Evaluation of 5 Intermediate Microglia’s Structural Variations Within an Organotypic Hippocampal Slice Model After Regionalized Toxic Injury

Evaluation of 5 Intermediate Microglia’s Structural Variations Within an Organotypic Hippocampal Slice Model After Regionalized Toxic Injury | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of 5 Intermediate Microglia’s Structural Variations Within an Organotypic Hippocampal Slice Model After Regionalized Toxic Injury Jesus Trejos, Francis Schanne This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4682521/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The dendritic cell of the CNS, the microglia (MG), is an initiation point of the immunological response within the post blood-brain barrier (BBB) compartment. Microglia drastically changes in response to cell stress to a much different non-dendritic morphology. This investigation postulates that if the first MG responses to toxic injury are isolated and studied in greater morphological detail there’s much to be learned about microglia’s metamorphosis from and M2 to an M1 state. The organotypic hippocampal slice was the experimental setting used to investigate microglial response to toxic injury; this isolates dendritic cell to post-BBB cells dynamics from the impact of nonspecific of in-vivo blood derived signaling. Within the context of biochemically verified precise toxic cell injury/death (induced with mercury or cyanide in combination with 2-deoxy-glucose) to a specific region within the hippocampal slice, MG’s morphological response was evaluated. There was up to 35% increase in microglia activation proximally to injury (CA3 region) and no changes distally (DG region) when compared to control slices treated with PBS. Maximum microglia activation consisted of a 3 plus-fold increase in the distance between the nucleus membrane and the cell membrane, which underscores an extensive and quantifiable amount of membrane rearrangement. This quantification can be applied to contemporaneous AI image analysis algorithms to demarcate and quantify relative MG activation in and around a site of injury. In between baseline and activated MG morphologies, 5 intermediate morphologies (or morphological behaviors) are described as it relates to its cell body, nucleus, and dendrites. The result from this study reconciles details of MG’s structure to its holistic characteristics in relation to parenchymal cell stress. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Microglia (MG) are the surveillance and maintenance immune cells of the central nervous system; and are also known as a type of dendritic cell. Their baseline dendritic morphology covers a large area of interstitial space and probes the highly exclusive compartment of the of the central nervous system (Li et al., 2018; Ginhoux et al., 2013 , Herculano-Houzel et al., 2018, Wirenfeldt et al. 2011, DiSabato et al., 2016). However, MG’s dendritic shape can drastically change in response to cell stress to a starkly different and compact and globular morphology. Therefore, this indicates they can take on several roles that are related to their different morphological states (Tang et al., 2015); namely its M1 state (activated, globular shape) and its M2 state (inactivated, dendritic shape). Importantly, MG monitor an interstitium that is considered one the purest ultrafiltrates in the body as it surveys tissue for damaged, dying, or dead cells. As such microglia’s sensitivity to the CNS environment allows prompt reaction to homeostatic perturbations within the CNS tissue matrix through 3 main characteristics; they are small, highly amorphous, and they are also motile. In addition to its janitorial duties, microglia are implicated in the pruning of synaptic connections that are important for neuronal networking (Paolicelli et al., 2011 ). Contemporaneously, much investigation has gone into some of portions of MG’s morphological characteristics; aspects such as size, area, branching, hull ratio, podocyte status has been considered (Fernández-Arjona et al., Filipo et al., 2019; Kamphuis et al., 2016 ; Minami et al., 2012 ). Also, some details of gene expression, mRNA profiling and single cell assessments have also been conducted to better understand their genetics (Keren- Shaul et al., 2017). However, more detailed information on MG’s individual and overall structural components is warranted to further characterize MGs dynamic morphology and potentially understand events antecedent to CNS cell death (loss of cell membrane integrity) modeled by toxic injury. This isolated tissue injury model can be harnessed to better establish intermediate microglial morphological states which could inform about its roles in homeostasis and disease within the isolated CNS’ post BBB compartment (Prinbz, et al, 2019; Li, et al 2018). Using MG’s holistic morphology as an endpoint can add greater resolution as to how this cell behaves during injury within the CNS which could be harnessed as a form of proxy determining adequacy for post BBB homeostasis. The differential shapes and sizes of microglia have been previously characterized in cell culture MG when the full range of morphology was evaluated 2 hours after ATP exposure (Xiang et al., 2006 ), which is a significant instigator of MG activation. Thus, the morphological profile is understood as isolated MG cells. However, the morphological profile of MG has not yet been thoroughly evaluated when embedded within cultured tissue. Therefore, a contextual way to evaluate the MG response is to utilize a model that represents not only the dendritic cell but its nascent cytostructural milieu, its adjoining tissue matrix. In addition, it would be best to hone in on the responses and signaling directly related to MG and CNS tissue matrix by isolating these responses from significant blood-derived immune cells replenishment and signaling outside the brain in-vivo and, conversely, more contextually than MG in isolated cell culture suspensions. The evaluation of MG was predicated on using one of its signature membrane proteins to determine its morphology, CD11. This protein is an important component of MG’s migratory capacity and therefore relates to one of its defining activity’s functions (Meerschaert, 1995 , Jurga et al., 2020). Furthermore, considering that CD11 is a membrane protein expressed on the extracellular surface of MG, a more detailed and representative depiction of its dynamic morphology could be appraised more so than an intracellular protein, such as Iba-1. Based on the immunohistochemical CD11 detection, the MG evaluated in this study has a morphology consistent with the dendritic motif and thereby under the purview of dendritic cell, that is a cell with dendritic processes (Gallizioli et al., 2020 ; Xiang et al., 2006 ; Kamphuis et al., 2016 ,) that migrates through the post BBB parenchyma. This study’s aim is to investigate how microglia have a definable gradient morphological response to regionalized biochemically verified toxic cell injury and/or CNS cell death (2 hours after inducing a toxic insult) in the context of an ex-vivo model, the organotypic hippocampal slice. Furthermore, the untreated area of the hippocampal slice can serve as an internal control to compare baseline MG near non-injured cells within tissue response to activated MG near injured/dead cells within tissue, and the intermediate morphologies in between. Nonetheless, within this response there’s focus on the morphological aspects such as MG cell body, dendrites, and nucleus placement, independently and holistically as metamorphosis occurs. These details can be potentially used to define intermediate forms of MG as it relates to different levels of CNS cells’ stress. As such, these different morphologies between M1 and M2 (Tang et al., 2015) can be designated to define the microglia’s “morphological behavior” which could be an important aspect of MG’s characterization as is found in and around injured tissue. Besides contextually displaying MG’s morphological information, this paradigm also concurrently isolates immune cell-parenchymal cell dynamics under the influence of cell stress with multiple controls. This gradation is the first time it has been characterized in an ex-vivo tissue model, not only does it confirm many of the known aspects of MG studied in-vivo and in-vitro , but also it allows visualization of MG’s inherent properties such as its sensitivity to fluid turbidity and motility. Overall, all this study will define in in-depth morphological detail, qualitative and quantitative aspects of MG’s metamorphosis from baseline (M2) to its activated state (M1) propagated by chemical toxicity within an isolated tissue context. METHODS Organotypic hippocampal slices Animal work in this study was performed under a IACUC (Institutional Animal Care and Use Committee) approved protocol in a facility accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. This facility also follows The Guide for the Care and Use of Animals, AVMA Guidelines on Euthanasia, PHS Policy on Humane Care and Use of Lab Animals, and USDA Animal Welfare Act regulations. All Sprague-Dawley rats were provided ad lib food; temperatures and humidity kept within recommended ranges; 12-hour light/dark cycles were maintained. Neonates were obtained from in-house IACUC- approved breeding protocol with breeder males and dams obtained from Taconic Farms. The best visualization of microglia (CD11 + cells) is in the neonate rat 10–21 day old (usually 1 neonate male or female per experiment), due to the relative translucency of the tissue matrix. Older animals have more opaque tissue and therefore CD11 + cells cannot be visualized in fine detail beyond 10x magnification. Animals were sacrificed via decapitation and brain was immediately excised from cranium, the whole hippocampi were carefully dissected out and placed in ice cold calcium and magnesium free Hanks balanced salt solution. Hippocampi were then placed on top of a 1.5% agar (Acros Organics Cat#: 400402500) block to slice tissue in a sagittal orientation at a thickness of 200 microns using a Syskiyou Tissue Slicer (Cat#: SKU 14240000E). Slices are then manually separated out individually by using a micro spatula immersed in ice cold calcium and magnesium free Hanks balanced salt solution. One rat (2 hippocampi) can yield 26–40 hippocampal slices. Tissue incubation Using a trimmed transfer pipette slices were removed from ice cold media and placed into Millipore filter (Cat#: PICM0RG50) within a well of a 6-well plate with preincubated culture media as described in previous papers (Marush, 2016; Stoppini et al., 1991 ); this media consists of 50% Minimum Essential Media (MEM), 25% Hanks Balanced Salt Solution (with calcium and magnesium) and 25% Horse serum. Excess calcium free and magnesium free media on the top of the filter should be removed prior to equilibration. Before any treatment with toxicants, the tissue was equilibrated in a cell culture incubator for 1 hour. Microglia Visualization After isolation and/or treatments hippocampal slices were placed in 4% paraformaldehyde in PBS for 15 minutes. Then slices were blocked with 10% FBS in PBS for 30 minutes. Primary Anti-CD11 Antibody (mouse anti-rat mAb Cat#: MA-9u29) was added to slice with 1.5% FBS and 1.5% goat serum for 1 hr under slight shaking. Secondary Ab conjugated with phycoerythrin (goat anti-mouse Cat #: Fb106) was added to slices with 1.5% FBS and 1.5% goat serum for 30–60 minutes. Slices were visualized from directly semiporous filter top appraise morphology. Slice could also be visualized after being placed into a glass slide and mounting media (Cat #: P36983 -) and gently capped with cover slip. An EVOS fluorescence microscope (Cat#: AMF7000) was utilized to capture all MG imagery after mounting media sets, preferably on the same day. Images were surveyed for CD11 cells (in between the central portion of slice and the CA3 or DG row of cells) and their morphological categorization; baseline shaped (stellate with fine processes) or activated (enlarged cell body with thickened processes). Greater than 3 activated MG adjacent to each other are rarely observed in baseline untreated slices and therefore when this was observed they were indicative of site of toxicant-related injury. RESULTS MG within the cultured 200-micron hippocampal slice tagged with an anti CD11 antibody demonstrated the same morphological featured reported in other in-vivo and in-vitro investigations (Fernández-Arjona et al., Filipo et al., 2019; Kamphuis et al., 2016 ; Minami et al., 2012 ; Lana et al., 2019 ). Microglia are henceforth defined visually as CD11 + continuous red staining enveloping a blue DAPI-stained nucleus. Baseline MG were similar whether slice was evaluated immediately after isolation or after a 2-hour incubation, indicating stability of baseline MG 2 hours after excision. Within the confines of the hippocampal tissue slice MG were ubiquitously observed throughout, they consist of a significant portion of the overall cell population, and they were evenly distributed (Figs. 1 -b, c, d). Within the isolated tissue context MG demonstrate a homogeneous distribution and they seldom overlap. The central portion of the hippocampal slice (yellow circle in Fig. 1 ) contains slightly more condensed microglia staining, it is also worth noting that there were more activated ameboid-shaped MG present within this central region. After surveying MG beyond the central portion (yellow circle in Fig. 1 -B, C) reveals that they have more spacing in between them and there are 5–7 cell rows of MG out before reaching the CA3 track of nuclei. The density of nuclei of the CA3 track interfere with clear MG visualization, and thus optimal region of MG morphological evaluation is the region in between the central MG-dense portion and the CA3 track (Where MG were circled with blue circles Fig. 1 -b). Therefore, after an appraisal of MG’s distribution and appearance throughout the hippocampal slice, MG’s morphology can be most effectively evaluated within the proposed tissue context in between the CA3 region and the central portion (yellow circle in Fig. 1 -B, C). In conditions where the hippocampal slice was immersed in media, instead of resting on a semiporous membrane (as historically used in electrophysiology experiments), several MG cells exhibited a highly ameboid shape (Fig. 1 -F, G), insofar as suggesting that the lack of stability brought about the fluid destabilizes the cell body and thus MG lose its fine structured dendritic motif. The stark change in morphology is consistent with the notion that this cell can readily be prompted to change shape from its originally observed fine-processed structured motif. Also, this suggests that a MGs baseline state (and ergo shape) is predicated upon attachment points (Tian et al., 1997 ) within the tissue. Therefore, MG can be prompted to change shape within the hippocampus slice. Characterization of activated microglia within the context of biochemically confirmed precise toxic cellular injury Examining the microglia response within the hippocampal slice using biochemically verified toxic doses resulted in stark morphological changes to MG. Upon toxicant exposure within a specific region of slice (on CA3 side) a crater forms and at high doses it is characterized by an intense core of nonspecific red fluorophore staining with a rim of activated microglia (Fig. 2 -A, B). Activated MG exhibit more intense fluorophore intense staining, have shorter and thicker dendritic processes and have enlarged cell bodies around their nucleus that make them easier to visualize in the magnification plane than when they are in their baseline state (Fig. 2 -C, D). The dentate gyrus region was not treated with toxicant and thus baseline MG remained in its non-activated fine-processed structured motif with a small cell body around the nucleus (Fig. 2 -G). Cell counting analysis on all the MG in 40x images indicated that not all MG become activated with greater distance you get from the site of injury the less activated the MG (Graphs on Fig. 2 -E and -F). Areas of tissue injury were characterized by the appearance of different MG morphologies that were different from its baseline shape. The spot-tox demonstrated a gradation of MG profile related to injury distance. The closer the MG were to the area of injury, the more activated and condensed they appeared. Therefore, MG can exhibit morphologies that indicate it is in its activated state (M1, ameboid) after being treated with biochemically verified toxic doses of mercury and cyanide in combination with 2-deoxy-glucose. Microglia’s different shapes and sizes from injured to non-injured tissue. After surveying the IHC (labelled for CD11) slice for MG in treated slices, MG changes in shape were observed near and around the area of toxicant exposure (spot-tox). Areas distant (dentate gyrus Fig. 2 -F) from spot-tox site exhibited mostly MG that resembled baseline shapes and were corroborated with control slices; that is, with fine dendrites and stellate form with a small cell body. In between these two regions there was a variety of shapes noted mostly in changes in overall shape and size. The size of a baseline shaped MG distal to the injury site is 30–40 microns and mostly exhibits fine-stellate processes that were 1 micron thick. MG near the nearest surviving area of the spot tox were much more condensed, globular and smaller in size (10–15 microns), however in certain instances stellate MG were also noted but with thicker processes of 7–9 microns thick. The MG in between these 2 shapes may represent a gradation of activation that is being predicated by differential toxicant concentration from the core of the placement of the 180 nL aliquot. Whereas the toxicant concentrations were highest at the central site where the 180nL drop landed on the tissue, the surrounding areas were diluted with the media already within the slice tissue matrix and thus the portions further from that area represent places where toxicant concentration was decreased. This is corroborated in the MTT studies (Trejos et al., In preparation), where a gradation in the shade of formazan blue was decreased, but PI was still being excluded; indicating areas of injured but still viable cells (defined as cells with membranes still excluding PI) toxicant concentrations. In these sublethal regions, MG were more mixed in morphology and varied between shapes that resembled baseline fine dendritic stellate motif, stellate with thicker dendrites and ameboid with little to no dendritic processes (Fig. 3 ). Another way to consider the changes of MG from injured to healthy tissue is the rearrangement of its cell membrane; insofar as there is an appreciable accretion of the membrane (and hence IHC CD11 + mediated staining) that thickened as it becomes more activated, and importantly, it becomes a denser cellular particle; this shape is contrary to a delicate fine structured web of stellate branching emanating from a small cell body when MG is in its baseline state. Ergo upon surveying these MG, the progression from baseline stellate structure in uninjured tissue to that of an activated ameboid around most injured viable tissue one may correspond a measurable change to the membrane, which accretes and thickens around the nucleus based on the severity of injury. Quantifying microglia’s structural aspects in different morphological states Baseline microglia compared with activated MG results (after 12 mM Hg injury) in the elucidation of quantifiable structural data as it pertains to its cell body/soma and rearrangement of cell membrane. As previously mentioned, baseline MG’s shape characteristics relates to not just size of the entire cell, but the presentation of its membrane’s distribution. The membrane encapsulates the nucleus and emanates from this centrality via the protrusion of fine filaments that are typically no wider than 1 micron thick; taken together, resembles the shape of a star and hence stellate in appearance (Fig. 3 -A). The opposite extreme of MG’s membrane distribution is the ameboid shape of MG that is the morphologically characterizes it as this it being in its activated form (Fig. 3 -P). In this opposite motif, the membrane also encapsulates the nucleus, however two main distinctions are obvious; that is that most, if not all, processes are no longer present (and those that remain are shorter), and the cell body that surrounds the nucleus is much thicker and stains more intensely. The stark changes in cell body can be quantified by measuring the greatest lateral distance (after an initial polarization of MG’s soma) of the cell membrane to that of the nucleus’ membrane within an individual MG. During surveying of control slices MG’s baseline state this distance is typically 0.8–1.5 micron thick, as demonstrated in Fig. 4 -A. During surveying of spot-tox treated slices MG’s opposite activated state this distance is greater than 3 microns as demonstrated in Fig. 4 -B. This structural demarcation was compared in the spot-tox injury model’s 20x images, and upon comparisons of different MG’s within, statistically significant (student t-test) quantitative changes in distance between the nucleus membrane and cell membrane resulted. When all the MG in the control slices were compared to all the MG in spot-tox treated slices a statistically significant change were observed; control slice MGs had distance from nucleus to cell membrane was 1.49 microns, while treated slices had distances of 2.93 microns (Graph on Fig. 5 ). Within Hg-treated slices that had activated MG around the injury area of spot-tox were compared to MG in regions proximal (non-treated area) and distal (DG area) to injury and thus within healthy portions of the tissue and statistically significant quantitative changes in structure were also found. A spot’s borders were set by the appearance of 2–3 MG next to each other within the region between center of slice and the CA3 track of nuclei. These MG has a nucleus to cell membrane distance of 3.46 microns (Graph on Fig. 5 ). Any other MG outside this border in between the CA3 nuclei track and the center of the slice was considered a proximal non-treated area; this area had average distance of 2.40 (Graph on Fig. 5 ). To ensure that the slice had enough baseline MG present, the dentate gyrus region was evaluated as a healthier portion of the slice that was distal to the spot-tox; these MG have a distance that was similar to control slices at 1.56 microns Graph on Fig. 5 ). Therefore, MG structural changes can be quantified by measuring the distance of the nucleus membrane to that of the cell membrane. This quantitative data is indicative of the amount of cell membrane rearrangement that occurs when a MG goes from one extreme state (baseline) to the other (activated). Figure 5 exemplifies many of the different shapes and forms captured in between the baseline form of MG and the activated form of MG. Within his study, there are intermediate forms of MG that were also captured; this metamorphosis indicates that as the MG gets activated and accretion of the cell membrane occurs, and thus the area that the cell membrane spreads throughout shrinks and the fine filaments (characteristic of the baseline state) thicken as they shorten into the cell body. Also, there is a polarity of the MG soma that is exhibited as it accretes more intensely at polar opposite ends of the cell body, which is indicative of a pattern of membrane compression. This significant rearrangement of cell mass is an important consideration to bear in mind within the context of the tissue matrix; this will be elaborated upon in a follow up manuscript that endeavors on describing intercellular spacing within this tissue (Trejos, 2023 in preparation). Another important consideration with regards to the changes in membrane rearrangement that MG undergo is the location of the nucleus within the enlarged cell body (Fig. 6 -E, F). Since MG generally have an asymmetric layout the placement of the nucleus can be an important consideration as it can serve as a point of morphological distinction. This is mostly appreciable when MG cell body is greater than 10 microns in length, which is twice the size of its nucleus’ diameter (consistently measured at 5 microns in this study). At baseline although the nucleus is clearly present there is very minimal cell body present to appraise the nucleus’ placement within. However, when the cell body is big enough, the placement of the nucleus can be categorized as central, or it can be located closer to one of the extremities of the elongated/enlarged cell body. In between baseline and activated morphologies MG exhibit many characteristics and different forms. One of the most important visual characteristics of baseline MG is the preponderance of dendritic branching (1 micron in thickness) emanating from a small cell body that contains the nucleus. Notably, that MG cell bodies are somewhat more difficult to see when they are in their baseline morphology as they are not only thinly dispersed, but they are also well-ensconced within the tissue matrix and hence visually blocked within the image fields (40x). At the other extreme, MG have very little to no branching and it is very globular in shape and very stark in appearance; activated MG morphologies are more readily visible than the baseline MG morphologies. In between these 2 extremes, other morphologies were observed (Fig. 3 -A and 3 -P), which are likely intermediate shapes that represent the membrane rearrangement described in the previous section. Also, it is important to note that these intermediate MG morphologies are present 2 hours after initial injury. As baseline MG accretes, the cell body in and around the nucleus begins to gain form in a polar manner; that is, the membrane is closing in from 2 opposing ends. Concurrent to this cell body rearrangement, the dendritic processes become shorter and thicken to greater than 1 micron. This thickening helps improve the resolution of MG’s seemingly amorphous cell body appearance as it gives the cell body and dendrites more structural definition, which assists in the delineation of structural landmark dendritic protrusions as they thicken as the membrane is rearranging into the cell soma. The plasmalemma from distal dendrites involute towards the nucleus which is considered a central position of this cell’s baseline layout. A simplified perspective, from a cell structural standpoint, this metamorphosis is a complete redistribution of MG’s plasmalemma. Membrane that was once 20 + microns away from the nucleus is now proximal to the nucleus and yielding a more prominent dense cellular particle with its plasmalemma concentrated in and around the nucleus. Therefore, within this controlled tissue sample matrix different iterations of CD11 + MG’s morphology and details of its structural constituents (soma, nucleus, dendrites) are visualized. Visualizing the number of microglia’s processes/dendrites A range of 6–10 dendritic processes were usually counted in an assessment of 26 baseline-shaped MG cells (in 16 different 40 x images across different experiments); the dendritic counts were corroborated with several other published studies (Ugloni et al., 2018; Fernández-Arjona et al., 2017 ; Masuch et al., 2016 ) that looked at MG morphology and thereby displayed detailed MG images (Fig. 6 -A-D). A dendrite was characterized as a track of red fluorescence (CD11-labelling) emanating out of MG’s main cell body’s membrane in a perpendicular trajectory. There are several presentations of how dendrites protrude out to resemble distinct motifs. A common MG motif is where one end has a major off-center dendrite that bifurcates into 2 large branches, the other major dendrite, seemingly a tail, that emanates directly from the soma end that spits into 2 tapering ends, similar to a maimed lobster (guide bars run parallel to dendrites in pictures of Fig. 6 - A, B, C). Usually two of these three major (thicker) branches have 2–3 major sub-branches that keep bifurcating out to other smaller branches when MG is in a baseline (M2) state. The other 3–6 branches are not as thick and long but can also bifurcate out to create smaller dendritic processes (Fig. 6 -A, B, C). Taken together, MG in its baseline M2 state presents with several dendritic processes that can be quantitated to a number of 6–10 in any given individual MG cell. DISCUSSION Microglia cells have a unique position in the immune response in the post BBB interstitium as they are usually the first motile responders during perturbations within the extracellular biological matrix. This cell is mobile and highly amorphous and as such its characteristics can potentially be visually read by evaluating its shape and the sum of its three main structural components: the soma, the nucleus, and the dendrites. Much investigation has gone into studying its behavior and signaling during activation (Fernández-Arjona et al., Filipo et al., 2019; Kamphuis et al., 2016 ; Minami et al., 2012 ), this is the first reported evaluation within a cultured organotypic tissue model that activated a subset of MG within the tissue model with a toxic injury but left the rest of the MG in its inactivated baseline state. Thus, one of the enticing aspects of observing MG embedded within a viable tissue matrix is observing MG response events in-situ; by modifying (via toxicity) the immediate interstitium amid a viable biologically active sample (as demonstrated in electrophysiology studies). Also important to note that maintains the microscopic structural layout of a mammalian brain is preserve in this tissue slice. The benefit of this condition is that it allows for evaluation of a spectrum of MG morphological changes that occur from being in a baseline state to that of being fully activated within the tissue context However, prior to delving into these deep queries on how MG (and CNS cells) ascribes a genetic commitment that leads to stress related biochemical, proteomic changes, a reproducible cellular response must first be ascertained, in this study such cellular response is morphology and thus how MG cell rearranges its cell membrane. Such is that this investigation into microglia’s morphology after precise toxic insult elucidates a nuanced cellular response, and in turn also revealed many details of MGs’ morphological behavior within its nascent CNS surroundings. The first two characteristics, nucleus and cell body of the MG are intimately related as they are both stark visual landmarks whether MG is in its baseline state or its activated state. Albeit there are appreciable changes in size of MG when activated versus in baseline, the most consistent quantifiable change is the space between the nucleus membrane and the cell membrane, as mentioned in