for creER to prevent knock out of Cx3cr1. To mediate Cre recombination, mice were administered an intraperitoneal (i.p) injection (0.05 mL) of tamoxifen (Sigma-Aldrich #T2859-1G) dissolved in corn oil (20 mg/mL) every other day for 5 days (total of 3 injections) at weaning. Both male and female adult mice were used at 2–6 months for the experiments83. All animal procedures were approved by the Institutional Animal Care and Use Committee at Dartmouth College (protocol number: 00002158). Animal euthanasia was conducted as described in the Tissue collection section of the methods. All animals were housed in a temperature and humidity-controlled vivarium in a 12 h light/dark cycle with ad libitum access to food and water.

Surgical procedures
Cranial window surgeries were performed over the somatosensory cortex as previously described38,84,85. Briefly, animals were anesthetized with an i.p. injection of ketamine (100 mg/kg) and xylazine (10 mg/kg) solution (K/X). Carprofen analgesic (50 mg/kg) was administered subcutaneously before, after, 24 h after, and 48 h after the surgery. A custom-made head plate was glued to the exposed skull, and then a craniotomy was performed to remove a circular portion of the skull (3×3 mm). For 2Phatal experiments, Hoechst 33342 nuclear dye (1:175) was directly applied to the exposed brain. The brain was sealed with a no. 0 cover glass allowing for intravital imaging. Experiments were performed 3–5 weeks post-surgery to allow the surgery to heal and for inflammation to subside. However, Hoechst 33342 optimally labels nuclei 24 h after topical application to the brain; therefore, we performed the 2Phatal experiments 24 h after the cranial window surgery.

Intravital imaging
While the mouse was still anesthetized from the cranial window surgery, high resolution images were acquired on an upright confocal microscope (Leica SP8) with a 20X water immersion objective (Leica NA 1.0). The purpose of imaging immediately after the surgery is to image the brain when the cranial window is the clearest to get the best quality high resolution images which is needed for 3D reconstructions. All other imaging was performed on an upright laser-scanning 2-photon microscope (Bruker Ultima) with a 20X water immersive objective (Zeiss NA 1.0). The cytoplasmic tdTomato was excited by 552 nm and 1040 nm laser wavelength on the confocal and 2-photon, respectively. The mitochondrial Dendra2 was excited by a 488 nm and 920 nm laser wavelength on the respective microscopes. The mitochondrial mKate2, microtubule (MT) eGFP, and the Hoechst 33342 nuclear dye were excited by 1175 nm, 920 nm, and 775 nm wavelengths on the 2-photon microscope, respectively. All Z-stacks were taken over a depth of 50-60 μm with a 1.5 μm step size between stacks. The imaging depth spanned layers 1 and 2 of the somatosensory cortex. All time-series were acquired by taking a Z-stack image every 1 min for a total of 30, 45, or 60 min. For anesthetized imaging sessions isoflurane anesthesia mixed with room oxygen was delivered to the animal via the SomnoSuite, Low-Flow Anesthesia System. Initially, 3.5% isoflurane was used to induce anesthesia, then anesthesia was maintained at 1.5% isoflurane while imaging. Awake imaging experiments were performed by head fixing the mouse by the head plate in the Neurotar’s Mobile HomeCage that allows the mouse to move ad libitum on an air table.

Three-dimensional segmentation and rendering from optical images
High resolution confocal images were used to segment microglial cytoplasm and their mitochondria. The image size was 2048×2048 pixels (pixel size 180×180 nm), and 1–3 positions were acquired per animal. A total of 14 microglia from 9 mice (n=4 female and 2 male mice) were segmented. The parameter to choose the microglia to segment was that all cell compartments had to be within the Z-depth imaged. Aside from that, the cells to segment were randomly selected (1–3 cells per animal).

The Volume Annotation and Segmentation Tool (VAST Lite, version 1.4.1)86 was used to segment the cytoplasmic (tdTomato) and mitochondrial (Dendra2) signal in 3D. Images were preprocessed in FIJI87: the tdTomato and Dendra2 channels were split, smoothed, the lookup table (LUT) changed to Grays, and converted from an 8-bit to RGB Color. The images were then imported to VAST to complete the segmentations. For each cell, first the cytoplasm was segmented to define the soma, processes, and primary process compartments. Then the mitochondrial networks were segmented and designated to the respective compartment they resided in. Lastly, with VAST we exported the following from the completed segmentations: (1) the cytoplasmic and mitochondrial volumes and (2) uncompressed TIFF images at mip level 0 (indicate the voxel resolution in X, Y, Z: 180 nm, 180 nm, 1500 nm). Both were later used in mitochondrial morphometric quantifications done in FIJI or Excel. The raw values for mitochondrial volume from the optical images were likely overestimated due to limits in axial resolution with optical fluorescence microscopy in addition to the inability to always resolve and separate single mitochondria from mitochondrial networks as mentioned in the discussion. Therefore, direct comparisons of mitochondrial volume between the optical and EM datasets cannot be made. This does not impact other comparisons as ratio-metric or within cell comparisons are accurate.

To 3D render the microglial cytoplasm and mitochondria, MATLAB (version 24.1.0)88 and VAST were used to export OBJ files of the cytoplasmic and mitochondrial segments at mip level 0. The OBJ files were used in 3D Slicer89–92 to create the 3D renderings (see examples in Fig. 1e and Supplementary Fig. 1c).

Human electron microscopy dataset analysis
To investigate mitochondria in microglia across species, we used a publicly available human electron microscopy (EM) dataset (H01) available online at http://h01-release.storage.googleapis.com/landing.html42. This dataset provides a complete cellular and vascular reconstruction of 1 cubic millimeter of the temporal cortex, the largest reconstruction of the human brain to date42. The brain tissue was donated from a 45-year-old female who underwent an epilepsy-related resection surgery42. To access and resect the epileptic focus, a section of the brain tissue above it was removed- a portion of which constitutes the H01 dataset42.

The tissue was prepared as described42, sectioned at ~30 nm thickness, and imaged using multibeam scanning electron microscopy with a resolution of 4×4 nm2. This group automated segmentation of cells and vasculature, which can be viewed in Neuroglancer42. We distinguished microglia from OPCs by their nuclear ultrastructure and cell cytoplasmic morphology43. Using Neuroglancer, we chose 6 microglia from cortical layer 5 to further segment their mitochondria. We used VAST86 to open the H01 dataset, import the coordinates of our cells of interest taken from Neuroglancer, and fill the microglia cytoplasm that had already been automatically segmented42. We further segmented other microglial compartments, including the soma, processes, primary processes, nucleus, and mitochondria. Mitochondria were designated to their respective compartment. Similar to the fluorescent segments, we used VAST to export the following from the specific bounding area of the EM segmentations: (1) the cytoplasmic, nuclear, and mitochondrial volumes and (2) uncompressed TIFF images at mip level 4 (X, Y, Z: 128 nm, 128 nm, 132 nm). A higher mip level lowered the resolution such that images could be exported in a timely manner. These exports were later used for mitochondrial morphometric quantifications done in FIJI or Excel.

To determine microglia process tip proximity to vasculature, vasculature and microglia segmentations were opened in Neuroglancer. For each microglia primary process, 2 tips were selected, and coordinates were recorded. At each tip, the nearest blood vessel was identified using 2D visualization of EM data simultaneously in the xy, xz, and yz planes, and the coordinates were recorded. The recorded coordinates were used to calculate the distance between each microglia tip and the nearest blood vessel. To determine the mitochondrial volume fraction at each tip, segmentations made in VAST of microglia process cytoplasm and mitochondria were exported as a tiff for a 20 μm × 20 μm × 20 μm region centered at each microglia tip. In FIJI, microglial cytoplasm and mitochondria area were calculated from maximum projections.

