In this paper, we describe a protocol for in vivo imaging of microglial Ca2+ activity and subsequent analysis of its spatiotemporal dynamics. This method enables thorough characterization of how microglia respond to changes in the brain environment, appropriately capturing the fine spatiotemporal scales at which such events occur.
Microglia are the sole resident immune cells in the central nervous system. Their morphology is highly plastic, changing depending on their activity. Under homeostatic conditions, microglia possess a highly ramified morphology. This facilitates their monitoring of the surrounding environment through the continuous extending and retracting of their processes. During brain injury and inflammation, however, microglia become activated and undergo dramatic morphological changes, retracting their ramified processes and swelling their cell body. This facilitates activities such as migration and phagocytosis, which microglia undertake to navigate the brain environment to a less pathological state.
This close relationship between microglial morphology and changes in their activity have enabled considerable insights into various microglial functions. However, such morphological and activity changes are themselves phenomena that can result from any number of intracellular signaling pathways. Moreover, the time-lag between stimulus and response, as well as the highly compartmentalized morphology of microglia, make it difficult to isolate the causative mechanisms that underpin function. To solve this problem, we developed a genetically modified mouse line in which a highly sensitive fluorescent Ca2+-indicator protein is specifically expressed in microglia.
After describing methods for in vivo microglial Ca2+ imaging, this paper presents a structured analysis approach that classifies this Ca2+ activity to rationally defined subcellular regions, thus ensuring that the spatial and temporal dimensions of the encoded information are meaningfully extracted. We believe that this approach will provide a detailed understanding of the intracellular signaling rules that govern the diverse array of microglial activities associated with both higher brain functions and pathological conditions.
Microglia are the resident immune cells in the central nervous system (CNS) and play important roles in maintaining a homeostatic brain environment and in regulating neural circuit formation during brain development1,2. A unique feature of microglia in the CNS is that their morphology is highly plastic; however, distinct morphological phenotypes can be associated with particular functions. Furthermore, the transformation between morphological phenotypes is highly dynamic, occurring on rapid time scales in response to changes in the surrounding environment3,4.
Under homeostatic physiological conditions, microglia assume a highly ramified morphology, with multiple processes radiating outward in all directions. These ramified processes themselves demonstrate high motility, continuously extending and retracting3,4. Such activity is primarily directed toward periodic contact with neuronal synapses, axons, and somas to monitor neuronal activity5,6,7,8,9. However, when the brain is injured, microglia quickly detect this abnormality, and as a first step in their adaptive response, direct the extension of their processes toward the corresponding locale3,4. Where microglia are required to undertake phagocytosis of dead cells and metabolites, they assume an amoeboid-like morphology, shortening their processes and enlarging their cell bodies, as part of their transition into the immunologically activated phenotype10,11.
However, whilst the dramatic morphological changes of microglial processes are easily detected, finer scale changes of the cell soma are significantly more difficult to capture, especially at a temporal resolution that is physiologically relevant. Furthermore, morphological changes themselves only represent the integrated result of any number of intracellular signaling pathways. This is problematic for a goal of tracking functional activity and mechanistically linking a stimulus with the end response it provokes.
Given its widespread role as a second messenger, examining intracellular Ca2+ dynamics better captures the associated spatiotemporal information when studying dynamic cell processes. Such an approach is applicable to microglia given that they express a variety of ionotropic and metabotropic receptors linked to downstream intracellular Ca2+ elevation. Indeed, in vivo Ca2+ imaging has been used to characterize spatiotemporal aspects of microglial activities in real time, successfully correlating changes in microglial Ca2+ activity with brain injury, inflammation, and both hyper- and hypoactivity in neurons12,13,14,15,16. For example, Ca2+ elevations associated with microglial process extension in response to hyper/hypoactive neuronal activity likely reflect the underlying Ca2+-dependent actin polymerization process16. Furthermore, in vivo Ca2+ imaging can also be readily combined with pharmacological approaches. For example, whilst microglia express both P2X (ionotropic) and P2Y (metabotropic) receptors, local application of P2Y agonists mimics and subsequently desensitizes the microglial Ca2+ response to damaged neighboring neurons13, thus implying the greater relevance of P2Y signaling to neuronal damage detection.