Graphs in figured 7 and 8. This is an important marker not just of size, but more so the rearrangement of MGs cell membrane borders. The amorphous nature of MG is one of its important characteristics and these stark changes to cell structure enable functions as it relates to MG’s baseline state or activated state. Thus, when MG is in its baseline state the cell membrane’s distance (the wider of the lateral 2 distances) from the nucleus is around 1 micron thick, thus it is presupposed that the rest of the membrane is thinly spread out covering a designated surface area as it conducts its baseline activities. Conversely when MG is activated the nucleus’ membrane distance from cell membrane is greater than 3 microns on average (up to 6 microns individually), which is a substantial change. This quantitative change can serve as an indicator of level of activation of MG. As such this distance can serve as a point of distinction by characterizing intermediate forms of MG, along with other ancillary visual characteristics: dendrites size, shape and nucleus placement. Irrespective of the two distinct mechanisms of cell death and injury, MG morphologically behaved in the same way at least in this rudimentary qualitative assessment of MG shape. These 2 models of toxicological insult (mercury and cyanide combined with 2-deoxy-glucose) leveraged the knowledge of toxicological agents’ mechanism of toxicity to induce a cellular response, activating MG from an M2 to an M1 state. Understanding the meaning/functionality MG dendrites is paramount in the understating of MG’s inherent biology and response to toxic insult. One of the most defining characteristics of MG is the presentation of their dendrites (Ugloni et al., 2018; Fernández-Arjona et al., 2017 ; Masuch et al., 2016 ). As described in the results, there are usually 3 major dendrites and one of them bifurcates into 2–3 branches of similar width, which resembles a claw. This dendrite is usually off center and therefore lateral, which indicates that these cells are asymmetrical. This asymmetry can be useful in determining the orientation of the cell and thus have a greater appreciation of its layout within the tissue matrix. Furthermore, the other dendrites serve some sort of functional weight, potentially distinguishing the functions of all these variety of dendrites and providing important information about these morphological behaviors. These behaviors can offer information about how these dendrites are protruding and assist in several different functions, for example: the adhesion or anchoring to the extracellular matrix, reach out to neighboring MG to maintain adequate spacing (since they seldomly overlap), probe the extracellular fluid (for either signaling or indications of cell damage), or directly probe neurons, astrocytes (and other CNS cells), cellular address probes, etc. and other undiscovered functions. Conversely these dendrites involute during MG’s most activated states, however often dendritic stumps remain, what role do these dendritic remnants emanating from the ameboid MG cell body play when MG is conducting its activation duties? Taken together, the nature of the MG cell is one that is highly animated and has several different opportunities for scientific endeavors on how these cells can serve as biomarkers of extracellular adequacy. The morphological plasticity of MG is intrinsically connected to its response to toxic injury. The main tenet of this study was to examine a controlled signal to noise of MG according to its morphology presentation within a sample that had simultaneously healthy and injured tissue, such is why the toxicity was localized to only injure a portion of the hippocampus tissue sample. Prints et al., (2019) describe that establishing microglial states can be essential to their roles in homeostasis and disease, such example was postulated as the disease associated MG (DAM) that was genetically characterized by (Keren- Shaul et al., 2017). This study ascribes the morphological state as a determinant of its behavior, ergo “morphological behavior”. Morphological behavior alludes to the benefit of a cell’s structure to a role it is executing in response to its surroundings. Structure is an important demarcation of cellular activity because of the cells biochemical, metabolic, proteomic, genetic, and adaptive commitment of maintaining a specific macro shape. Many of the descriptions of baseline microglia in the literature default this structural motif to that of it being in a state of “sensing” the extracellular environment. Taking into account the known roles of MG it is understood that this state is within its purview of its characteristic activities, a sentinel of extracellular medium’s adequacy. In a baseline state they are spread out evenly throughout the hippocampus tissue matrix and seldom overlap; this fine stellate form is suggestive of a behavior such as sensing and probing the interstitium’ s integrity as well as the somatic cells they mount as they migrate through an extracellular region. Baseline MG size ranges from 30 to 40 microns, and the filaments that emanate from the cell body that is just 1 micron thicker than the nucleus compartment, and the filaments themselves are barely thicker than a micron in width. This is logical considering the generally accepted phenotypic job description of dendritic cells, it is virtually a cellular detector of extracellular conditions. Upon its activation, MG changes into a much different shape and therefore it is no longer optimized for detection, it metamorphizes into a compact globular circular shape in its most extreme form of activation. The activated shape is likely more amenable for endocytosis of cellular debris that occurs during injury, accelerated motility and/or cordoning off a space withing the interstitium as this enlarged shape decreases the space available through micro-openings in the interstitium from which motile cells lay their trails. Spatial obstruction by activated MG could decrease the flow of non-optimal extracellular fluid contaminated with potentially harmful intracellular contents from cells with compromised membranes. Table 1- Structural details about microglia's 5 different Structural Variation s between its baseline morphology (M2 state) and activated morphology (M1 state) It is also important to note that MG activation does not seem to be a binary outcome, that is, there are other intermediate forms that can arise and participate in the recovery or pathologic process. The most compelling piece of evidence of this is simply the appearance of these intermediate forms near regions of cellular stress. This region is found right outside the most central part of the spot, where all cells are presumed dead (Fig. 2 - B). Further, these changes can be characterized by membrane rearrangement, the appearance and morphologies of dendrites and nucleus placement within the MG. Had MG morphology been a binary outcome only baseline and activated forms would have been found in these areas. Therefore, considering that MG activation fall into some sort of spectrum, these forms can signify the state of the immediate matrix they are surrounded by, and thus have a better understanding of the initial stages of cellular perturbation as recognized by this primary sentinel immune cell’s morphological presentation. As described in the results section (Graphs on Figs. 6 , 7 ) one of the most quantitative ways to assign this morphological spectrum is to measure the distance of the nucleus membrane to the cell membrane as that underlines the extensive amount of membrane rearrangement MG undergo that happened after the cell polarizes. In between these 2 extremes 5 different morphologies were identified using cues from the size and shape of the soma and dendrites as well as the overall length of MG (Fig. 7 , 7 T). These are postulated to be stable morphologies since they are present even 2 hours after the initial toxicological insult and since there is no migration of MG observed these are not interloper MG cells that migrated from other region (or from nearby blood vessel). Had there been migration it could have been postulated that these were migrant MG from other areas that were just arriving at the sites of injury and thus in the middle of the M2 to M1 metamorphosis. Therefore, these intermediate morphologies can be ascribed to roles that have not yet been elucidated. Collating the visual empirical data gathered in this study together, that is MG overall size, shape/size of soma and appearance of dendrites a pattern of other morphological behavior intermediates emerges. Namely 5 different intermediate structural variations become apparent (Table 9T). These qualitative categorizations are subjected to the appearance of the soma, nucleus, and dendrites in a 2-dimentional plane that captures all three. The 2 extremes of morphological behavior are M1 (activated MG) and M2 (baseline MG); the former is a dense cellular particle that is globular and has no dendritic processes, the latter is the appearance of a nucleus enveloped by a thin cell body with several thin dendrites emanating out of it. Since based on the quantitative assessment, the membrane of the soma gains greater distance from the membrane of the nucleus, a qualitative assessment as to the orientation of the membrane is applied; that is, when and where this separation starts to happen. Also, how this qualitative characterization change in membranes’ distance relates to the thickness and length of the dendrites is appraised. In between the two extremes five morphological states are described: Morphological behavior 1 - The first indication of morphological changes after the baselines state is the widening of the soma as the space between the nucleus membrane and the cell membrane start to gain some distance, this distance improves the visualization of MG as membrane stain is more intense. Morphological behavior 2 - Is demarcated after the first separation of the nucleus and cell membranes, the soma begins to polarize, that is, the slightly thicker membrane begins to accrete at opposite ends which results in an uneven encirclement of the nucleus which renders the soma more oval than circular in shape, in addition the soma is elongated to the point that the nucleus can be regionalized within, usually there is 10 microns (or 2 nucleus lengths) between the 2 polar ends of the soma. After the polarization/elongation the soma begins to widen and the measurement of the lateral distance of the soma’s membrane to the nucleus’ membrane could be objectively measured (as was demonstrated in Graphs in Figs. 6 , 7 ). Morphological behavior 3 - Is the further elongation of the soma to the point that it reaches 3 nucleus lengths, but its width starts to be greater than 7–8 microns wide and thereby lateral separation from nucleus membrane begins; another very important distinction is the widening and shortening of the dendrites. An important structural consideration to morphological behavior 3 is that the accretion of soma is beginning to yield a denser cellular particle, which means it is becoming a more obstructive presence within the space it occupies, an important spatial consideration. The immediate consequence of this size and shape change is the alteration of interstitial fluid flow and the passage of motile cells. Morphological behavior 4 - After max elongation is reached (usually 15–20 microns) presents as a highly visible MG that has a much bigger and thickened soma but still stellate as all the dendrites are also thickened. Notably its dendrites are shortening into the soma, also, the nucleus membrane will gain greater distance from the cell membrane. Morphological behavior 5 - the last step before full activation, the soma is even more globular, rotund, but most notably there are fewer dendrites and the ones left over appear as stumps, compared to how they looked previously. This metamorphosis does appear to bear some impact on the conditions of the unique interstitium of the CNS, namely in the redistribution of the area of this cell’s soma and the impact of this on the availability of interstitial space, which will be discussed at greater length in an upcoming manuscript (Trejos, in preparation). Taken together, breaking apart the main characteristics of MG (soma, dendrites, nucleus) their intermediate forms suggest that they could be objectively discerned as having distinct visually definable morphological behaviors; this is important because they can be associated with states of cellular stress prior to cell death as many of these intermediate shapes appear within the injury region of the spot tox adjacent to the epicenter. Furthermore, and importantly although the measurements in this research were done manually (Fig. 4 and Fig. 5 ), this quantification can illustrate a great potential image analysis tool to evaluate the relative activation of MG in and around injured tissue. This can be potentially applied to AI program algorithms that can detect and evaluate MG in greater detail, so long as the setting can be programmed to detect and discern the nuclear membrane to that of the cell membrane; the relative distance between these 2 walls can be easily measured. Microglia characterization within the tissue suggest a cell that undergoes dynamic change and structurally acquiesces to its extracellular environment, likely why MG evacuating the tissue matrix exhibit differences from MG embedded within tissue (Fig. 2 -F, G). Utilizing this morphological behavior criterion can inform the relative response of a MG with regards to its response to a cellular event that indicates cell damage is occurring. In Fig. 7 the higher gradations of structural variations surround the activated state whereas conversely the lower gradations surround the baseline state. Having this response layout can add resolution to the level of cell injury and how the structural variations of MG can be utilized as a proxy for perturbations in cellular or interstitial homeostasis. The offered resolution to cellular metamorphosis of MG should serve as important distinction points of its activity as it relates to its morphology that can suggest an anomalous interstitial condition (which arises from an injured cell that is about to lose viability) ergo a precursor pathological event that eventually leads to some CNS pathology (in this case pathology that arises from chemical toxicity). Importantly, this detectable/measurable precursor event, microglial metamorphosis, may offer better opportunity for understanding how dendritic/MG cells respond to post BBB CNS cell stress; that is, if we confide in the ability of these cells to detect CNS cell injury prior to than the current most sensitive determinants (intracellular enzyme levels increases in extracellular fluids which suggests their leakage from damaged cells). These cellular events are likely antecedent to mass enzyme leakage which represent cell membrane rupture. In conclusion, microglia are a unique cell within the most exclusive extracellular matrix in the body, its 3 main characteristics, that is: size, dendrites and cell body shapes allow the assignment of distinct morphological structures. Affirmations of cell stress that is biochemically verifiable and confirmations of MG shape shifting characteristics could most effectively be done in this culture model; further and probably most importantly, the initial