To determine microglial process tip proximity to neighboring neurons, the nearest neighboring neuron soma was identified using 2D visualization of EM data simultaneously in the xy, xz, and yz planes in Neuroglancer. Some microglia somas (4/6) directly contacted neurons. For each identified neuron, coordinates were recorded in the center of the neuron soma. For each microglia, coordinates were recorded in the center of the soma and at process tips as described above. Coordinates were used to calculate distances between neuron somas and microglia somas or tips. Microglia mitochondria volume fractions were determined as described above. Visualizations of other cells contacting microglia were made in Neuroglancer.

Mitochondrial morphometric analysis
Morphometrics in this study encompass mitochondrial content, shape, and subcellular distribution. Starting with content, all volume exports from the 3D segmentations were used to determine the mitochondrial to cytoplasmic volume fraction (%) and the total or average mitochondrial volume (μm3) in the whole microglia and/or by microglial compartment (soma and processes). Additionally, mitochondrial network number and the number of individual mitochondria were manually counted while segmenting the optical (mouse) and EM (human) datasets, respectively. For the optical dataset, if a mitochondrial network spanned more than one compartment, its’ volume was split to represent the compartment it resided in, but it was counted as one network. For the EM dataset, if a mitochondrion spanned more than one compartment, it was assigned to the one it most occupied.

From the optical segmentations, mitochondrial shape was determined by circularity and aspect ratio: two different calculations to determine how circular or elongated an object is. A value equal to 1.0, from both circularity (4π(area/perimeter²)) and aspect ratio (width/length), represents an object that is a perfect circle. Therefore, as the value moves further from 1.0, the object becomes more elongated. To quantify the mitochondrial shape, mitochondrial segments from each microglia were opened in FIJI, a maximum intensity projection was made, default threshold applied, then the “Analyze Particles” command was used to automatically calculate circularity and aspect ratio from the shape descriptors. Circularity and aspect ratio consider different features of the object. Using both methods ensures a thorough analysis, as one calculation might not detect a shape difference, while the other does.

Multiple analyses were used to dissect the subcellular distribution of mitochondria in microglia. First, a Sholl analysis was done on the cytoplasmic and mitochondrial segments (from optical and EM datasets) separately. Sholl is used on cells with a branched morphology to determine the complexity of the branching. It does this by counting the number of intersections that branches make on evenly spaced concentric circles that radiated out from the cell center. With Sholl, we wanted to determine how mitochondria radiate from the cell center relative to the microglial branching complexity. To perform Sholl, maximum intensity projections were made from the cytoplasmic and mitochondrial segments in FIJI, a default threshold was applied, a straight line was drawn from the cell center to the edge of the image, and the “Neuroanatomy” plugin was used to execute Sholl. Sholl parameters for the optical dataset were set to 1 μm for the starting radius and step size with a 70 μm ending radius. Given the increased spatial resolution of the EM dataset, we used the following Sholl parameters: 0.5 μm for the starting radius and step size with an 80 μm ending radius. Results were graphed as number of intersections against the distance from the cell center. Of note, to exclude contributions from the soma, radii 1–8 μm were excluded from the Sholl graphs (Figs. 1 and 2) since the average soma radius of microglia is around 8 μm in the optical and EM datasets.

The second set of analyses determined the subcellular distribution of mitochondria along the length of individual primary processes in 10% bins. To measure the primary process lengths, the optical 3D segments (from the cell soma and the primary process cytoplasm and mitochondria) were first maximum intensity projected and merged into one image in FIJI. In the merged image, only the cytoplasm and soma channels were made visible. The mitochondrial channel was off to ensure the researcher was blind to the mitochondrial location along the primary branch length. Next, a 5-pixel segmented line tool was used to trace the longest branch in the primary process from soma end to tip end, such that the shortest possible path was traced. Then, the “Plot Profile” command was executed in reference to the mitochondrial channel, which provided the primary process length (μm) and information (from gray value) on where mitochondria specifically reside along that length. To interpret this information, the length of all the primary processes was normalized to each other by considering the length as 0–100% (soma=0% and tip of process=100%) and quantifying the mitochondrial occupancy in 10% bins along the length of the primary process. This method was a more thorough and used to confirm findings from the Sholl analysis.

The third set of analyses further described mitochondrial subcellular distribution in primary processes by scatter plotting the mitochondrial volume in each primary process (μm3) by the primary process length (μm) with both the optical and EM datasets. The primary process lengths of the human EM microglia were measured with plot profile as described above. Primary process length, not cytoplasmic volume, was used in these analyses to distinguish long processes from short processes. Cytoplasmic volume was misleading because some short processes had greater volume than longer and thinner processes.

Lastly, Excel was used to perform a k-means cluster (k=2) using the mitochondrial volume per primary process. This unbiased clustering approach defined two groups that contained either high mitochondrial volume (>67.1 μm3) or low mitochondrial volume (<67.1 μm3). Within those 2 groups we determined the circularity and aspect ratio of the individual mitochondrial networks in each primary process (excluding the primary processes lacking mitochondria). The goal of this analysis was to determine if mitochondrial shape in a microglia process differs depending on the volume of mitochondria occupying that process. We used the optical mouse dataset for this analysis given the abundance of primary processes analyzed.

Microtubule (MT) and mitochondrial distribution
The Cx3cr1-creER: Ai9: Kaleidoscope mouse model was used to determine MT and mitochondrial distribution in microglia. Images acquired from the 2-photon microscope were 1024×1024 pixels (pixel size 213×213 nm), and 2 positions were acquired per animal (n=2 female and 3 male mice). In FIJI, the images were smoothed then 3–4 microglia/animal were selected for analysis and cropped with a 75×75 μm ROI. A 13.5 μm maximum intensity projection was made for each cell with the soma in the center of each Z depth projected. From the cropped microglia each channel was automatically thresholded: cytoplasm/tdTom was default thresholded, and the MT/eGFP and mitochondrial/mKate2 channels were Max Entropy thresholded. Then, the area fraction of each thresholded channel was acquired to calculate the MT:cytoplasm and mitochondria:cytoplasm area fractions within each microglia (n=19 microglia from 5 mice, 2 female and 3 male).

Next, 12 of the microglia selected above were used to analyze the presence of MTs relative to mitochondrial presence. In each cell, 2 processes with and 2 processes without mitochondria were selected with the researcher blind to the MT channel. Then, 5×5 μm ROIs were overlayed on the processes selected, and the MT channel was turned on to quantify the percentage of processes containing MTs.

Mitochondrial presence during microglial surveillance
To determine mitochondrial presence during microglial surveillance, animals were imaged under isoflurane anesthesia 3–5 weeks after the cranial window surgery (see Surgical Procedures and Intravital Imaging). A 30 min time-series was captured from 4 mice (n=2 female and 2 male mice). In FIJI, the time-series was 3D Drift Corrected based on the tdTomato channel, then 25 microglia were selected also using the tdTomato channel. Each microglial cell was cropped, smoothed, and then maximum intensity projected from the 5 slices above and 5 slices below the center of the microglial soma. Then, branches (3–6 per cell) and process tips (3–6 per cell) were selected (using the tdTomato channel) from each microglia and the following analyses were performed.

We defined the branches as “stable”, present at 0 min and 30 min, or “lost”, branch was present at 0 min but gone at 30 min. Stable branches were considered less motile than the lost branches. With this we determined the percentage of branches that were stable or lost. To confirm that the branches selected had no difference in mitochondrial occupancy at time point 0 min, we determined the percentage of branches that contained and did not contain mitochondria. Then, we determined the percentage of branches containing mitochondria in the stable branches vs. the lost branches. Given that much motility occurs at the tips of the processes we overlayed a 5×5 μm2 region of interest (ROI) around the tip’s center and determined the percentage of tips that contained or did not contain mitochondria.