To date, previous reports examining microglial Ca2+ activity have employed region of interest (ROI)-based analysis methods. A drawback of these approaches is that they are still too coarse to be able to resolve the spatiotemporal dynamics of Ca2+ activity at the level of individual microglial processes. Thus, this protocol describes both conventional ROI-based methods for analyzing microglial Ca2+ activity and newer event-based approaches, which can extract individual Ca2+ events in microglial processes. Before this, we provide a general guide for in vivo two-photon imaging to appropriately capture microglial Ca2+ activity for detailed analysis.
All animal experiments were approved by the National Institute for Physiological Sciences Animal Research Committees and were in accordance with the National Institutes of Health guidelines. For all experiments, 8-10-week-old male mice were raised under a 12/12 h light/dark cycle with ad libitum access to food and water. To visualize Ca2+ activity in microglia, ionized Ca2+ binding adapter molecule 1 (Iba1)-tetracycline transactivator (Iba1-tTA) mice were crossed with tetracycline operator-GCaMP6 (tetO-GCaMP6) mice17,18. Thus, in the absence of tetracycline-analog supplementation, the Iba1 promoter drives the expression of GCaMP6, exclusively in microglia. For all experiments, doxycycline dietary supplementation was stopped at 6 weeks after birth. At the end of all experiments, mice were euthanized by isoflurane overdose followed by cervical dislocation. See the Table of Materials for details related to all materials, animals, and reagents used in this protocol.
1. Surgical preparation of mice for in vivo two-photon imaging; day 1
2. Surgical preparation of mice for in vivo two-photon imaging; day 2
3. Data collection using in vivo two-photon imaging
4. Preparation for analysis (motion correction, mean/max z-projection)
5. ROI-based analysis
6. Event-based analysis
In transgenic mice exclusively expressing GCaMP6 (Ca2+-sensitive fluorescent protein) in microglia, we typically observe diverse patterns of microglial Ca2+ activity (Figure 2A). Importantly, even within a single microglia, the patterns of Ca2+ activity can differ dramatically between processes.
To quantify such process-to-process differences in the spatiotemporal dynamics of microglial Ca2+ activity, stable areas must first be identified and then divided into finely segmented ROIs (Figure 2B,C). For each ROI, parameters of Ca2+ activity must be derived and quantified, such as amplitude and frequency, by extracting features such as local amplitudes and trace slopes from the fluorescence intensity time series (Figure 2D–G).
Next, individual Ca2+ events must be examined by applying the accurate quantification algorithm AQuA (Figure 3A). From such event-based analyses, vast differences are typically observed in the origin, amplitude, duration, location, and flow direction characteristics of individual Ca2+ events (Figure 3B). If focusing on analyzing Ca2+ activity dynamics in microglial processes, a classification scheme of local events, events traveling toward the soma, and events traveling away from the soma is informative (Figure 3C).
Figure 1: Experimental setup for in vivo microglial Ca2+ imaging. (A) Experimental setup. An Iba1-tTA × tetO-GCaMP6 mouse with microglia-specific GCaMP6 expression. By inserting a cranial window in the mouse's skull, microglial Ca2+ activity can be observed in vivo using two-photon microscopy. (B) Experimental schedule and analysis procedure. 4D images are acquired for at least 10 min as five-frame z-stacks. The frame acquisition rate is 2.5 frames/s. Before analyzing microglial Ca2+ activity, the five-frame z-stacks are converted into 2D z-projections by taking the average (or maximum) intensity. The z-projection playback rate is 0.5 frames/s. Please click here to view a larger version of this figure.