events of cellular stress within the context of cellular architectural tissue matrix are isolated. Downstream biochemistries can be studied that ascribe certain genetic (as demonstrated by Keren- Shaul et al., 2017) or proteomic changes that can relate to MG’s morphology can be further characterized and studies in greater detail in this isolated sample without the noise presented by extra-matrix influences of blood derived cells and chemokine signaling outside the interstitium; and conversely, much more contextually than in cell suspension culture isolation. And, albeit MG appears as an amorphous construct, it follows a certain structure pattern as it metamorphosizes and thus leads to 5 distinct intermediate definable structural variations between baseline (M2) and activated (M1) forms. Furthermore, detailed, and definable aspects of its cell body structure (and quantitative changes in membrane distances that can be amenable to algorithmic evaluation), nucleus placement and number of dendrites indicate that perhaps MG’s shape isn’t as vague as it appears. Also, it is important to note that as MG reach the M1 state (structural variations 3+) they become a denser cellular particle that can impact interstitial spacing and thus glymphatics (Nedergaard et al., 2020; Trejos et al., in preparation) and thereby interrupt interstitial flow. Such is that the data generated from this isolation indicated that the hippocampal tissue slice is a relevant biological quantum of contextualized cells that maintains initial immune cell activity, confirmable survival, and spacing profile of CNS tissue matrix after excision. The biochemical confirmation of a cellular stress and death using MTT and PI, and then evaluating the individual properties of the MG cell response as a dendritic cell represents a fortified rational biological sequence of events that can be isolated and explored further. This isolation can shed some further depth of biochemical, proteomic, and genetic understanding as to what happens when tissue is injured and how it concerts with immune cells’ morphological response. Nevertheless, the structural resolution offered describes how microglia behave morphologically and can be used to potentially attribute events antecedent to cell death within the post BBB CNS and adds greater depth of knowledge to microglia’s role in this highly exclusive parenchymal compartment. Abbreviations Artificial Intelligence (AI) Antibody (Ab) Blood Brain Barrier (BBB) Central Nervous System (CNS) Cluster of Differentiation 11 (CD11) Dentate Gyrus (DG) Disease Associated Microglia (DAM) Ionized Calcium-Binding Adaptor (IBA-1) Lactate Dehydrogenase LDH Immunohistochemistry (IHC) Messenger Ribonucleic Acid (mRNA) Microglia (MG) Modified Eagle Medium (MEM) Phosphate Buffered Saline (PBS) Propidium Iodide (PI) Fetal Bovine Serum (FBS) Fluorescein Diacetate (FDA) Cell Counting Kit 8 (CCK-8) 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) 4′,6-Diamidino-2-Phenylindole (dapi) Declarations Author Contribution JAT wrote the manuscript, FAX edited and reviewed manuscript. Acknowledgments: Linnea R. Vose, Ph.D. and Patrick K. Stanton Ph.D. for training on how to isolate rat hippocampal slices using a Syskiyou tissue slicer. References DiSabato D, Quan N, and Godbout JP. Neuroinflammation: The Devil is in the Details. 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Overview of General and Discriminating Markers of Differential Microglia Phenotypes. Frontiers in Cellular August 2020. Volume 14 Article 198 Kamphuis W, Kooijman L, Schetters S, Orre M, Hol EM. Transcriptional profiling of CD11c-positive microglia accumulating around amyloid plaques in a mouse model for Alzheimer's disease. (2016) Biochimica et Biophysica Acta 1862 1847–1860 Keren-Shaul H, Spinrad A, Weiner A, Matcovitch-Natan O, Dvir-Szternfeld R, Ulland TK, David E, Baruch K, Lara-Astaiso D, Toth B, Itzkovitz S, Colonna M, Schwartz M, and Amit I. A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease. Cell 169, 1276–1290 (2017) Lana D, Ugolini F, Wenk, Giovannini MG, Zecchi-Orlandini S, Nosi D. Microglial distribution, branching, and clearance activity in aged rat hippocampus are affected by astrocyte meshwork integrity: evidence of a novel cell‐cell interglial interaction. (2019) FASEB J. Mar;33(3):4007-4020. Li Q and Barres BA. Microglia and macrophages in brain homeostasis and disease. | APRIL 2018 | VOLUME 18, 225-242 Masuch A, van der Pijl R, F€uner L, Wolf Y, Eggen B, Boddeke E, and Biber K. Microglia replenished OHSC: A Culture System to Study In Vivo Like Adult Microglia. Glia. 2016 Aug;64(8):1285-97. Meerschaert J and Furie MB. The Adhesion Molecules Used By Monocytes for Migration Across Endothelium Include CD1 I a/CD18, CDl 1 b/CD18, and VLA-4 on Monocytes and ICAM-1, VCAM-1, and Other ligands on Endothelium. The journal of Immunobgy, 1995, 154: 4099-41 12. Minami SS, Sun B, Popat K, Kauppinen T, Pleiss M, Zhou Y, Ward ME, Floreancig P, Mucke L, Desai T and Gan L. Selective targeting of microglia by quantum dots. (2012) Journal of Neuroinflammation, 9:22 Nedergaard M and Goldman SA. Glymphatic failure as a final common pathway to dementia. Science 370, 50–56 (2020) Paolicelli RC, Bolasco G, Pagani F, Maggi L, Scianni M, Panzanelli P, Giustetto M, Ferreira TA, Guiducci E, Dumas L, Ragozzino D, Gross CT. Synaptic Pruning by Microglia Is Necessary for Normal Brain Development. (2011) Science 333, 1456 Prinz M, Jung S Priller J. Microglia Biology: One Century of Evolving Concepts. Volume 179, Issue 2, 3 October 2019, Pages 292-311 Stanton PK AND Sarvey J. M.. Blockade Of Long-Term Potentiation In Rat Hippocampal Ca1 Region By Inhibitors Of Protein Synthesis (1984) The Journal of Neuroscience Vol. 4, No. 12, pp. 3080-3088 December Stoppini L, Buchs PA and Muller D. A simple method for organotypic cultures of nervous tissue. (1991) Journal of Neuroscience Methods. 37 173-182 173 Tang Y and Le W. Differential Roles of M1 and M2 Microglia in Neurodegenerative Diseases. Mol Neurobiol (2016) 53:1181–1194 Tian, L., Kilgannon, P., Yoshihara, Y., Mori, K., Gallatin, W. M., Carpén, O., et al. (2000a). Binding of T lymphocytes to hippocampal neurons through ICAM- 5 (telencephalin) and characterization of its interaction with the leukocyte integrin CD11a/CD18. Eur. J. Immunol. 30, 810–818. doi: 10.1002/1521 Tian L, Yoshihara Y, Mizuno T, Mori K, and Cahmberg CG. The Neuronal Glycoprotein Telencephalin Is a Cellular Ligand for the CD11 a/CDl8 Leukocyte Integrin. The Journal of Immunology, 1997, 158: 928-936. Wirenfeldt M, Dissing-Olesen L, Babcock AA, Nielsen M, Meldgaard M, Zimmer J, Azcoitia I, Leslie RGQ, Dagnaes-Hansen F, and Finsen B. Population Control of Resident and Immigrant Microglia by Mitosis and Apoptosis. (2007) The American Journal of Pathology, Vol. 171, No. 2. Xiang Z, Chen M, Ping J, Dunn P, Lv J, Jiao B, and Burnstock G. Microglial Morphology and Its Transformation After Challenge by Extracellular ATP In Vitro. (2006) Journal of Neuroscience Research 83:91–101 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 09 Jul, 2024 Submission checks completed at journal 08 Jul, 2024 First submitted to journal 03 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4682521","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324505804,"identity":"a2a6bb0c-47c4-44e4-bc3b-f7667db55383","order_by":0,"name":"Jesus Trejos","email":"data:image/png;base64,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","orcid":"","institution":"St. John's University","correspondingAuthor":true,"prefix":"","firstName":"Jesus","middleName":"","lastName":"Trejos","suffix":""},{"id":324505805,"identity":"c371a602-4005-4300-9439-6d61a424169d","order_by":1,"name":"Francis Schanne","email":"","orcid":"","institution":"St. John's University","correspondingAuthor":false,"prefix":"","firstName":"Francis","middleName":"","lastName":"Schanne","suffix":""}],"badges":[],"createdAt":"2024-07-03 20:11:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4682521/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4682521/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62140669,"identity":"ed515b4d-b96d-4a71-bb09-f0bd19f11eaa","added_by":"auto","created_at":"2024-08-09 17:06:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1591328,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1-A) Hypothesis of MG response to toxicant insult in experimental design and anticipated microglia morphology outcome. A regionalized toxicant exposure to the CA3 area of a hippocampal slice, grey circle, will result to a graded microglia morphological response (or morphological behavior) based on the extent of cell injury. MG nearest to the grey circle are depicted in M1 state, whereas MG furthest away are in M2 state, the MG in between these 2 extremes represents an intermediate morphology of MG. Surviving microglia near spot epicenter will be more M1 state, whereas microglia distal from spot (DG) epicenter will be more M2 state.\u003c/p\u003e\n\u003cp\u003e1- B, C) Typical MG IHC 10x field layout within cultured hippocampal consisted of 3 main visual landmarks, the track of dapi-stained nuclei that constitute CA3 (blue pixelated semicircle), a central core with increased red fluorescence staining (enclosed in yellow circle) and the space in between these 2 regions. This region is where the most clearly visualized MG (a sole MG is within small blue circles in figure 2a) are found due to minimal background, adequate spacing and preponderance of baseline MG this subregion within the hippocampal slice used to survey and conduct MG morphology analysis.\u003c/p\u003e\n\u003cp\u003e1- B, C) Typical MG IHC 10x field layout within cultured hippocampal consisted of 3 main visual landmarks, the track of dapi-stained nuclei that constitute CA3 (blue pixelated semicircle), a central core with increased red fluorescence staining (enclosed in yellow circle) and the space in between these 2 regions. This region is where the most clearly visualized MG (a sole MG is within small blue circles in figure 2a) are found due to minimal background, adequate spacing and preponderance of baseline MG this subregion within the hippocampal slice used to survey and conduct MG morphology analysis.\u003c/p\u003e\n\u003cp\u003e1-D) Typical MG layout through a 40x field area of analysis: MG have thin cell bodies that enclose the nucleus, thin processes also emanate out of the soma-nuclei structure. Also, MG are always covering a specific area and generally do not overlap with other MG.\u003c/p\u003e\n\u003cp\u003e1-E) Evidence of MG motility: After several days of culture cells begin to dissociate from tissue mass, several of these stained for CD11 underscoring MG motility as it starts to evacuate out.\u003c/p\u003e\n\u003cp\u003e1-F, G) Evidence of morphology changes: After immersion of slice into media (instead of resting on semiporous membrane) MG indiscriminately begin to take on ameboid shape consistent with M1, activated motif. In both treated and untreated slices resulted in same morphology pattern. This indicates that MG shape is sensitive to fluid turbidity and lack thereof attachment points.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/8cd3391c00a84adb343cbd44.png"},{"id":62140665,"identity":"6c28d48f-aa4e-4390-8b8b-e83959d2882c","added_by":"auto","created_at":"2024-08-09 17:06:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1350401,"visible":true,"origin":"","legend":"\u003cp\u003e*All cells from images in Figure 2 were tagged with an anti-CD11 antibody, captured under red channel; all nuclei in fields counterstained with Dapi, Blue channel\u003c/p\u003e\n\u003cp\u003e4- A, B) Low (10X) magnification visualization of CA3 spot: Hippocampal slice indicates areas of toxicity by an increase in the appearance of ameboid MG proximal and distal to the area of toxicant exposure, especially at the edge of where background staining is greatest (yellow circle) and there likely is most cells that are stressed, but viable.\u003c/p\u003e\n\u003cp\u003e4-C, D) High magnification of MG field near at border of treatment spot: Results in the appearance of MG mostly in their activated form (B). Compared to analogous area of the PBS-treated slice (A) and the untreated portions of the slice, activated MG consisted of thickened cell soma and dendrites, in addition to the shortening of MG’s dendritic processes.\u003c/p\u003e\n\u003cp\u003e4-E, F) Quantitative data from 40x fields: Results indicate that there is up to a 30%+ increase in MG activation at the evaluated areas. The quantitative data for activated MG is similar for mercury and cyanide/2-deoxy-glucose.\u003c/p\u003e\n\u003cp\u003e* Statistically significant from control (Students T-Test)\u003c/p\u003e\n\u003cp\u003e4-G) Dentate gyrus intra-slice negative control: To have a gradation of MG morphologies from injured to non-injured tissue, the dentate gyrus was evaluated as a heathy region of the slice that still contains MG predominantly in its baseline morphology and hence serves an intra-slice control.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/bdd180248f45fe7929132d72.png"},{"id":62140667,"identity":"f8c702ab-266e-4e76-9a1f-3a1f0cf3b582","added_by":"auto","created_at":"2024-08-09 17:06:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":750550,"visible":true,"origin":"","legend":"\u003cp\u003eMicroglia’s shapes in between baseline dendritic morphology and activated globular morphology. MG’s many forms indicate a progressive accretion of the cell membrane: Distance of cell membrane to nucleus’ wall increases. Also, there is a thickening and shortening of dendritic processes, which involute into the soma. Bar= 5 microns\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/7028874a51fbbdb50408b30e.png"},{"id":62140662,"identity":"e398a123-ed06-45e4-9943-41ef8aac49c3","added_by":"auto","created_at":"2024-08-09 17:06:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":422885,"visible":true,"origin":"","legend":"\u003cp\u003ea) Baseline MG soma consists of nucleus enveloped by a thin cell membrane that ranges from 1-1.5 microns thick (distance from nucleus membrane and cell membrane). Also, several dendritic processes (up to 9) emanate out of the soma, usually 1 micron in thickness during baseline state and extend out 20-25 microns from soma’s center.\u003c/p\u003e\n\u003cp\u003eb) Activated MG soma consists of nucleus enveloped by a thickened cell membrane that ranges from 2-6 microns thick (distance from nucleus membrane and cell membrane). Also, less dendritic processes emanate out of the soma, remaining dendrites are shorter and thickened to 3+ microns in thickness during MG’s activated state and do not extend out very far from soma’s center. Also, noteworthy that the most prominent dendrites are still present albeit as stumps, instead of branches. * Statistically significant from MG of control slices (Students T-Test)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/b7831905dfbcc47b4dfc5e02.png"},{"id":62140663,"identity":"a01a1930-0581-4e53-a59e-ec6d7f67e202","added_by":"auto","created_at":"2024-08-09 17:06:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":485498,"visible":true,"origin":"","legend":"\u003cp\u003eIn this representative image the region of activated MG within the yellow circle is the area that toxicity was induced within the tissue. Across 4 experiments these cells had a nucleus membrane and cell membrane average distance of 3.46 microns. Outside the circle is considered near the area of toxicity, which consists of a mix of baseline dendritic MG and activated MG yielded a distance of 2.4 microns. Hippocampus slice region distal to toxic injury, the dentate gyrus, had membrane distances that resembled control slices, CA3 and DG regions.