Next, we quantified the area covered by the cytoplasmic and mitochondrial signal across the 30 min time-series by temporally projecting all the 30 images together (designated as 0→30 min). We visualized process and mitochondrial motility from manual tracks made in the FIJI’s TrackMate plugin. An increase in area fraction indicates motility, therefore, we aimed to quantify the motility by these methods to compare microglial process and mitochondrial motility during surveillance. Each cropped cell was further processed in FIJI: the cytoplasmic and mitochondrial channels were split, bleach corrected, “Li” thresholded to make a binary image with minimal background signal, and finally temporally projected. From this, area fraction from the cytoplasmic and mitochondrial channels was determined from the 0 min image and the temporal projection 0→30 min. We determined the percent of mitochondrial to cytoplasmic area fraction, and the percent change in area fraction for each signal separately.

Next, we quantified the instantaneous velocity for the tips of the processes that were defined in the ROIs described above. Each process tip was manually tracked using the “Manual Tracking” plugin in FIJI while blinded to the Dendra2/mitochondrial channel. The process tips were tracked for the whole duration of the 30 min time-series or, in case of retraction, until they merged into the soma or parent process. The processes with mitochondria were later qualitatively classified as stable, extending, or retracting.

Awake to isoflurane anesthetized imaging and analysis
Awake to anesthetized imaging was performed 3–5 weeks after the cranial window surgery (see Surgical Procedures and Intravital Imaging). First, the animal was acclimated to the Neurotar Mobile HomeCage for 30 min, then a 30 min time-series was captured. Next, the same animal was removed from the awake imaging set-up and anesthetized. We allowed the mouse to acclimatize to the anesthesia for 30 min before locating the same position that was imaged during wakefulness. Then, a 30 min time-series was captured. Therefore, two 30 min time-series were acquired from the same animal in the same position: first during wakefulness and then during anesthesia allowing us to compare the same microglia and their mitochondria under different arousal states (n=6 mice, 3 female and 3 male).

For analyzing the mitochondria and processes’ dynamics in awake and isoflurane anesthetized conditions, first, the Z-stacks were registered to correct for the Z-drift with reference to the cytoplasmic channel. The cells to be analyzed were randomly selected with reference only to the first time point and the analyzer was blinded to the experimental condition. The cells were cropped, smoothed, and used to create maximum intensity Z-projections which were later thresholded similarly for the mitochondria and cytoplasmic channel. To measure the processes’ dynamics, Z-projections of the first and last time points as well as of all the time points along the 30 min time-series were created for the cytoplasmic channel. Area fraction in the cropped region was measured for the first time point as well as for the temporal projections and the change in area fraction between the two was calculated.

Mitochondria motility analysis was done only for the mitochondria in the processes of the selected cells, and mitochondria present in the soma or other cells in the environment were cleared out. The thresholded images were then run in TrackMate93 with the following settings: the LoG detector was selected, and the estimated object diameter was set at 3, quality threshold at 1, and sub-pixel localization was checked; the simple LAP tracker was selected, and the linking and gap-closing max distance was set at 3 microns, and gap-closing max frame gap at 2. The tracks with less than 5 spots were excluded and displacement was collected for each of the automatically tracked mitochondrial networks. To correct for any remaining drift caused by imaging and sample motion artifacts, first, the mitochondrial track that traveled the smallest distance along the 30 min time-series was identified. It was assumed that any displacement collected from this track was due to drift and therefore all the other displacement values were corrected accordingly based on this track. All the above steps were kept consistent for both awake and isoflurane conditions. Lastly, all the mitochondria displacement values of all the tracks analyzed in both condition were combined to calculate the mean and standard deviation. Their sum (rounded up to 3 microns) was determined to be the displacement threshold above which the mitochondria tracks were considered motile.

Laser lesion imaging and analysis
The laser lesion experiment was performed in awake animals using the Neurotar Mobile HomeCage 3–5 weeks after the cranial window surgery (see Surgical Procedures and Intravital Imaging). The laser power was increased to ~75 mW for the lesion. The high laser power used for the lesion causes cell rupture and spillage of ATP into the parenchyma3. ATP then triggers a chemotactic response from microglia via the transmembrane purinergic P2Y12 receptor94. This method of applying focal tissue damage serves as a model of acute inflammatory response by microglia. Before the lesion was induced a 30 min time-series was acquired to capture baseline surveillance. In the same position, a laser lesion was induced in an 8×8-pixel ROI in an area with little to no fluorescent signal, then immediately after the lesion a 45 min time-series was captured. This allowed us to observe the microglial transition from baseline surveillance to rapid chemotactic response to the lesion and assess the mitochondrial positioning and motility throughout this process. Additionally, the same position was imaged at 1 and 6 h after the lesion to observe the progression of mitochondrial dynamics as microglia work to clear the debris. The same position was identified at each time point using the vascular morphology and cellular patterning. One to two laser lesions were induced in each animal (n=6 mice, 3 female and 3 male).

To determine when microglial processes and mitochondria arrive to the laser lesion, the change in fluorescence over time was quantified in the region surrounding the lesioned area. To do this the 30 min and 45 min time-series were preprocessed as follows: a maximum intensity projection was made, the tdTomato and Dendra2 channels were each bleach corrected, then the projection was corrected for 3D drift, referring to the Dendra2 channel, the tdTomato and Dendra2 channels were split, then the lesion location was identified. Next, the “Li” threshold was applied to the projections to create a binary image stack of each channel and remove background signal. Then, a 50×50-pixel ROI was centered around lesion site ROI (Fig. 9b), and the “TimeSeries Analyzer V3” FIJI plugin was used to quantify the average fluorescent intensity around in the donut ROI over time. The average fluorescent intensities across the 30 min times-series were averaged for each position and channel (tdTomato and Dendra2) imaged. This average served as the baseline fluorescence for the position, and it was used to calculate the change in fluorescent intensity minute by minute for the 30 min before and 45 min after the lesion was induced. The change in fluorescent intensity was also quantified from a single 6 h time point to determine the possible progression of mitochondrial arrival to the lesion site.

2Phatal imaging and analysis
Targeted two-photon chemical apoptotic ablation (2Phatal) experiments were performed in awake animals using the Neurotar Mobile HomeCage 24 h after the cranial window surgery (see Surgical Procedures and Intravital Imaging). 2Phatal enabled us to trigger apoptotic death of single neurons5 in layer 2 of the somatosensory cortex. We observed the microglia mitochondrial response to this non-inflammatory injury7–9 as a single microglia recognized the apoptotic neuron and initiated phagocytosis of the neuronal corpse5,6. Neuronal nuclei were identified by their granular morphology and large size5. 2Phatal was induced as previously described5,84. Briefly, an 8×8-pixel ROI was placed over the Hoechst 33342 labeled neuronal nucleus, the dwell time was increased to 100 μs, the laser intensity was increased, and then the nuclear dye was laser ablated for 3.2 s. This damages the DNA and triggers apoptosis5. One position per animal was captured and within each position, 1–8 neuronal nuclei were targeted (n=6 mice, 4 female and 2 male). Images were taken before, 3 h, 6 h, and 24 h after 2Phatal. The same position was identified at each time point using the vascular morphology and nuclear patterning. This is a valuable non-inflammatory cell death method that enables visualization of how the mitochondrial dynamics interplay with the microglial process dynamics when clearing a single neuron.

First, we qualitatively assessed the nuclear condensation, microglial engagement, and mitochondrial presence at each time point imaged (before, 3 h, 6 h, and 24 h). Nuclear condensation was defined as either normal, partially condensed, fully condensed, or absent. Microglial engagement was defined as no engagement, partial process cup, process engulfment, or soma engulfment. Mitochondrial presence was defined as absent, <50% present, or >50% present. These scorings of engagements were individually graphed to show the percentage of total cells presenting the specific nuclear, cytoplasmic, and mitochondrial phenotypes before and after 2Phatal.