Figure 2: ROI-based analysis for microglial Ca2+ activity. (A) Mean GCaMP6 intensity projection over 10 min for an individual microglia. (B) Stable areas (white) are defined by an overlay of binarized, maximum GCaMP6 intensity t-projections derived from 2 min samples taken at the start (magenta) and end (green) of an imaging period. (C) Stable areas are further segmented into regional ROIs. Individual colors indicate individual ROIs. (D) ΔF/F traces of all individual ROIs in C. Note the variation in activity patterns between ROIs. (E) Original trace of a ΔF/F time series derived from absolute intensity values for a single ROI. (F) The same ΔF/F time series after low-pass filtering. Candidate Ca2+ events are detected by an amplitude cut-off threshold (red line) defined as baseline + three SDs. The baseline (green line) is defined as the median value across the entire ΔF/F time-series within an upper and lower ceiling that excludes the maximum and minimum 10% of ΔF/F values. (G) The slope trace derived from the filtered ΔF/F time series in F. True Ca2+ events are sorted from candidate Ca2+ events based on a slope cut-off threshold (red line) defined as baseline + three SDs. The baseline (green line) is defined as the average value across the entire slope time-series within an upper and lower ceiling that excludes the maximum and minimum 10% of slope values. (H) Candidate Ca2+ events identified by amplitude criteria in F are indicated in orange. True Ca2+ events sorted from candidate Ca2+ events by slope criteria in G in red. Note that some candidate Ca2+ events have been merged based on the slope criteria. The corresponding filtered ΔF/F time series is overlayed below for reference. The black line indicates zero amplitude (ΔF/F). Mean and maximum amplitude of true Ca2+ events are derived as the mean and maximum of their corresponding peaks in the filtered ΔF/F time series. Frequency (events/min) is derived as the number of true Ca2+ firing events divided by the imaging period (10 min). Scale bars = 20 µm (A,B), 10 µm (C). Abbreviation: ROI = region of interest. Please click here to view a larger version of this figure.
Figure 3: Event-based analysis for microglial Ca2+ activity. (A) Representative images of events detected using the AQuA algorithm. The colors indicate individual event areas detected at one particular time point. (B) Representative normalized Ca2+ activity (ΔF/F) in individual events sorted by the order of onset. The right bar indicates color-indicated ΔF/F. (C) Representative activity-footprints of events propagating toward and away from the soma or local events. For local events, the event shape is shown in blue. For propagative events, the event onset time is indicated by the blue-yellow scale. Since AQuA initially detects Ca2+ events individually, propagative events are identified subsequently based on the overlapping spatial locations and time series of multiple individual Ca2+ events. Note that this is the same dendritic branch used for the ROI analysis in Figure 2E–H. Scale bars = 20 µm (A), 10 µm (C). Abbreviation: ROI = region of interest; S = soma. Please click here to view a larger version of this figure.
This paper introduces an improved approach for imaging microglial Ca2+ activity with a high spatiotemporal resolution. This method is sensitive enough to detect different types of microglial Ca2+ activity at the level of single ramified processes, readily distinguishing between local and propagative events.
In the general method for in vivo two-photon imaging of microglial Ca2+ activity, careful attention must be paid to the following points to maximize imaging quality. First, as microglia are extremely sensitive to injury, it is important to minimize directly touching the surface of the brain with surgical tools during surgery. Key indications that surgery has been proficiently performed are intact blood vessels and dura and very minimal bleeding during surgery. Second, secure attachment of the head-plate to the mouse's skull and good contact between the double coverslip and brain surface greatly reduce motion-related artifacts whilst imaging. This is especially important when imaging with high spatiotemporal resolutions and in fully awake mice. Whilst the analysis pipeline reliably compensates for motion-related artifacts arising from the heartbeat, respiration, and general drift, it is less robust when handling significant geometric distortions that arise from sudden large movements.
The two analysis methods described here offer different advantages and are suited to different research questions. In ROI-based analysis, the user predefines the ROI (such as individual processes), allowing for the aggregate dynamics of Ca2+ activity of this ROI to be extracted. Thus, it is most suited to situations where phenomena are expected to be localized to a subcellular area that has both well-defined morphological boundaries and a relatively large area (i.e., a process branch). In event-based analysis, individual events are defined based on the spatiotemporal dynamics of the microglial Ca2+ activity itself and must then be placed in the context of user-defined landmarks within the microglia for their function to be interpreted. Thus, it is most suited to situations where assumptions about phenomena localization cannot be made or where the area of interest is relatively small (i.e., a process tip). As such, event-based analysis offers improved spatiotemporal resolution when characterizing microglial Ca2+ activity as compared to previous methods.