\u003c/p\u003e\n\u003cp\u003e* Statistically significant from non-treated within slice near treatment area (Students T-Test); ** Statistically significant from distal areas within slice (DG)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/f9169c2a685ecb4932dd31e1.png"},{"id":62141082,"identity":"d03ae9a6-5108-46d0-926b-df6f17ba31ed","added_by":"auto","created_at":"2024-08-09 17:14:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":996604,"visible":true,"origin":"","legend":"\u003cp\u003e*All cells from images in Figure 6 were tagged with an anti-CD11 antibody, captured under red channel; all nuclei in fields counterstained with Dapi, Blue channel\u003c/p\u003e\n\u003cp\u003e5-A, B, C) Dendritic layout in baseline MG: A qualitative assessment of the size and thickness of the 6-10 dendrites that microglia present in dictates that major dendritic processes are part of the structural motif, an off-center lateral dendrite that culminates in a trifurcation, and 2 ends that split off the opposite end that bifurcate. Bar = 5 microns\u003c/p\u003e\n\u003cp\u003e5-D) Number of dendrites: An analysis of branching out of the soma indicates that MG can exhibit 6-10 dendritic processes. These processes can bifurcate into other branches at varying lengths.\u003c/p\u003e\n\u003cp\u003e5-E, F) MG nucleus: Nucleus shape and/or placement within the MG can also be differentiated to describe the cell’s activity. The microglia in captured within the yellow square (lower left corner) has a pinched nucleus which indicated that it is likely migrating through a narrow opening within the parenchyma. The microglia on the right has an elongated soma which postulates that the nucleus has ample room to move about that intracellular compartment.\u003c/p\u003e\n\u003cp\u003e5-G) Visualization of different types of structural variations within an injury region: Contextualizing microglia’s structural variations within a region of toxicity within a cultured hippocampal slice indicate that as you get further from the region of toxic injury microglia appear less activated. Since there is very minimal microglia migration (and thus these changes do not represent newly arrived MG mid metamorphosis) within the slice after 2 hours these morphologies are stable indicators of cell stress. Ergo they could be associated with different levels of cell injury as it relates to the viability of a parenchymal cell or the MG cell itself.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/f7eb87e3ce689b68d5c5f188.png"},{"id":62141083,"identity":"a5b1a5d1-e381-4764-ba23-e4b329898051","added_by":"auto","created_at":"2024-08-09 17:14:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":474854,"visible":true,"origin":"","legend":"\u003cp\u003eIn between the 2 known states of microglia M2 (baseline) and M1 (activated), 5 intermediate structural variations can be identified based on the shape of the soma, the contraction of the dendrites and the cells’ overall size. Structural variations greater than 3 indicate that microglia ceases being a fine stellate form and is becoming a dense cellular particle. Bar = 5 microns\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/83bf2ecfd77b17f20522eead.png"},{"id":62141409,"identity":"7f0c0cef-91a6-4271-9e6e-1bd5dc606b96","added_by":"auto","created_at":"2024-08-09 17:22:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":623938,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4682521/v1/d28c1cb0-86ea-492c-a71a-9d6169fcc522.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEvaluation of 5 Intermediate Microglia’s Structural Variations Within an Organotypic Hippocampal Slice Model After Regionalized Toxic Injury \u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMicroglia (MG) are the surveillance and maintenance immune cells of the central nervous system; and are also known as a type of dendritic cell. Their baseline dendritic morphology covers a large area of interstitial space and probes the highly exclusive compartment of the of the central nervous system (Li et al., 2018; Ginhoux et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, Herculano-Houzel et al., 2018, Wirenfeldt et al. 2011, DiSabato et al., 2016). However, MG\u0026rsquo;s dendritic shape can drastically change in response to cell stress to a starkly different and compact and globular morphology. Therefore, this indicates they can take on several roles that are related to their different morphological states (Tang et al., 2015); namely its M1 state (activated, globular shape) and its M2 state (inactivated, dendritic shape). Importantly, MG monitor an interstitium that is considered one the purest ultrafiltrates in the body as it surveys tissue for damaged, dying, or dead cells. As such microglia\u0026rsquo;s sensitivity to the CNS environment allows prompt reaction to homeostatic perturbations within the CNS tissue matrix through 3 main characteristics; they are small, highly amorphous, and they are also motile. In addition to its janitorial duties, microglia are implicated in the pruning of synaptic connections that are important for neuronal networking (Paolicelli et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Contemporaneously, much investigation has gone into some of portions of MG\u0026rsquo;s morphological characteristics; aspects such as size, area, branching, hull ratio, podocyte status has been considered (Fern\u0026aacute;ndez-Arjona et al., Filipo et al., 2019; Kamphuis et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Minami et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Also, some details of gene expression, mRNA profiling and single cell assessments have also been conducted to better understand their genetics (Keren- Shaul et al., 2017). However, more detailed information on MG\u0026rsquo;s individual and overall structural components is warranted to further characterize MGs dynamic morphology and potentially understand events antecedent to CNS cell death (loss of cell membrane integrity) modeled by toxic injury. This isolated tissue injury model can be harnessed to better establish intermediate microglial morphological states which could inform about its roles in homeostasis and disease within the isolated CNS\u0026rsquo; post BBB compartment (Prinbz, et al, 2019; Li, et al 2018). Using MG\u0026rsquo;s holistic morphology as an endpoint can add greater resolution as to how this cell behaves during injury within the CNS which could be harnessed as a form of proxy determining adequacy for post BBB homeostasis.\u003c/p\u003e\u003cp\u003eThe differential shapes and sizes of microglia have been previously characterized in cell culture MG when the full range of morphology was evaluated 2 hours after ATP exposure (Xiang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), which is a significant instigator of MG activation. Thus, the morphological profile is understood as isolated MG cells. However, the morphological profile of MG has not yet been thoroughly evaluated when embedded within cultured tissue. Therefore, a contextual way to evaluate the MG response is to utilize a model that represents not only the dendritic cell but its nascent cytostructural milieu, its adjoining tissue matrix. In addition, it would be best to hone in on the responses and signaling directly related to MG and CNS tissue matrix by isolating these responses from significant blood-derived immune cells replenishment and signaling outside the brain \u003cem\u003ein-vivo\u003c/em\u003e and, conversely, more contextually than MG in isolated cell culture suspensions.\u003c/p\u003e\u003cp\u003eThe evaluation of MG was predicated on using one of its signature membrane proteins to determine its morphology, CD11. This protein is an important component of MG\u0026rsquo;s migratory capacity and therefore relates to one of its defining activity\u0026rsquo;s functions (Meerschaert, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1995\u003c/span\u003e, Jurga et al., 2020). Furthermore, considering that CD11 is a membrane protein expressed on the extracellular surface of MG, a more detailed and representative depiction of its dynamic morphology could be appraised more so than an intracellular protein, such as Iba-1. Based on the immunohistochemical CD11 detection, the MG evaluated in this study has a morphology consistent with the dendritic motif and thereby under the purview of dendritic cell, that is a cell with dendritic processes (Gallizioli et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xiang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Kamphuis et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e,) that migrates through the post BBB parenchyma.\u003c/p\u003e\u003cp\u003eThis study\u0026rsquo;s aim is to investigate how microglia have a definable gradient morphological response to regionalized biochemically verified toxic cell injury and/or CNS cell death (2 hours after inducing a toxic insult) in the context of an \u003cem\u003eex-vivo\u003c/em\u003e model, the organotypic hippocampal slice. Furthermore, the untreated area of the hippocampal slice can serve as an internal control to compare baseline MG near non-injured cells within tissue response to activated MG near injured/dead cells within tissue, and the intermediate morphologies in between. Nonetheless, within this response there\u0026rsquo;s focus on the morphological aspects such as MG cell body, dendrites, and nucleus placement, independently and holistically as metamorphosis occurs. These details can be potentially used to define intermediate forms of MG as it relates to different levels of CNS cells\u0026rsquo; stress. As such, these different morphologies between M1 and M2 (Tang et al., 2015) can be designated to define the microglia\u0026rsquo;s \u0026ldquo;morphological behavior\u0026rdquo; which could be an important aspect of MG\u0026rsquo;s characterization as is found in and around injured tissue. Besides contextually displaying MG\u0026rsquo;s morphological information, this paradigm also concurrently isolates immune cell-parenchymal cell dynamics under the influence of cell stress with multiple controls. This gradation is the first time it has been characterized in an \u003cem\u003eex-vivo\u003c/em\u003e tissue model, not only does it confirm many of the known aspects of MG studied \u003cem\u003ein-vivo\u003c/em\u003e and \u003cem\u003ein-vitro\u003c/em\u003e, but also it allows visualization of MG\u0026rsquo;s inherent properties such as its sensitivity to fluid turbidity and motility. Overall, all this study will define in in-depth morphological detail, qualitative and quantitative aspects of MG\u0026rsquo;s metamorphosis from baseline (M2) to its activated state (M1) propagated by chemical toxicity within an isolated tissue context.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e \u003cb\u003eOrganotypic hippocampal slices\u003c/b\u003e \u003c/p\u003e \u003cp\u003e Animal work in this study was performed under a IACUC (Institutional Animal Care and Use Committee) approved protocol in a facility accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. This facility also follows The Guide for the Care and Use of Animals, AVMA Guidelines on Euthanasia, PHS Policy on Humane Care and Use of Lab Animals, and USDA Animal Welfare Act regulations. All Sprague-Dawley rats were provided ad lib food; temperatures and humidity kept within recommended ranges; 12-hour light/dark cycles were maintained. Neonates were obtained from in-house IACUC- approved breeding protocol with breeder males and dams obtained from Taconic Farms.\u003c/p\u003e \u003cp\u003eThe best visualization of microglia (CD11\u0026thinsp;+\u0026thinsp;cells) is in the neonate rat 10\u0026ndash;21 day old (usually 1 neonate male or female per experiment), due to the relative translucency of the tissue matrix. Older animals have more opaque tissue and therefore CD11\u0026thinsp;+\u0026thinsp;cells cannot be visualized in fine detail beyond 10x magnification. Animals were sacrificed via decapitation and brain was immediately excised from cranium, the whole hippocampi were carefully dissected out and placed in ice cold calcium and magnesium free Hanks balanced salt solution. Hippocampi were then placed on top of a 1.5% agar (Acros Organics Cat#: 400402500) block to slice tissue in a sagittal orientation at a thickness of 200 microns using a Syskiyou Tissue Slicer (Cat#: SKU 14240000E). Slices are then manually separated out individually by using a micro spatula immersed in ice cold calcium and magnesium free Hanks balanced salt solution. One rat (2 hippocampi) can yield 26\u0026ndash;40 hippocampal slices.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTissue incubation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eUsing a trimmed transfer pipette slices were removed from ice cold media and placed into Millipore filter (Cat#: PICM0RG50) within a well of a 6-well plate with preincubated culture media as described in previous papers (Marush, 2016; Stoppini et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1991\u003c/span\u003e); this media consists of 50% Minimum Essential Media (MEM), 25% Hanks Balanced Salt Solution (with calcium and magnesium) and 25% Horse serum. Excess calcium free and magnesium free media on the top of the filter should be removed prior to equilibration. Before any treatment with toxicants, the tissue was equilibrated in a cell culture incubator for 1 hour.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMicroglia Visualization\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAfter isolation and/or treatments hippocampal slices were placed in 4% paraformaldehyde in PBS for 15 minutes. Then slices were blocked with 10% FBS in PBS for 30 minutes. Primary Anti-CD11 Antibody (mouse anti-rat mAb Cat#: MA-9u29) was added to slice with 1.5% FBS and 1.5% goat serum for 1 hr under slight shaking. Secondary Ab conjugated with phycoerythrin (goat anti-mouse Cat #: Fb106) was added to slices with 1.5% FBS and 1.5% goat serum for 30\u0026ndash;60 minutes. Slices were visualized from directly semiporous filter top appraise morphology. Slice could also be visualized after being placed into a glass slide and mounting media (Cat #: P36983 -) and gently capped with cover slip. An EVOS fluorescence microscope (Cat#: AMF7000) was utilized to capture all MG imagery after mounting media sets, preferably on the same day. Images were surveyed for CD11 cells (in between the central portion of slice and the CA3 or DG row of cells) and their morphological categorization; baseline shaped (stellate with fine processes) or activated (enlarged cell body with thickened processes). Greater than 3 activated MG adjacent to each other are rarely observed in baseline untreated slices and therefore when this was observed they were indicative of site of toxicant-related injury.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eMG within the cultured 200-micron hippocampal slice tagged with an anti CD11 antibody demonstrated the same morphological featured reported in other \u003cem\u003ein-vivo\u003c/em\u003e and \u003cem\u003ein-vitro\u003c/em\u003e investigations (Fern\u0026aacute;ndez-Arjona et al., Filipo et al., 2019; Kamphuis et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Minami et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Lana et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Microglia are henceforth defined visually as CD11\u0026thinsp;+\u0026thinsp;continuous red staining enveloping a blue DAPI-stained nucleus. Baseline MG were similar whether slice was evaluated immediately after isolation or after a 2-hour incubation, indicating stability of baseline MG 2 hours after excision. Within the confines of the hippocampal tissue slice MG were ubiquitously observed throughout, they consist of a significant portion of the overall cell population, and they were evenly distributed (Figs. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-b, c, d). Within the isolated tissue context MG demonstrate a homogeneous distribution and they seldom overlap. The central portion of the hippocampal slice (yellow circle in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) contains slightly more condensed microglia staining, it is also worth noting that there were more activated ameboid-shaped MG present within this central region. After surveying MG beyond the central portion (yellow circle in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-B, C) reveals that they have more spacing in between them and there are 5\u0026ndash;7 cell rows of MG out before reaching the CA3 track of nuclei. The density of nuclei of the CA3 track interfere with clear MG visualization, and thus optimal region of MG morphological evaluation is the region in between the central MG-dense portion and the CA3 track (Where MG were circled with blue circles Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-b). Therefore, after an appraisal of MG\u0026rsquo;s distribution and appearance throughout the hippocampal slice, MG\u0026rsquo;s morphology can be most effectively evaluated within the proposed tissue context in between the CA3 region and the central portion (yellow circle in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-B, C).\u003c/p\u003e\n\u003cp\u003eIn conditions where the hippocampal slice was immersed in media, instead of resting on a semiporous membrane (as historically used in electrophysiology experiments), several MG cells exhibited a highly ameboid shape (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-F, G), insofar as suggesting that the lack of stability brought about the fluid destabilizes the cell body and thus MG lose its fine structured dendritic motif. The stark change in morphology is consistent with the notion that this cell can readily be prompted to change shape from its originally observed fine-processed structured motif. Also, this suggests that a MGs baseline state (and ergo shape) is predicated upon attachment points (Tian et al., \u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e) within the tissue. Therefore, MG can be prompted to change shape within the hippocampus slice.\u003c/p\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacterization of activated microglia within the context of biochemically confirmed precise toxic cellular injury\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eExamining the microglia response within the hippocampal slice using biochemically verified toxic doses resulted in stark morphological changes to MG. Upon toxicant exposure within a specific region of slice (on CA3 side) a crater forms and at high doses it is characterized by an intense core of nonspecific red fluorophore staining with a rim of activated microglia (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-A, B). Activated MG exhibit more intense fluorophore intense staining, have shorter and thicker dendritic processes and have enlarged cell bodies around their nucleus that make them easier to visualize in the magnification plane than when they are in their baseline state (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-C, D). The dentate gyrus region was not treated with toxicant and thus baseline MG remained in its non-activated fine-processed structured motif with a small cell body around the nucleus (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-G). Cell counting analysis on all the MG in 40x images indicated that not all MG become activated with greater distance you get from the site of injury the less activated the MG (Graphs on Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-E and -F). Areas of tissue injury were characterized by the appearance of different MG morphologies that were different from its baseline shape. The spot-tox demonstrated a gradation of MG profile related to injury distance. The closer the MG were to the area of injury, the more activated and condensed they appeared. Therefore, MG can exhibit morphologies that indicate it is in its activated state (M1, ameboid) after being treated with biochemically verified toxic doses of mercury and cyanide in combination with 2-deoxy-glucose.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cstrong\u003eMicroglia\u0026rsquo;s different shapes and sizes from injured to non-injured tissue.\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eAfter surveying the IHC (labelled for CD11) slice for MG in treated slices, MG changes in shape were observed near and around the area of toxicant exposure (spot-tox). Areas distant (dentate gyrus Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-F) from spot-tox site exhibited mostly MG that resembled baseline shapes and were corroborated with control slices; that is, with fine dendrites and stellate form with a small cell body. In between these two regions there was a variety of shapes noted mostly in changes in overall shape and size. The size of a baseline shaped MG distal to the injury site is 30\u0026ndash;40 microns and mostly exhibits fine-stellate processes that were 1 micron thick. MG near the nearest surviving area of the spot tox were much more condensed, globular and smaller in size (10\u0026ndash;15 microns), however in certain instances stellate MG were also noted but with thicker processes of 7\u0026ndash;9 microns thick. The MG in between these 2 shapes may represent a gradation of activation that is being predicated by differential toxicant concentration from the core of the placement of the 180 nL aliquot. Whereas the toxicant concentrations were highest at the central site where the 180nL drop landed on the tissue, the surrounding areas were diluted with the media already within the slice tissue matrix and thus the portions further from that area represent places where toxicant concentration was decreased. This is corroborated in the MTT studies (Trejos et al., In preparation), where a gradation in the shade of formazan blue was decreased, but PI was still being excluded; indicating areas of injured but still viable cells (defined as cells with membranes still excluding PI) toxicant concentrations. In these sublethal regions, MG were more mixed in morphology and varied between shapes that resembled baseline fine dendritic stellate motif, stellate with thicker dendrites and ameboid with little to no dendritic processes (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Another way to consider the changes of MG from injured to healthy tissue is the rearrangement of its cell membrane; insofar as there is an appreciable accretion of the membrane (and hence IHC CD11\u0026thinsp;+\u0026thinsp;mediated staining) that thickened as it becomes more activated, and importantly, it becomes a denser cellular particle; this shape is contrary to a delicate fine structured web of stellate branching emanating from a small cell body when MG is in its baseline state. Ergo upon surveying these MG, the progression from baseline stellate structure in uninjured tissue to that of an activated ameboid around most injured viable tissue one may correspond a measurable change to the membrane, which accretes and thickens around the nucleus based on the severity of injury.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantifying microglia\u0026rsquo;s structural aspects in different morphological states\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline microglia compared with activated MG results (after 12 mM Hg injury) in the elucidation of quantifiable structural data as it pertains to its cell body/soma and rearrangement of cell membrane. As previously mentioned, baseline MG\u0026rsquo;s shape characteristics relates to not just size of the entire cell, but the presentation of its membrane\u0026rsquo;s distribution. The membrane encapsulates the nucleus and emanates from this centrality via the protrusion of fine filaments that are typically no wider than 1 micron thick; taken together, resembles the shape of a star and hence stellate in appearance (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e-A). The opposite extreme of MG\u0026rsquo;s membrane distribution is the ameboid shape of MG that is the morphologically characterizes it as this it being in its activated form (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e-P). In this opposite motif, the membrane also encapsulates the nucleus, however two main distinctions are obvious; that is that most, if not all, processes are no longer present (and those that remain are shorter), and the cell body that surrounds the nucleus is much thicker and stains more intensely. The stark changes in cell body can be quantified by measuring the greatest lateral distance (after an initial polarization of MG\u0026rsquo;s soma) of the cell membrane to that of the nucleus\u0026rsquo; membrane within an individual MG. During surveying of control slices MG\u0026rsquo;s baseline state this distance is typically 0.8\u0026ndash;1.5 micron thick, as demonstrated in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e-A. During surveying of spot-tox treated slices MG\u0026rsquo;s opposite activated state this distance is greater than 3 microns as demonstrated in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e-B. This structural demarcation was compared in the spot-tox injury model\u0026rsquo;s 20x images, and upon comparisons of different MG\u0026rsquo;s within, statistically significant (student t-test) quantitative changes in distance between the nucleus membrane and cell membrane resulted. When all the MG in the control slices were compared to all the MG in spot-tox treated slices a statistically significant change were observed; control slice MGs had distance from nucleus to cell membrane was 1.49 microns, while treated slices had distances of 2.93 microns (Graph on Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Within Hg-treated slices that had activated MG around the injury area of spot-tox were compared to MG in regions proximal (non-treated area) and distal (DG area) to injury and thus within healthy portions of the tissue and statistically significant quantitative changes in structure were also found. A spot\u0026rsquo;s borders were set by the appearance of 2\u0026ndash;3 MG next to each other within the region between center of slice and the CA3 track of nuclei. These MG has a nucleus to cell membrane distance of 3.46 microns (Graph on Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Any other MG outside this border in between the CA3 nuclei track and the center of the slice was considered a proximal non-treated area; this area had average distance of 2.40 (Graph on Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). To ensure that the slice had enough baseline MG present, the dentate gyrus region was evaluated as a healthier portion of the slice that was distal to the spot-tox; these MG have a distance that was similar to control slices at 1.56 microns Graph on Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Therefore, MG structural changes can be quantified by measuring the distance of the nucleus membrane to that of the cell membrane.\u003c/p\u003e\n\u003cp\u003eThis quantitative data is indicative of the amount of cell membrane rearrangement that occurs when a MG goes from one extreme state (baseline) to the other (activated). Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e exemplifies many of the different shapes and forms captured in between the baseline form of MG and the activated form of MG. Within his study, there are intermediate forms of MG that were also captured; this metamorphosis indicates that as the MG gets activated and accretion of the cell membrane occurs, and thus the area that the cell membrane spreads throughout shrinks and the fine filaments (characteristic of the baseline state) thicken as they shorten into the cell body. Also, there is a polarity of the MG soma that is exhibited as it accretes more intensely at polar opposite ends of the cell body, which is indicative of a pattern of membrane compression. This significant rearrangement of cell mass is an important consideration to bear in mind within the context of the tissue matrix; this will be elaborated upon in a follow up manuscript that endeavors on describing intercellular spacing within this tissue (Trejos, 2023 in preparation).\u003c/p\u003e\n\u003cp\u003eAnother important consideration with regards to the changes in membrane rearrangement that MG undergo is the location of the nucleus within the enlarged cell body (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e-E, F). Since MG generally have an asymmetric layout the placement of the nucleus can be an important consideration as it can serve as a point of morphological distinction. This is mostly appreciable when MG cell body is greater than 10 microns in length, which is twice the size of its nucleus\u0026rsquo; diameter (consistently measured at 5 microns in this study). At baseline although the nucleus is clearly present there is very minimal cell body present to appraise the nucleus\u0026rsquo; placement within. However, when the cell body is big enough, the placement of the nucleus can be categorized as central, or it can be located closer to one of the extremities of the elongated/enlarged cell body.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn between baseline and activated morphologies MG exhibit many characteristics and different forms.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne of the most important visual characteristics of baseline MG is the preponderance of dendritic branching (1 micron in thickness) emanating from a small cell body that contains the nucleus. Notably, that MG cell bodies are somewhat more difficult to see when they are in their baseline morphology as they are not only thinly dispersed, but they are also well-ensconced within the tissue matrix and hence visually blocked within the image fields (40x). At the other extreme, MG have very little to no branching and it is very globular in shape and very stark in appearance; activated MG morphologies are more readily visible than the baseline MG morphologies. In between these 2 extremes, other morphologies were observed (Fig.