For a quantitative assessment of the microglial cytoplasmic and mitochondrial response to clearing an apoptotic neuron, we determined the average fluorescent intensity at each time point (before, 3 h, 6 h, and 24 h) imaged post-2Phatal. To perform this analysis in FIJI, a 20×20 μm2 circular ROI was centered the 2Phatal targeted nuclei to produce a cropped image for each nucleus at each time point. From the cropped images, the channels (tdTomato and Dendra2) were split, and a default threshold was applied to each image. Then, a 20×20 μm2 circular ROI was overlayed on each image and the mean gray value was effectively quantified around the immediate vicinity of the target nucleus across all time points and in both the cytoplasmic and mitochondrial channels.

Tissue collection, immunohistochemistry, and analysis
At P125-158 and 5–6 weeks after the cranial window surgery, mice were anesthetized with K/X and transcardially perfused with 4% paraformaldehyde solution diluted in 1X PBS. Brains were fixed for 24 h in 4% paraformaldehyde and then moved to 1X PBS for long term storage. Brains were sectioned at 75 μm thickness with a vibratome and cryopreserved at −20 °C.

For immunohistochemistry, the following materials were used: primary antibodies included rabbit anti-TOMM20 (1:200, Abcam, #ab78547), rabbit anti-hexokinase 2 (1:100, Abcam, #ab209847), and rabbit anti-hexokinase 3 (1:100, Proteintech, #13333-1-AP); the secondary antibody was donkey anti-rabbit 647 (1:500, Jackson ImmunoResearch Laboratories Inc., #711-605-152); Hoechst 33342 nuclear dye diluted in 0.3% Triton X-100 in 1X PBS (1:2000, Thermo Fisher Scientific, #H3570); and Prolong Diamond Mountant (P36970). Primary and secondary antibodies were diluted in 0.3% Triton X-100 and 1% Bovine Albumin Serum in 1X PBS. For the immunostain procedure, free floating brain sections were first incubated in primary antibody solution overnight, then incubated in the secondary antibody solution for 2 h, and lastly the nuclear dye solution was applied for 30 minutes. Before and after each step of the procedure, the slices were washed with 1X PBS, and throughout the procedure incubations and washes occurred on a shaker at RT. The sections were mounted and stored at 4 degrees Celsius until imaged on a confocal microscope with a 63X oil immersion objective (Leica NA 1.4). Each section was imaged in the somatosensory cortex, spanning layers 1–2, region. All fixed tissue analysis was performed in FIJI.

TOMM20 staining was performed to determine the recombination efficiency of Dendra2. Four microglia per animal were analyzed (n=4 mice, 2 female and 2 male). Five TOMM20 labeled spots within the cell cytoplasm were randomly selected per cell while being blinded to the Dendra2 channel (total of 80 spots). Each of the spots was later qualitatively assessed to determine the overlap rate of the two mitochondrial labels, Dendra2 and TOMM20.

For analysis of hexokinase distribution the following was done for HK2 and HK3 immunostains. Three microglia from each animal were analyzed (n=8 mice, 5 female and 3 male). For each microglia analyzed, 2 processes with high and 2 processes with low mitochondrial occupancy were selected with only the cytoplasmic (tdTomato) and mitochondrial (Dendra2) channels; the researcher was blind to the hexokinase 2 and 3 channels. For each process, a maximum intensity projection of two Z slices was “default” thresholded for the cytoplasmic channel, and “moments” thresholded for the mitochondrial and hexokinase channels. Then, an 8.50×5.50 pixel ROI was used to crop the selected process (while blind to the hexokinase channels). Next, the “Analyze Particles” command was used to automatically generate ROIs of the cytoplasm and mitochondria within the cropped ROI. Lastly, the area fraction of hexokinase signal within the cytoplasmic and mitochondrial ROIs was acquired.