In these mice, the only fluorescent marker expressed by microglia is the Ca2+ indicator GCaMP6. Thus, in regions where Ca2+ activity is low, microglial morphology must be extracted by combining multiple time frames, which can degrade temporal resolution. However, this limitation can be overcome by expressing a separate red stably-fluorescent protein in microglia. Notably, novel adeno-associated viruses capable of transfecting microglia have recently been described23,24,25.
How microglial Ca2+ activity is altered by the surrounding environment is an emerging topic of interest. In particular, microglial Ca2+ activity appears to show significant correlations with neuronal activity, though the functional significance of this has yet to be thoroughly characterized. Thus, combining neuronal activity manipulation with the imaging and analysis methods for microglial Ca2+ activity presented here should yield new insights into microglial physiology and further advance our understanding of the roles that microglia play in physiological and pathological states.
The authors have nothing to disclose.
We are grateful to Prof. Kenji Tanaka (Keio University, Tokyo, Japan) for providing Iba1-tTA mice and tetO-GCaMP6 mice. This work was supported by Grants-in-Aid for Young Scientists (B) [16K19001 (to H.H.)], Grants-in-Aid for Early-Career Scientists [18K14825 (to H.H.)], Grant-in-Aid for Scientific Research (B) [21H03027 (to H.H.)], Grant-in-Aid for Transformative Research Areas (A) [21H05639 (to H.H.)], Grant-in-Aid for Scientific Research (A) [17H01530, 20H00500 (to J.N.)], and JST CREST Grant [JPMJCR1755 (to J.N.)], Japan.
2% xylocaine jelly | AstraZeneca, UK | ||
B6(129S6)-Tg(Aif1-tTA)54Kftnk | RIKEN RBC, Japan | RBRC05769 | Iba1-tTA mice |
B6;129-Actb(tm3.1(tetO-GCaMP6)Kftnk) | RIKEN RBC, Japan | RBRC09552 | tetO-GCaMP6 mice |
Forceps | Fine science tools, US | 13008-12 | |
G-CEM ONE | GC corporation, Japan | ||
Glass capillary | Narishige, Japan | GDC-1 | |
ImageJ | NIH, US | ||
Isofulrane | Pfizer, US | ||
Ketamin | Daiichi-Sankyo, Japan | ||
Kwik-sil | World Precision Instruments, US | KWIK-SIL | |
MATLAB, 2017b | MathWorks, US | ||
Micro cover glass (2 x 2 mm, No.3) | Matsunami, Japan | custum-made | Bottom glass for cranial window |
Micro cover glass (3 x 3 mm, No.0) | Matsunami, Japan | custum-made | Upper glass for cranial window |
N25X-APO-MP | Nikon, Japan | N25X-APO-MP | Objective lens (25x) |
Norland optical adhesive | Edmund optics, US | 6101 | |
Piezo nano-positioning system, Nano-Drive | Mao City Labs, US | ||
Razor blade | Feather, Japan | FA-10 | |
Scissors | Fine science tools, US | 14060-11 | |
Steel drill | Minitor, Japan | BS1201 | |
Stereotaxic instruments | Narishige, Japan | SR-5M-HT | |
Super-bond (C&B kit) | Sun Medical, Japan | 4560227797382 | |
Surgical needle hook | Fine science tools, US | 10065-15 | |
Ti:Sappire laser, MaiTai DeepSee | Spectra Physics, US | Mai Tai eHP DS | |
Tweezers | Fine science tools, US | 11051-10 | |
Tweezers | Fine science tools, US | 11255-20 | |
Two-photon microscope | Nikon, Japan | A1R-MP | |
UV craft resin | Kiyohara, Japan | UVR | |
Xylazine | Bayer, Germany |
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