\u0026nbsp;\u0026lt;link rid=\u0026quot;fig3\u0026quot;\u0026gt;\u003cspan class=\"InternalRef\"\u003e3\u0026lt;/link\u0026gt;\u003c/span\u003e-A and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e-P), which are likely intermediate shapes that represent the membrane rearrangement described in the previous section. Also, it is important to note that these intermediate MG morphologies are present 2 hours after initial injury. As baseline MG accretes, the cell body in and around the nucleus begins to gain form in a polar manner; that is, the membrane is closing in from 2 opposing ends. Concurrent to this cell body rearrangement, the dendritic processes become shorter and thicken to greater than 1 micron. This thickening helps improve the resolution of MG\u0026rsquo;s seemingly amorphous cell body appearance as it gives the cell body and dendrites more structural definition, which assists in the delineation of structural landmark dendritic protrusions as they thicken as the membrane is rearranging into the cell soma. The plasmalemma from distal dendrites involute towards the nucleus which is considered a central position of this cell\u0026rsquo;s baseline layout. A simplified perspective, from a cell structural standpoint, this metamorphosis is a complete redistribution of MG\u0026rsquo;s plasmalemma. Membrane that was once 20\u0026thinsp;+\u0026thinsp;microns away from the nucleus is now proximal to the nucleus and yielding a more prominent dense cellular particle with its plasmalemma concentrated in and around the nucleus. Therefore, within this controlled tissue sample matrix different iterations of CD11\u0026thinsp;+\u0026thinsp;MG\u0026rsquo;s morphology and details of its structural constituents (soma, nucleus, dendrites) are visualized.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVisualizing the number of microglia\u0026rsquo;s processes/dendrites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA range of 6\u0026ndash;10 dendritic processes were usually counted in an assessment of 26 baseline-shaped MG cells (in 16 different 40 x images across different experiments); the dendritic counts were corroborated with several other published studies (Ugloni et al., 2018; Fern\u0026aacute;ndez-Arjona et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Masuch et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) that looked at MG morphology and thereby displayed detailed MG images (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e-A-D). A dendrite was characterized as a track of red fluorescence (CD11-labelling) emanating out of MG\u0026rsquo;s main cell body\u0026rsquo;s membrane in a perpendicular trajectory. There are several presentations of how dendrites protrude out to resemble distinct motifs. A common MG motif is where one end has a major off-center dendrite that bifurcates into 2 large branches, the other major dendrite, seemingly a tail, that emanates directly from the soma end that spits into 2 tapering ends, similar to a maimed lobster (guide bars run parallel to dendrites in pictures of Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e- A, B, C). Usually two of these three major (thicker) branches have 2\u0026ndash;3 major sub-branches that keep bifurcating out to other smaller branches when MG is in a baseline (M2) state. The other 3\u0026ndash;6 branches are not as thick and long but can also bifurcate out to create smaller dendritic processes (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e-A, B, C). Taken together, MG in its baseline M2 state presents with several dendritic processes that can be quantitated to a number of 6\u0026ndash;10 in any given individual MG cell.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eMicroglia cells have a unique position in the immune response in the post BBB interstitium as they are usually the first motile responders during perturbations within the extracellular biological matrix. This cell is mobile and highly amorphous and as such its characteristics can potentially be visually read by evaluating its shape and the sum of its three main structural components: the soma, the nucleus, and the dendrites. Much investigation has gone into studying its behavior and signaling during activation (Fern\u0026aacute;ndez-Arjona et al., Filipo et al., 2019; Kamphuis et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Minami et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e), this is the first reported evaluation within a cultured organotypic tissue model that activated a subset of MG within the tissue model with a toxic injury but left the rest of the MG in its inactivated baseline state. Thus, one of the enticing aspects of observing MG embedded within a viable tissue matrix is observing MG response events in-situ; by modifying (via toxicity) the immediate interstitium amid a viable biologically active sample (as demonstrated in electrophysiology studies). Also important to note that maintains the microscopic structural layout of a mammalian brain is preserve in this tissue slice. The benefit of this condition is that it allows for evaluation of a spectrum of MG morphological changes that occur from being in a baseline state to that of being fully activated within the tissue context However, prior to delving into these deep queries on how MG (and CNS cells) ascribes a genetic commitment that leads to stress related biochemical, proteomic changes, a reproducible cellular response must first be ascertained, in this study such cellular response is morphology and thus how MG cell rearranges its cell membrane. Such is that this investigation into microglia\u0026rsquo;s morphology after precise toxic insult elucidates a nuanced cellular response, and in turn also revealed many details of MGs\u0026rsquo; morphological behavior within its nascent CNS surroundings.\u003c/p\u003e\n\u003cp\u003eThe first two characteristics, nucleus and cell body of the MG are intimately related as they are both stark visual landmarks whether MG is in its baseline state or its activated state. Albeit there are appreciable changes in size of MG when activated versus in baseline, the most consistent quantifiable change is the space between the nucleus membrane and the cell membrane, as mentioned in Graphs in figured 7 and 8. This is an important marker not just of size, but more so the rearrangement of MGs cell membrane borders. The amorphous nature of MG is one of its important characteristics and these stark changes to cell structure enable functions as it relates to MG\u0026rsquo;s baseline state or activated state. Thus, when MG is in its baseline state the cell membrane\u0026rsquo;s distance (the wider of the lateral 2 distances) from the nucleus is around 1 micron thick, thus it is presupposed that the rest of the membrane is thinly spread out covering a designated surface area as it conducts its baseline activities. Conversely when MG is activated the nucleus\u0026rsquo; membrane distance from cell membrane is greater than 3 microns on average (up to 6 microns individually), which is a substantial change. This quantitative change can serve as an indicator of level of activation of MG. As such this distance can serve as a point of distinction by characterizing intermediate forms of MG, along with other ancillary visual characteristics: dendrites size, shape and nucleus placement. Irrespective of the two distinct mechanisms of cell death and injury, MG morphologically behaved in the same way at least in this rudimentary qualitative assessment of MG shape. These 2 models of toxicological insult (mercury and cyanide combined with 2-deoxy-glucose) leveraged the knowledge of toxicological agents\u0026rsquo; mechanism of toxicity to induce a cellular response, activating MG from an M2 to an M1 state.\u003c/p\u003e\n\u003cp\u003eUnderstanding the meaning/functionality MG dendrites is paramount in the understating of MG\u0026rsquo;s inherent biology and response to toxic insult. One of the most defining characteristics of MG is the presentation of their dendrites (Ugloni et al., 2018; Fern\u0026aacute;ndez-Arjona et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Masuch et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). As described in the results, there are usually 3 major dendrites and one of them bifurcates into 2\u0026ndash;3 branches of similar width, which resembles a claw. This dendrite is usually off center and therefore lateral, which indicates that these cells are asymmetrical. This asymmetry can be useful in determining the orientation of the cell and thus have a greater appreciation of its layout within the tissue matrix. Furthermore, the other dendrites serve some sort of functional weight, potentially distinguishing the functions of all these variety of dendrites and providing important information about these morphological behaviors. These behaviors can offer information about how these dendrites are protruding and assist in several different functions, for example: the adhesion or anchoring to the extracellular matrix, reach out to neighboring MG to maintain adequate spacing (since they seldomly overlap), probe the extracellular fluid (for either signaling or indications of cell damage), or directly probe neurons, astrocytes (and other CNS cells), cellular address probes, etc. and other undiscovered functions. Conversely these dendrites involute during MG\u0026rsquo;s most activated states, however often dendritic stumps remain, what role do these dendritic remnants emanating from the ameboid MG cell body play when MG is conducting its activation duties? Taken together, the nature of the MG cell is one that is highly animated and has several different opportunities for scientific endeavors on how these cells can serve as biomarkers of extracellular adequacy.\u003c/p\u003e\n\u003cp\u003eThe morphological plasticity of MG is intrinsically connected to its response to toxic injury. The main tenet of this study was to examine a controlled signal to noise of MG according to its morphology presentation within a sample that had simultaneously healthy and injured tissue, such is why the toxicity was localized to only injure a portion of the hippocampus tissue sample.\u003c/p\u003e\n\u003cp\u003ePrints et al., (2019) describe that establishing microglial states can be essential to their roles in homeostasis and disease, such example was postulated as the disease associated MG (DAM) that was genetically characterized by (Keren- Shaul et al., 2017). This study ascribes the morphological state as a determinant of its behavior, ergo \u0026ldquo;morphological behavior\u0026rdquo;. Morphological behavior alludes to the benefit of a cell\u0026rsquo;s structure to a role it is executing in response to its surroundings. Structure is an important demarcation of cellular activity because of the cells biochemical, metabolic, proteomic, genetic, and adaptive commitment of maintaining a specific macro shape. Many of the descriptions of baseline microglia in the literature default this structural motif to that of it being in a state of \u0026ldquo;sensing\u0026rdquo; the extracellular environment. Taking into account the known roles of MG it is understood that this state is within its purview of its characteristic activities, a sentinel of extracellular medium\u0026rsquo;s adequacy. In a baseline state they are spread out evenly throughout the hippocampus tissue matrix and seldom overlap; this fine stellate form is suggestive of a behavior such as sensing and probing the interstitium\u0026rsquo; s integrity as well as the somatic cells they mount as they migrate through an extracellular region. Baseline MG size ranges from 30 to 40 microns, and the filaments that emanate from the cell body that is just 1 micron thicker than the nucleus compartment, and the filaments themselves are barely thicker than a micron in width. This is logical considering the generally accepted phenotypic job description of dendritic cells, it is virtually a cellular detector of extracellular conditions. Upon its activation, MG changes into a much different shape and therefore it is no longer optimized for detection, it metamorphizes into a compact globular circular shape in its most extreme form of activation. The activated shape is likely more amenable for endocytosis of cellular debris that occurs during injury, accelerated motility and/or cordoning off a space withing the interstitium as this enlarged shape decreases the space available through micro-openings in the interstitium from which motile cells lay their trails. Spatial obstruction by activated MG could decrease the flow of non-optimal extracellular fluid contaminated with potentially harmful intracellular contents from cells with compromised membranes.\u003c/p\u003e\n\u003cp\u003eTable 1- Structural details about microglia\u0026apos;s 5 different Structural Variation s between its baseline morphology (M2 state) and activated morphology \u0026nbsp;(M1 state)\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"840\" height=\"386\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eIt is also important to note that MG activation does not seem to be a binary outcome, that is, there are other intermediate forms that can arise and participate in the recovery or pathologic process. The most compelling piece of evidence of this is simply the appearance of these intermediate forms near regions of cellular stress. This region is found right outside the most central part of the spot, where all cells are presumed dead (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e- B). Further, these changes can be characterized by membrane rearrangement, the appearance and morphologies of dendrites and nucleus placement within the MG. Had MG morphology been a binary outcome only baseline and activated forms would have been found in these areas. Therefore, considering that MG activation fall into some sort of spectrum, these forms can signify the state of the immediate matrix they are surrounded by, and thus have a better understanding of the initial stages of cellular perturbation as recognized by this primary sentinel immune cell\u0026rsquo;s morphological presentation.\u003c/p\u003e\n\u003cp\u003eAs described in the \u003cspan class=\"InternalRef\"\u003eresults\u003c/span\u003e section (Graphs on Figs. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e) one of the most quantitative ways to assign this morphological spectrum is to measure the distance of the nucleus membrane to the cell membrane as that underlines the extensive amount of membrane rearrangement MG undergo that happened after the cell polarizes. In between these 2 extremes 5 different morphologies were identified using cues from the size and shape of the soma and dendrites as well as the overall length of MG (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eT). These are postulated to be stable morphologies since they are present even 2 hours after the initial toxicological insult and since there is no migration of MG observed these are not interloper MG cells that migrated from other region (or from nearby blood vessel). Had there been migration it could have been postulated that these were migrant MG from other areas that were just arriving at the sites of injury and thus in the middle of the M2 to M1 metamorphosis. Therefore, these intermediate morphologies can be ascribed to roles that have not yet been elucidated.