Statistical analysis
All statistical analyses were performed using GraphPad Prism (version 10.3.0) or Excel. No statistical methods were used to predetermine the sample size, and all data was assumed to have a normal distribution. For t-tests, variance was tested and if significant then Welch’s correction was applied and noted in the figure legend. Sample sizes were based on those reported in previous publications. Statistical tests, cell numbers, and animal numbers are indicated in the figure legends for each experiment. The parameters to select the cells analyzed in this study were based on the quality of the images and that all cell compartments were within the imaged Z depth. The cells for the motility analyses were randomly selected with reference to the first time point of the time-series, and the data was blinded for awake and isoflurane anesthetized conditions. The cells analyzed from the EM dataset were selected based on the microglial identification criteria. Throughout the study, the analyzer only referred to the cytoplasmic channel, and not the mitochondrial channel, when defining ROIs to prevent bias to the regions selected. For applicable datasets, data was analyzed by animal and sex differences were determined which are detailed in Supplementary Figs. 3–6. No animals were excluded from the statistical analysis.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this research paper, the authors used a novel, triple transgenic mouse line enabling dual fluorophore expression in the cell cytoplasm (Ai9) and mitochondrial matrix (Dendra2) driven by tamoxifen inducible cre recombination in Cx3CR1-positive cells. Using in vivo imaging and histology, they show an uneven distribution of microglial mitochondria on the proximo-distal axis of microglial processes, which is also confirmed in human samples. They show that mitochondria are heterogeneously distributed among microglial processes, and processes lacking mitochondria are more motile. Furthermore, mitochondrial motility is not altered by anaesthesia, and early microglial processes responding to laser lesion also lack mitochondria. In line with this, mitochondria are recruited to microglial processes engulfing dying neurons in a delayed manner.\n\nThe scope of the paper is interesting and timely. The experimental models used are largely appropriate. While the observations made are likely to be important for the field, the paper remains descriptive and little insight is provided on the mechanisms that regulate the distribution of microglial mitochondria and their role in cellular responses and function.\n\nSpecific points:\n- Immunofluorescent validation of transgenic mice to determine the specificity of mitochondrial labelling and to quantify its effectiveness to visualize all mitochondria would support the interpretation of the data presented.\n- The authors report that the image stacks used for morphometry were taken immediately after cranial window surgery. Could the acute side-effects of the surgery influence mitochondrial placement within microglia? On the fixed human samples mitochondrial distribution seems to be more homogeneous than in the mouse samples. Could this be a biological difference between mouse and human microglia, or rather a technical one, rooting in the different processing / imaging methods?\n- The authors show that mitochondria are heterogeneously partitioned throughout microglial processes. While this is an interesting observation, it would better characterize the distribution of mitochondria if Sholl-analysis on 3D renderings of individual cells was performed in 3D, instead of Sholl analysis on 2D projection images. Applying 3-dimensional analysis would reveal a more detailed picture on the distribution.\n- The authors show that microglial branches and processes lacking mitochondria are more motile. This is an interesting observation, but the measurements to support this could be more direct. Stating that microglial processes are more motile under anesthesia solely based on larger microglial coverage of summation images may not be sufficient. Could the authors assess the velocity of individual microglial processes and correlate this with the number and other morphological parameters of mitochondria?\n- It is also unclear, to what extent the distribution of microglial mitochondria are representative for given microglial proceses over time. Do the authors have repeated imaging data from individual microglia over several days to elaborate on this issue?\n- One major limitation of this study is that the otherwise very interesting observations remain very descriptive concerning the mechanisms that regulate mitochondrial numbers in given microglial processes, and the role of mitochondria in shaping the movement and responses of individual microglial processes also remains unclear. At least, it would be interesting to see whether the more motile, mitochondria-free microglial processes would have higher levels of proteins necessary for enhanced glycolytic energy production (HK2, GLUT1) than those more stationary and with mitochondria. It would also be important to see to what extent microglia-specific mitochondrial interventions (targeted uncoupling for example) would interfere with the reactive properties of the mitochondria-free, motile processes. The results of these experiments would greatly enhance our understanding of microglial metabolic properties.", "reviewer_2": "In this work, Pietramale and colleagues develop a method for long-term fluorescent in vivo imaging of brain macrophages (including microglia) and their constituent mitochondria in mice. They use this method to track mitochondrial migration in processes extending from putative microglia in the steady state, under anesthesia, and in response to damage from laser burns and during efferocytosis of apoptotic cells. These results generate a rare and valuable characterization of mitochondrial migration in brain macrophages in vivo during multiple biologically relevant processes. Furthermore, the authors use these data to suggest that mitochondria are largely absent from nascent processes in these cells. However, the overall conclusions are not well supported by the data and are at times oversold. The biological importance of these findings is also unclear without significant follow-up with complementary methods. Rather, it appears that mitochondria are indeed transported to extending processes, but lag behind the distal end of these processes. Without direct comparison to other cell types using the same system, the claim that this is unique among cells in the CNS cannot be made. The relevance of this mitochondrial transport lag is also not explored and may be further established through the observation of metabolic activity with subcellular resolution to determine of mitochondria-free processes make use of alternative metabolic processes to support their energetic demands.\n\nThe major concern is that there is no attempt to do a causal experiment. For example, I would use Miro1 knockout mice specifically in microglia o test some their hypothesis. Miro1 floxed mice are available (RRID:IMSR_JAX:031126). In the absence of a causal experiment, I cannot support publication.\n\n• Major comments\no Care should be taken throughout the manuscript to highlight the descriptive nature of these findings and to avoid over-interpretation, particularly within results sections. For instance, the suggestion in line 168 that processes lacking mitochondria are more highly motile ignores many possible alternative interpretations, e.g. that synapses lacking mitochondria are eliminated at a higher rate.\no Based on Figure 7, the claim that mitochondria are absent from microglial processes performing (at least) phagocytic engulfment appears to be incorrect. Rather, it seems that mitochondria simply lag behind the process as it extends. This makes sense, given that cytoskeletal elements in theory must precede mitochondrial transport. While it is interesting to consider the metabolic consequences in the interim, it is unclear what the relevance of this finding ultimately is to efferocytosis or process extension, as a whole. This is more correctly addressed in the discussion.\no The use of in vivo imaging in this study is very impressive, but many of these findings would be further substantiated by long-term time-lapse imaging of ex vivo microglia or BV2 cells. Specifically, the temporal dynamics of mitochondria: is there a period of complete mitochondrial exclusion in nascent processes, or is the delay simply a result of transport of mitochondria into the processes? Furthermore, is there local reliance on glycolysis in the mitochondria-free processes? Advanced sensors such as those in (PMID: 35881794) or high-resolution mass spectrometry with nanoSIMS could theoretically offer the high spatial and temporal resolution necessary to answer this question.\no Claims that an uneven distribution of mitochondria is unique to microglia in the brain (lines 319-322) compares cells undergoing active process extension to those in the steady state. Based on the data presented herein, it is entirely possible that mitochondria would lag behind neurites during synapse formation or cell migration. This claim should either be addressed in neurons and astrocytes using the same methods in relevant drivers or removed entirely. The alternative explanation of actin vs microtubule utilization (lines 341-343) alternatively should be investigated directly, perhaps ex vivo or in vitro. Furthermore, the mention of prior studies to suggest that microglia are unique in this regard is problematic for the following reasons:\n  Han et al., Neuron (2016), reference 48: 24hr timepoint, when mitochondria in this model have fully migrated into the extending process. Performed in C. elegans, where temporal dynamics are not directly comparable.\n  Cunniff et al., Mol. Biol. of the Cell (2016), reference 49: speaks directly to mitochondrial dynamics in a migrating cell with high temporal resolution. However, this study is performed in a cancer cell line in vitro, with limited relevance to cells in the intact CNS.\n  Desai et al., Biophysical Journal (2013), reference 50: ibid.\n  Crosis-Molist et al., Nat. Comm. (2023), reference 51: ibid.\n  Schneyer et al., Sci. Rep. (2017), reference 52: ibid.\no Studies of this type frequently suffer from pseudoreplication and a very low biological n. The authors have admirably used a reasonable number of mice in these investigations and have reported both biological and total n, as should be the standard.\no The authors should acknowledge that the Cx3cr1-CreER driver also targets border-associated macrophages which are not easily visually distinguished from microglia.\n• Minor comments\no Awkward sentence at line 28: “Here, we performed intravital imaging of microglia mitochondria, revealing that microglial processes diverge, with some containing multiple mitochondria while others are completely void.”\no The statement “Microglia are the most dynamic cell in the central nervous system” (line 38) is unnecessarily contentious. Microglia are highly plastic cells, but so are many other cell types.\no The more specific term, “efferocytosis”, should be used in line 44.\no Metabolic shifts in microglia during inflammation, such as increased glycolysis or iron retention, are arguably part of normal macrophage function and should not be characterized purely as “metabolic dysfunction” (lines 55-56).\no The introduction makes no substantial mention of the prior knowledge on the role of mitochondria in microglial process extension. While it appears that data identifying a potential link is lacking, this would be quite valuable for placing the findings in context. At present, the motivation behind examining mitochondrial density in microglial processes is largely unclear. Could this, for instance, potentially explain the increased utilization of glycolysis in activated microglia?", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "The manuscript presents valuable findings about the location of mitochondria in microglia and will, therefore, have potential implications for the microglia community. The results align with previous in vivo microglia data analysis using the same mouse model strategy (Maes et al. 2023, cited by the authors) applied in live in vivo imaging settings in the somatosensory cortex. The experimental data shown is solid. The study remains descriptive primarily and does not provide insights into the lack of mitochondria in the dynamic microglial processes and their delayed arrival at lesion/cup formation sites. This aspect needs to be included to extend the study of being incremental.\n\nIntroduction:\nThe introduction provides a short overview of microglia, following the partially outdated concept of activated and non-activated microglia. Microglia are not the only ones monitoring tissue damage or infection for rapid detection (L25), and the introduction repeats this mistake. It has become well-accepted that microglia are sensitive to environmental changes beyond pathogens and injury and are also involved in modulating various aspects of the CNS (see Neuroglia, 3rd or 4th edition).\nFurther, the introduction introduces the current knowledge gaps about incomplete intracellular cellular architecture (L46). The relevance of studying this aspect and justifying the focus on mitochondria in microglia needs further explanations. Other organelles, such as lysosomes involved in phagocytosis, would be more intuitive targets than mitochondria. Why is it important to know when and where mitochondria are located within a process? Would this provide insights into chemotaxis, phagocytic cup formation, and lysosomal support for protein degradation at process tips, to name a few? For example, mitochondrial localization along neuronal dendrites is positioned to support presynaptic vesicle endo/exocytosis and Ca2+ buffering, among many others.\nIf the study intends to describe the metabolic state of the microglia based on the mitochondria network distribution related to fission and fusion (L53), then the currently presented data would be insufficient. There is a connection between the change of mitochondria shape through fission and fusion and the cell's metabolic state. Yet, this analysis has been primarily established in the cell culture model, raising the question of applicability in vivo. If this study extends its analysis to develop this aspect, this manuscript would be fundamental and of broad interest.\nThe introduction requires more background to give a comprehensive perspective on the study's goal and the expected readout. The introduction also mentions aging and neurodegeneration (L54) as causes of mitochondrial dysregulation, yet this study does not address either of these aspects and focuses on homeostasis as the baseline.\n\nResults:\nFigure 1:\ni) The justification for performing the high-resolution optical images immediately after (24h) performing the cranial window surgery to have an optimal expression of the Hoechst dye (L81) is only described in the method section (L411). These come with several limitations: first, microglia are still reactive due to the surgical procedure, and second, the brain tissue is under painkillers. Painkillers like carprofen (L406) target the prostaglandin G/H synthase 1/2 pathway (https://go.drugbank.com/drugs/DB00821), which will directly and indirectly affect microglia. The lack (or delay due to drug wear off) of mitochondrial movement under the 2Phatal experiment might be associated with this experimental limitation and should be controlled for.\nii) L92: The description of the result needs to be clarified, and the results compared to typical profiles from other studies that have traced microglia (e.g., the deposit https://neuromorpho.org/ has several microglial skeletons). This will support a general conclusion.\niii) Fig. 1e: The authors should show each primary branch of microglia individually as a first indication of whether specific branch properties, such as the branching complexity, relate to the abundance of mitochondria, especially since this will become a topic from L145 and a correlation exists for individual microglia in Fig. 3c.\niv) The analysis in Fig. 1f identified more elongated mitochondria without further insights into the meaning of this phenotype.\nv) Microglia show a sex-specific morphological response, especially during development, aging, and disease (Paolicelli et al. 2022, Colombo et al. 2022). The authors must annotate the data points in all manuscript plots, whether derived from male or female mice.\n\nFigure 2:\ni) The human EM datasets confirm similar distribution in mitochondria across branches as the mice; however, the value-add of this data falls short of its potential. Since the presence/absence of the mitochondria in specific processes is the focus of this manuscript, could the authors probe this available and annotated dataset to (i) compare individual branch features as described in Fig. 1; and (ii) identify when microglial processes are interacting with other cellular structures, i.e. neuronal dendrites, synapses or blood vessels and determine whether these processes contain mitochondria? If, for example, mitochondria are often located at contact sites with blood vessels, the authors’ in vivo imaging setup could interrogate interaction with blood vessels and corresponding mitochondrial location using a dextran dye during imaging in subsequent figures.\nii) Also, since this data is generated in females, a specific comparison to female mice microglia should be investigated.\n\nFigure 3:\nA summary plot is missing showing whether the observed phenotypes described in L154f are common across all the evaluated microglia and whether sex-specific differences exist.\n\nFigure 4/5:\ni) The data shows that dynamic microglia branches lack microglia.\n- This result seems counterintuitive since movement would require ATP. The authors do not provide further explanation for this phenotype.\n- Which explanation can be provided for the differences in the mitochondria distribution?\n- The authors should determine the microglia processes’ speed and compare the results to the values in the literature (https://doi.org/10.7554/eLife.86749.2) to ensure that their data aligns. The same holds for the anesthesia experiments in Figure 5.\nii) The effect of anesthesia on microglia and mitochondrial networks is introduced (L182ff), yet the rationale for investigating these conditions is unclear.\n\nFigure 6/7:\ni) The results show that mitochondria are delayed in relocating to the microglial processes engaged with the lesion/apoptotic cell. These exciting results raise several questions:\n- Are the mitochondria arriving in the engaged process transiting from the soma region, or is mitochondrial biogenesis occurring to generate more mitochondria for distribution to the cellular compartment in need? To address this, it is pertinent first to assess whether the total mitochondrial content within a cell has changed during the imaging.\n- Both laser damage and 2phatal induce apoptosis, thus releasing ATP into the neuronal environment. As one of the classic chemoattractants for microglia, is this involved in the mitochondrial transit? Or is the transit via a different signaling mechanism? Could the authors recapitulate the delay in mitochondrial transit in a culture system using ATP to begin dissecting a mechanism? Alternatively, if the process movement was delayed by adding a P2RY12-antagonist such as Clopidogrel, do the mitochondria transit within the original time frame or faster/slower than the process movement?\n- Changes in microglial metabolism in response to damage are essential to the mitochondria’s function. Although the authors discussed this concept at length (Paragraph L362), they could show whether optimal metabolism or altered metabolism affects the microglial process and mitochondrial transit in their two experimental setups. Do changes in microglial metabolism or available substrates affect the microglial process response or mitochondrial transit to the process? For example, in the HK2- mg specific KO mouse or in a brain slice setup, one could then apply different compounds as illustrated in https://doi.org/10.1038/s41467-020-15267-z\n\nDiscussion:\nThe authors provide a comprehensive and well-written discussion highlighting several of the most recent findings in the subfield of mitochondria in microglia. There is a slight bias towards oligodendrocyte comparison (L327ff). While very thought-provoking, the paragraph discussion of metabolic changes would ideally be in relation to the results presented.\nThe discussion would also benefit from introducing the microglia concept of different states (see Paolicelli et al. 2022) and how the organelle distribution might allow distinguishing different states.\n\nOverstatements:\nThe study suffers from several overstatements, which should be corrected:\ni) L38: Are microglia indeed the most dynamic cells in the CNS?\nii) L74/75: The retina is also part of the brain.\niii) From the medical perspective, the temporal cortex of an epileptic patient, even though not the primary focal point, is also classified as diseased and not as a healthy, non-pathological condition (L461).\n(L247) The authors conclude in Fig 6 that ‘microglia that immediately chemotaxis to the site of acute tissue damage do not have mitochondria…’ It seems the authors mean to conclude that the processes do not have mitochondria.", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We respectfully disagree with the assertion that the study is descriptive and incremental. This is the first investigation and definition of microglial mitochondrial morphometrics and dynamics under multiple physiologically relevant contexts, all in vivo. Our new investigations in the revised manuscript of microtubule organization in microglia and their close association with mitochondrial localization provides additional insight into the cellular mechanisms regulating mitochondrial partitioning in microglia, a significant advance in the field.