\u003c/p\u003e\n\u003cp\u003eCollating the visual empirical data gathered in this study together, that is MG overall size, shape/size of soma and appearance of dendrites a pattern of other morphological behavior intermediates emerges. Namely 5 different intermediate structural variations become apparent (Table\u0026nbsp;9T). These qualitative categorizations are subjected to the appearance of the soma, nucleus, and dendrites in a 2-dimentional plane that captures all three. The 2 extremes of morphological behavior are M1 (activated MG) and M2 (baseline MG); the former is a dense cellular particle that is globular and has no dendritic processes, the latter is the appearance of a nucleus enveloped by a thin cell body with several thin dendrites emanating out of it. Since based on the quantitative assessment, the membrane of the soma gains greater distance from the membrane of the nucleus, a qualitative assessment as to the orientation of the membrane is applied; that is, when and where this separation starts to happen. Also, how this qualitative characterization change in membranes\u0026rsquo; distance relates to the thickness and length of the dendrites is appraised. In between the two extremes five morphological states are described:\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMorphological behavior 1\u003c/span\u003e- The first indication of morphological changes after the baselines state is the widening of the soma as the space between the nucleus membrane and the cell membrane start to gain some distance, this distance improves the visualization of MG as membrane stain is more intense.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMorphological behavior 2\u003c/span\u003e- Is demarcated after the first separation of the nucleus and cell membranes, the soma begins to polarize, that is, the slightly thicker membrane begins to accrete at opposite ends which results in an uneven encirclement of the nucleus which renders the soma more oval than circular in shape, in addition the soma is elongated to the point that the nucleus can be regionalized within, usually there is 10 microns (or 2 nucleus lengths) between the 2 polar ends of the soma. After the polarization/elongation the soma begins to widen and the measurement of the lateral distance of the soma\u0026rsquo;s membrane to the nucleus\u0026rsquo; membrane could be objectively measured (as was demonstrated in Graphs in Figs. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMorphological behavior 3\u003c/span\u003e- Is the further elongation of the soma to the point that it reaches 3 nucleus lengths, but its width starts to be greater than 7\u0026ndash;8 microns wide and thereby lateral separation from nucleus membrane begins; another very important distinction is the widening and shortening of the dendrites. An important structural consideration to morphological behavior 3 is that the accretion of soma is beginning to yield a denser cellular particle, which means it is becoming a more obstructive presence within the space it occupies, an important spatial consideration. The immediate consequence of this size and shape change is the alteration of interstitial fluid flow and the passage of motile cells.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMorphological behavior 4\u003c/span\u003e- After max elongation is reached (usually 15\u0026ndash;20 microns) presents as a highly visible MG that has a much bigger and thickened soma but still stellate as all the dendrites are also thickened. Notably its dendrites are shortening into the soma, also, the nucleus membrane will gain greater distance from the cell membrane.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMorphological behavior 5\u003c/span\u003e- the last step before full activation, the soma is even more globular, rotund, but most notably there are fewer dendrites and the ones left over appear as stumps, compared to how they looked previously. This metamorphosis does appear to bear some impact on the conditions of the unique interstitium of the CNS, namely in the redistribution of the area of this cell\u0026rsquo;s soma and the impact of this on the availability of interstitial space, which will be discussed at greater length in an upcoming manuscript (Trejos, in preparation).\u003c/p\u003e\n\u003cp\u003eTaken together, breaking apart the main characteristics of MG (soma, dendrites, nucleus) their intermediate forms suggest that they could be objectively discerned as having distinct visually definable morphological behaviors; this is important because they can be associated with states of cellular stress prior to cell death as many of these intermediate shapes appear within the injury region of the spot tox adjacent to the epicenter.\u003c/p\u003e\n\u003cp\u003eFurthermore, and importantly although the measurements in this research were done manually (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e), this quantification can illustrate a great potential image analysis tool to evaluate the relative activation of MG in and around injured tissue. This can be potentially applied to AI program algorithms that can detect and evaluate MG in greater detail, so long as the setting can be programmed to detect and discern the nuclear membrane to that of the cell membrane; the relative distance between these 2 walls can be easily measured.\u003c/p\u003e\n\u003cp\u003eMicroglia characterization within the tissue suggest a cell that undergoes dynamic change and structurally acquiesces to its extracellular environment, likely why MG evacuating the tissue matrix exhibit differences from MG embedded within tissue (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e-F, G). Utilizing this morphological behavior criterion can inform the relative response of a MG with regards to its response to a cellular event that indicates cell damage is occurring. In Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e the higher gradations of structural variations surround the activated state whereas conversely the lower gradations surround the baseline state. Having this response layout can add resolution to the level of cell injury and how the structural variations of MG can be utilized as a proxy for perturbations in cellular or interstitial homeostasis. The offered resolution to cellular metamorphosis of MG should serve as important distinction points of its activity as it relates to its morphology that can suggest an anomalous interstitial condition (which arises from an injured cell that is about to lose viability) ergo a precursor pathological event that eventually leads to some CNS pathology (in this case pathology that arises from chemical toxicity). Importantly, this detectable/measurable precursor event, microglial metamorphosis, may offer better opportunity for understanding how dendritic/MG cells respond to post BBB CNS cell stress; that is, if we confide in the ability of these cells to detect CNS cell injury prior to than the current most sensitive determinants (intracellular enzyme levels increases in extracellular fluids which suggests their leakage from damaged cells). These cellular events are likely antecedent to mass enzyme leakage which represent cell membrane rupture.\u003c/p\u003e\n\u003cp\u003eIn conclusion, microglia are a unique cell within the most exclusive extracellular matrix in the body, its 3 main characteristics, that is: size, dendrites and cell body shapes allow the assignment of distinct morphological structures. Affirmations of cell stress that is biochemically verifiable and confirmations of MG shape shifting characteristics could most effectively be done in this culture model; further and probably most importantly, the initial events of cellular stress within the context of cellular architectural tissue matrix are isolated. Downstream biochemistries can be studied that ascribe certain genetic (as demonstrated by Keren- Shaul et al., 2017) or proteomic changes that can relate to MG\u0026rsquo;s morphology can be further characterized and studies in greater detail in this isolated sample without the noise presented by extra-matrix influences of blood derived cells and chemokine signaling outside the interstitium; and conversely, much more contextually than in cell suspension culture isolation. And, albeit MG appears as an amorphous construct, it follows a certain structure pattern as it metamorphosizes and thus leads to 5 distinct intermediate definable structural variations between baseline (M2) and activated (M1) forms. Furthermore, detailed, and definable aspects of its cell body structure (and quantitative changes in membrane distances that can be amenable to algorithmic evaluation), nucleus placement and number of dendrites indicate that perhaps MG\u0026rsquo;s shape isn\u0026rsquo;t as vague as it appears. Also, it is important to note that as MG reach the M1 state (structural variations 3+) they become a denser cellular particle that can impact interstitial spacing and thus glymphatics (Nedergaard et al., 2020; Trejos et al., in preparation) and thereby interrupt interstitial flow. Such is that the data generated from this isolation indicated that the hippocampal tissue slice is a relevant biological quantum of contextualized cells that maintains initial immune cell activity, confirmable survival, and spacing profile of CNS tissue matrix after excision. The biochemical confirmation of a cellular stress and death using MTT and PI, and then evaluating the individual properties of the MG cell response as a dendritic cell represents a fortified rational biological sequence of events that can be isolated and explored further. This isolation can shed some further depth of biochemical, proteomic, and genetic understanding as to what happens when tissue is injured and how it concerts with immune cells\u0026rsquo; morphological response. Nevertheless, the structural resolution offered describes how microglia behave morphologically and can be used to potentially attribute events antecedent to cell death within the post BBB CNS and adds greater depth of knowledge to microglia\u0026rsquo;s role in this highly exclusive parenchymal compartment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eArtificial Intelligence (AI)\u003c/p\u003e\u003cp\u003eAntibody (Ab)\u003c/p\u003e\u003cp\u003eBlood Brain Barrier (BBB)\u003c/p\u003e\u003cp\u003eCentral Nervous System (CNS)\u003c/p\u003e\u003cp\u003eCluster of Differentiation 11 (CD11)\u003c/p\u003e\u003cp\u003eDentate Gyrus (DG)\u003c/p\u003e\u003cp\u003eDisease Associated Microglia (DAM)\u003c/p\u003e\u003cp\u003eIonized Calcium-Binding Adaptor (IBA-1)\u003c/p\u003e\u003cp\u003eLactate Dehydrogenase LDH\u003c/p\u003e\u003cp\u003eImmunohistochemistry (IHC)\u003c/p\u003e\u003cp\u003eMessenger Ribonucleic Acid (mRNA)\u003c/p\u003e\u003cp\u003eMicroglia (MG)\u003c/p\u003e\u003cp\u003eModified Eagle Medium (MEM)\u003c/p\u003e\u003cp\u003ePhosphate Buffered Saline (PBS)\u003c/p\u003e\u003cp\u003ePropidium Iodide (PI)\u003c/p\u003e\u003cp\u003eFetal Bovine Serum (FBS)\u003c/p\u003e\u003cp\u003eFluorescein Diacetate (FDA)\u003c/p\u003e\u003cp\u003eCell Counting Kit 8 (CCK-8)\u003c/p\u003e\u003cp\u003e3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT)\u003c/p\u003e\u003cp\u003e4\u0026prime;,6-Diamidino-2-Phenylindole (dapi)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJAT wrote the manuscript, FAX edited and reviewed manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003eLinnea R. Vose, Ph.D. and Patrick K. Stanton Ph.D. for training on how to isolate rat hippocampal slices using a Syskiyou tissue slicer.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDiSabato D, Quan N, and Godbout JP. Neuroinflammation: The Devil is in the Details. J Neurochem. 2016 October; 139(Suppl 2): 136\u0026ndash;153. doi:10.1111/jnc.13607.\u003c/li\u003e\n\u003cli\u003eFern\u0026aacute;ndez-Arjona MM , Grondona JM, Granados-Dur\u0026aacute;n P, Fern\u0026aacute;ndez-Llebrez P and L\u0026oacute;pez-\u0026Aacute;valos MD Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis. \u003c/li\u003e\n\u003cli\u003eFern\u0026aacute;ndez-Arjona M, Grondona JM, Granados-Dur\u0026aacute;n P, Fern\u0026aacute;ndez-Llebrez P and L\u0026oacute;pez-\u0026Aacute;valos MD. 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(2007) The American Journal of Pathology, Vol. 171, No. 2.\u003c/li\u003e\n\u003cli\u003eXiang Z, Chen M, Ping J, Dunn P, Lv J, Jiao B, and Burnstock G. Microglial Morphology and Its Transformation After Challenge by Extracellular ATP In Vitro. (2006) Journal of Neuroscience Research 83:91\u0026ndash;101\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4682521/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4682521/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe dendritic cell of the CNS, the microglia (MG), is an initiation point of the immunological response within the post blood-brain barrier (BBB) compartment. Microglia drastically changes in response to cell stress to a much different non-dendritic morphology. This investigation postulates that if the first MG responses to toxic injury are isolated and studied in greater morphological detail there\u0026rsquo;s much to be learned about microglia\u0026rsquo;s metamorphosis from and M2 to an M1 state. The organotypic hippocampal slice was the experimental setting used to investigate microglial response to toxic injury; this isolates dendritic cell to post-BBB cells dynamics from the impact of nonspecific of \u003cem\u003ein-vivo\u003c/em\u003e blood derived signaling. Within the context of biochemically verified precise toxic cell injury/death (induced with mercury or cyanide in combination with 2-deoxy-glucose) to a specific region within the hippocampal slice, MG\u0026rsquo;s morphological response was evaluated. There was up to 35% increase in microglia activation proximally to injury (CA3 region) and no changes distally (DG region) when compared to control slices treated with PBS. Maximum microglia activation consisted of a 3 plus-fold increase in the distance between the nucleus membrane and the cell membrane, which underscores an extensive and quantifiable amount of membrane rearrangement. This quantification can be applied to contemporaneous AI image analysis algorithms to demarcate and quantify relative MG activation in and around a site of injury. In between baseline and activated MG morphologies, 5 intermediate morphologies (or morphological behaviors) are described as it relates to its cell body, nucleus, and dendrites. The result from this study reconciles details of MG\u0026rsquo;s structure to its holistic characteristics in relation to parenchymal cell stress.\u003c/p\u003e","manuscriptTitle":"Evaluation of 5 Intermediate Microglia’s Structural Variations Within an Organotypic Hippocampal Slice Model After Regionalized Toxic Injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 17:06:38","doi":"10.21203/rs.3.rs-4682521/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-07-09T05:46:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-09T01:49:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Neuroinflammation","date":"2024-07-03T20:09:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroinflammation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jneu","sideBox":"Learn more about [Journal of Neuroinflammation](http://jneuroinflammation.biomedcentral.com)","snPcode":"12974","submissionUrl":"https://submission.nature.com/new-submission/12974/3","title":"Journal of Neuroinflammation","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ea80330b-9bfb-4820-8b48-2faa52e0587a","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-08-09T17:06:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-09 17:06:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4682521","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4682521","identity":"rs-4682521","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}