\nThe revised manuscript from Pietramale and colleagues has addressed the major concerns of this reviewer. The addition of several new figures provides further insight beyond the initial observations in the original manuscript, namely, datasets of mitochondrial localization as it relates to microtubles (Fig. 5) and HK2 (Fig. 6) within microglia. Importantly, these new additions begin to answer the questions of ‘why’ and ‘how’ the mitochondria take on the localization observed in microglia. We recognize the efforts of the authors to probe several compounds to interrogate metabolic changes in relation to mitochondrial localization (Rev Fig. 1-3), and agree that it is out of the scope of the current manuscript.\n\nIntroduction:\nThe introduction provides a short overview of microglia, following the partially outdated concept of activated and non-activated microglia. Microglia are not the only ones monitoring tissue damage or infection for rapid detection (L25), and the introduction repeats this mistake. It has become well-accepted that microglia are sensitive to environmental changes beyond pathogens and injury and are also involved in modulating various aspects of the CNS (see Neuroglia, 3rd or 4th edition).\nWe focused the introduction on features of microglia that were relevant to the study at hand. We understand microglia have multiple functions and that there are many states beyond simply “activated” and “non-activated” microglia. Nowhere in our paper did we use these terms. We are also aware that other cells are involved in responding to tissue damage or infection but the relevance of this to our study is not clear.\nTo clarify in L42 “prove the environment for infection or injury”, this is not the main task of microglia. Recent studies have been pointing towards microglia remodeling amongst others synapses and extracellular matrix. Infection and injuries are not the main event that microglia will respond in a healthy CNS.\nThe authors use the term “radical morphological changes” (L48). If they intend to refer to surveillance vs. amoeboid, this is true. Yet, in the context of surveillance “radically” morphologically changes are rare, as they also see in their data. The authors have the option to remove “radical” or define it in the context of homeostasis.\nFurther, the introduction introduces the current knowledge gaps about incomplete intracellular cellular architecture (L46). The relevance of studying this aspect and justifying the focus on mitochondria in microglia needs further explanations. Other organelles, such as lysosomes involved in phagocytosis, would be more intuitive targets than mitochondria. Why is it important to know when and where mitochondria are located within a process? Would this provide insights into chemotaxis, phagocytic cup formation, and lysosomal support for protein degradation at process tips, to name a few? For example, mitochondrial localization along neuronal dendrites is positioned to support presynaptic vesicle endo/exocytosis and Ca2+ buffering, among many others.\nIndeed, it would be interesting to investigate lysosome partitioning and dynamics in microglia under all the conditions we investigated here. This doesn’t mean that it is not justified to also investigate mitochondrial partitioning. In the second paragraph of the introduction, we introduce the many functions of mitochondria and why it is important to investigate their location, morphology, and motility in all cells, including microglia. Since this has never been done before, we disagree and feel that the justification for these studies is readily apparent in our introduction.\nL63: Phagocytosis typically does not happen in the healthy brain. A sentence restructuring such as “... microglia perform surveillance in the healthy brain and how they respond to injury via phagocytosis...” or similar.\nIf the study intends to describe the metabolic state of the microglia based on the mitochondria network distribution related to fission and fusion (L53), then the currently presented data would be insufficient. There is a connection between the change of mitochondria shape through fission and fusion and the cell's metabolic state. Yet, this analysis has been primarily established in the cell culture model, raising the question of applicability in vivo. If this study extends its analysis to develop this aspect, this manuscript would be fundamental and of broad interest.\nOur study lays the foundation for future studies investigating how changes in metabolic state impact mitochondria in microglia in vivo. Critically we must first define what the baseline is, which we have exhaustively done in our manuscript. We do not claim that we have defined the metabolic state in microglia, but it is useful to mention this idea to justify establishing and defining the baseline.\nFine.\nThe introduction requires more background to give a comprehensive perspective on the study's goal and the expected readout. The introduction also mentions aging and neurodegeneration (L54) as causes of mitochondrial dysregulation, yet this study does not address either of these aspects and focuses on homeostasis as the baseline.\nLike the previous response, aging and neurodegeneration are mentioned to introduce the concept that microglial states and/or metabolism are altered in these situations. If we want to know how mitochondria are changed in microglia in these conditions, we must first define the baseline.\n\nResults:\nFigure 1:\ni) The justification for performing the high-resolution optical images immediately after (24h) performing the cranial window surgery to have an optimal expression of the Hoechst dye (L81) is only described in the method section (L411). These come with several limitations: first, microglia are still reactive due to the surgical procedure, and second, the brain tissue is under painkillers. Painkillers like carprofen (L406) target the prostaglandin G/H synthase 1/2 pathway (https://go.drugbank.com/drugs/DB00821), which will directly and indirectly affect microglia. The lack (or delay due to drug wear off) of mitochondrial movement under the 2Phatal experiment might be associated with this experimental limitation and should be controlled for.\nOur justification for acquiring high resolution optical images immediately after the surgery is to ensure the window is as clear as possible to perform 3D reconstructions, this justification has been clarified in the methods (see lines 538-540 for revision).\nThe possibility of acute side-effects of the surgery influencing mitochondrial placement in microglia is a valid concern. Please see our response to Reviewer #1 for details on how we addressed this by performing analysis on mitochondrial distribution in fixed tissue from the Cx3cr1-creER: Ai9: PhAM mouse line.\nFine.\nRegarding the effect of carprofen, our experiments in a chronic window (laser lesion response) and in an acute window (2Phatal) both show a delay in mitochondrial arrival to the processes responding to those injuries. Additionally, microglial responses to lesions and 2Phatal in our hands is the same as what has been reported before as stated in our references to previous studies in the original manuscript. Therefore, there is no evidence to show that carprofen is having a significant effect on microglial function that justifies repeating all the experiments with an alternative analgesic.\nOur intention was not to enforce repetition of the entire experiment. Instead, the authors should make the reader aware that painkillers can be a source of variability and should be part of the method/ discussion.\nii) L92: The description of the result needs to be clarified, and the results compared to typical profiles from other studies that have traced microglia (e.g., the deposit https://neuromorpho.org/ has several microglial skeletons). This will support a general conclusion.\nThe microglial morphological phenotype we report is consistent across several contexts in various brain regions. To emphasize this, we have added a revision to lines 101-102 referencing a couple primary examples that have also performed Sholl analyses to describe the pattern of microglial complexity.\nSince this is not the main focus of the study, the strategy is fine.\niii) Fig. 1e: The authors should show each primary branch of microglia individually as a first indication of whether specific branch properties, such as the branching complexity, relate to the abundance of mitochondria, especially since this will become a topic from L145 and a correlation exists for individual microglia in Fig. 3c.\nIt is not clear how this would significantly add to the study outside of what we already report. Our new data showing that microtubule presence is linked to mitochondrial partitioning adds additional information to explain which microglial processes have mitochondria and the underlying cytoskeletal mechanisms controlling this.\nFine.\niv) The analysis in Fig. 1f identified more elongated mitochondria without further insights into the meaning of this phenotype.\nThis is addressed in Figure 3e where we show that primary processes with greater mitochondrial content are more likely to have elongated mitochondria.\nv) Microglia show a sex-specific morphological response, especially during development, aging, and disease (Paolicelli et al. 2022, Colombo et al. 2022). The authors must annotate the data points in all manuscript plots, whether derived from male or female mice.\nWe appreciate the reviewer pointing this out and we agree that it is important to report sex differences. To provide a thorough report we have added now Supplementary Figures 5-6 for analyses of sex differences for all applicable experiments.\nThe addition of sex-specific analyses and data is appreciated and important for the transparency of published literature in the microglial field. However, there are some new and interesting findings from the data that is not mentioned or discussed in the text. Specifically, the female microglia have more rapid trafficking of mitochondria into the FOV after 2Phatal compared to the males (Supp Fig. 6g). And if more animals had been included, may also have resulted in greater nuclei cleared at 24 hrs by female microglia compared to males (Supp Fig. 6h). These findings could be very relevant to neurodegenerative conditions, as outlined by the authors in the introduction, and would be worthy of highlighting in the discussion section.\n\nFigure 2:\ni) The human EM datasets confirm similar distribution in mitochondria across branches as the mice; however, the value-add of this data falls short of its potential. Since the presence/absence of the mitochondria in specific processes is the focus of this manuscript, could the authors probe this available and annotated dataset to (i) compare individual branch features as described in Fig. 1; and (ii) identify when microglial processes are interacting with other cellular structures, i.e. neuronal dendrites, synapses or blood vessels and determine whether these processes contain mitochondria? If, for example, mitochondria are often located at contact sites with blood vessels, the authors’ in vivo imaging setup could interrogate interaction with blood vessels and corresponding mitochondrial location using a dextran dye during imaging in subsequent figures.\nTo address this request and further use the rich H01 human EM dataset, we determined microglia proximity to major features of the local cellular landscape in the new Figure 4. Specifically, and taking the advice of the reviewer, we focused on whether mitochondrial partitioning within single microglia varies depending on process proximity to blood vessels or neuron somas. We found no correlation between mitochondrial presence and proximity to vessels or neurons.\nMapping the connectome of a cellular process is a massive undertaking (For example: Wu et al. Neuron, 2024, PMID: 37898123) that is beyond the scope of the work. To begin to demonstrate the complexity of the microglia connectome, in Figure 4e, we provided 3D renderings of all cellular structures in contact with a single microglia process at a single z-plane. From EM data, we cannot determine if these contacts are interactions or chance contacts.\nThe provided insights are a plus, and we agree that it would require more extensive work to dig further into the details.\nii) Also, since this data is generated in females, a specific comparison to female mice microglia should be investigated.\nThere is no difference in male and female morphometric analyses from the mouse dataset (see the new Supplementary Fig. 5a, b). This indicates that our claim of the EM dataset corroborating the mitochondrial distribution observed in mouse microglia holds true- regardless of sex.\n\nFigure 3:\nA summary plot is missing showing whether the observed phenotypes described in L154f are common across all the evaluated microglia and whether sex-specific differences exist.\nPlease see the new Supplementary Figure 5d showing there are no sex-specific differences for the data the reviewer referenced in Figure 3e (lines 154-156 in the original manuscript, and now lines 162-164 in the revised manuscript).\nFine.\n\nFigure 4/5:\ni) The data shows that dynamic microglia branches lack microglia.\n- This result seems counterintuitive since movement would require ATP. The authors do not provide further explanation for this phenotype.\n- Which explanation can be provided for the differences in the mitochondria distribution?\n- The authors should determine the microglia processes’ speed and compare the results to the values in the literature (https://doi.org/10.7554/eLife.86749.2) to ensure that their data aligns. The same holds for the anesthesia experiments in Figure 5.\nWe completely agree with the reviewer that the result showing that dynamic microglial branches lack microglia is counterintuitive. In fact, the overall results of our study pertaining to the uneven partitioning of mitochondria in microglia and mitochondrial motility not keeping up with microglial process motility was entirely unexpected. In the revised discussion we emphasize these sentiments in the first paragraph, and in the rest of the discussion, we use the data from the new Figures 5 and 6 to offer a possible explanation for these stark observations.\nWe appreciate the reviewer’s suggestion to determine microglial process speed. Reviewer #1 also requested this, so the explanation of how we added this analysis to the new Figure 7c can be found in our response to Reviewer #1.\nWe agree with the authors that this data provides now novel insights.\nii) The effect of anesthesia on microglia and mitochondrial networks is introduced (L182ff), yet the rationale for investigating these conditions is unclear.\nPlease see lines 301-303 for a revision that adds a rationale for investigating awake vs. anesthesia conditions.\nFine.\n\nFigure 6/7:\ni) The results show that mitochondria are delayed in relocating to the microglial processes engaged with the lesion/apoptotic cell. These exciting results raise several questions:\n- Are the mitochondria arriving in the engaged process transiting from the soma region, or is mitochondrial biogenesis occurring to generate more mitochondria for distribution to the cellular compartment in need? To address this, it is pertinent first to assess whether the total mitochondrial content within a cell has changed during the imaging.\nThese are interesting questions. In the response to a laser lesion, we qualitatively observe that all microglial processes polarize toward the lesion site making all the mitochondria concentrate in the soma (this can be observed in Supplementary Movie 5 and in the time-series of the new Fig. 9). So yes, we can assume in the context of a laser lesion that mitochondria are transported from the soma to the process tips. When considering microglia processes that are initiating engulfment of an apoptotic neuron, we do not have the temporal resolution (time points obtained were 0, 3, 6, and 24 hours) to determine where the mitochondria are originating before they enter the process that is contacting the corpse of the neuron soma.\nWe do not believe intravital imaging of minute-to-minute process motility provides the resolution capabilities needed to determine changes in mitochondrial content over time. Therefore, we do not have the data to consistently and reliably provide a thorough analysis of increases or decreases in mitochondrial content. Future experiments with more sophisticated imaging and tagging of new vs. old mitochondria would be an interesting next step.\nAgreed. This point can be added to the discussion as future perspective.\n- Both laser damage and 2phatal induce apoptosis, thus releasing ATP into the neuronal environment. As one of the classic chemoattractants for microglia, is this involved in the mitochondrial transit? Or is the transit via a different signaling mechanism? Could the authors recapitulate the delay in mitochondrial transit in a culture system using ATP to begin dissecting a mechanism? Alternatively, if the process movement was delayed by adding a P2RY12-antagonist such as Clopidogrel, do the mitochondria transit within the original time frame or faster/slower than the process movement?\nTo clarify, only 2Phatal induces apoptosis while a laser lesion induces cellular membrane rupture and spillage of cellular contents (including ATP). This was explained in the original manuscript of the methods section for laser lesion and 2Phatal, and in the results section for 2Phatal- all with relevant citations. It is outside the scope of this study to repeat all the experiments to assay arrival of mitochondria into the processes when process motility is delayed. However, this would be interesting to assess in future studies, and we appreciate the reviewer’s suggestion.\nFine.\n- Changes in microglial metabolism in response to damage are essential to the mitochondria’s function. Although the authors discussed this concept at length (Paragraph L362), they could show whether optimal metabolism or altered metabolism affects the microglial process and mitochondrial transit in their two experimental setups. Do changes in microglial metabolism or available substrates affect the microglial process response or mitochondrial transit to the process? For example, in the HK2- mg specific KO mouse or in a brain slice setup, one could then apply different compounds as illustrated in https://doi.org/10.1038/s41467-020-15267-z\nWe appreciate the recommendation to investigate the effect of altered metabolism on microglial process and mitochondrial motility. The details of the experiment we performed to address this is discussed in the introduction of this document under the “In response to question #2” section.\nWe acknowledge the authors' efforts and recognize that this can be a challenging task and requires more substantial work.\n\nDiscussion:\nThe authors provide a comprehensive and well-written discussion highlighting several of the most recent findings in the subfield of mitochondria in microglia. There is a slight bias towards oligodendrocyte comparison (L327ff). While very thought-provoking, the paragraph discussion of metabolic changes would ideally be in relation to the results presented.\nThe discussion would also benefit from introducing the microglia concept of different states (see Paolicelli et al. 2022) and how the organelle distribution might allow distinguishing different states.\nWith the addition of the revision experiments the discussion has been reformatted, and the oligodendrocyte comparison was removed. Regarding introducing the concept of organelle distribution in different states, we have added a revision to touch on this in line 452.\nThe discussion comprehensively covers the most relevant aspects.\n\nOverstatements:\nThe study suffers from several overstatements, which should be corrected:\ni) L38: Are microglia indeed the most dynamic cells in the CNS?\nThis statement has been removed, and the initial sentences of the introduction reframed. See lines 40-41.\nThanks.\nii) L74/75: The retina is also part of the brain.\nYes, the authors agree that the retina is also part of the brain. The statement (now lines 79-80) emphasizes that this research has not been performed in the intact brain which is accurate as far as we are aware.\nFine.\niii) From the medical perspective, the temporal cortex of an epileptic patient, even though not the primary focal point, is also classified as diseased and not as a healthy, non-pathological condition (L461).\nThank you for this clarification. See lines 585-586 for revision.\nFine.\n(L247) The authors conclude in Fig 6 that ‘microglia that immediately chemotaxis to the site of acute tissue damage do not have mitochondria…’ It seems the authors mean to conclude that the processes do not have mitochondria.\nYes, we did mean to conclude that the processes do not have mitochondria. Thank you for catching that, see revision in line 358.\nFine.\nWe appreciate the overall positive feedback and helpful suggestions on the first submission. We have extensively revised the manuscript based on new experiments and additional data analyses. Overall, we took a multifaceted approach to address the reviewer requests, while also balancing the experimental and technical complexity of performing new experiments in vivo. We would like to emphasize that the request to generate a new knockout mouse line is prohibitively long and out of the scope of our study. This would involve generating a new quadruple transgenic mouse line. We agree that such experiments are worthwhile but waiting months to generate a new mouse strain followed by redoing essentially the entire study is certainly out of the scope of a revision. In the introductory section of this document, we summarize the approach we took for answering the major questions brought up by the reviewers before addressing each reviewer request, point-by point."}, {"round": 2, "reviewer_comments": {"reviewer_1": "No further questions.", "reviewer_2": "the lack of causal experiments is still a concern but I guess the descriptive experiments might be useful to some.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_4": "We thank the reviewers for their extensive work on the revision.\nWe have a few minor comments remaining that we added in the attached document in \"green\".", "reviewer_5": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter