Our laboratory has previously used targeted laser ablation to injure specific regions of the 3 dpf larval zebrafish heart (Figure 1A; Matrone et al., 2013, 2014). We further optimized this approach to induce a localized injury at the ventricular apex of 3 dpf larvae (Supplementary Figure 1-supplement 1). Targeting this region increases reproducibility as it is anatomically unambiguous and minimizes the risk of heart rupture, thus avoiding the release of erythrocytes into the pericardium, which interferes with imaging. These refinements therefore provide a cardiac injury model that more closely mimics a human MI.

Immediately following laser injury, the myocardium at the apex swells and contraction diminishes (Figure 1B). Injured ventricles display a lack of contractility leading to a reduced ventricular ejection fraction compared to uninjured larvae at 2 h post injury (hpi) (Figure 1C and Supplementary Video 1). The injured region is marked by a loss of GFP signal in the cardiomyocyte reporter line Tg(myl7:GFP) (Figure 1D and Supplementary Video 1). Staining with propidium iodide (PI) shows this GFP negative region is necrosed myocardium (Supplementary Figure 1-supplement 2A). TUNEL staining of injured hearts at 2 hpi shows the GFP-negative border zone containing apoptotic cardiomyocytes (Figure 1E), which was corroborated using acridine orange staining (Supplementary Figure 1-supplement 2B). To further validate the injury response, we utilized the Tg(myl7:mCherry;nfkb:GFP) line to determine if NFkB, an important regulator of programmed cell death, is upregulated following heart injury, as reported in other animal models of MI (Tillmanns et al., 2006; Karra et al., 2015). We observed increased nfkb expression in cardiomyocytes bordering the ventricular lesion at 24 hpi (Figure 1F). This ring-like expression pattern (Figure 1G) mimicked TUNEL staining (Figure 1E), again supporting that laser-targeted cardiomyocytes undergo programmed cell death.

To characterize the recruitment of neutrophils and macrophages to the heart following laser injury we serially imaged Tg(myl7:GFP;mpx:mCherry) and Tg(myl7:GFP;mpeg1:mCherry) larvae respectively over a two-day period at 2, 6, 24, and 48 hpi using epifluorescence microscopy (Figures 2A,B). Following heart injury, neutrophil numbers on the ventricle increased from 2 hpi, peaked at 6 hpi (3.2 ± 0.4), and gradually resolved to uninjured levels at 48 hpi (0.6 ± 0.2) (Figures 2A,C). While macrophage numbers increased significantly from 6 hpi, cardiac macrophages aggregated at the lesion from 2 hpi (Figure 2B). Macrophage numbers remain elevated at 24 hpi (7.6 ± 0.7), decreasing but not returning to uninjured levels by 48 hpi (5.1 ± 0.4 vs 1.8 ± 0.3) (Figures 2B,C). Both neutrophils and macrophages localized primarily at the ventricular apex injury site (Figures 2A,B and Supplementary Video 2). We also observed neutrophils cyclically migrating around the injured heart, being propelled forwards with each cardiac contraction in real time (Supplementary Video 3).

We contextualized the findings of our heart injury model by comparing it to the well-characterized larval tail fin transection model (Renshaw et al., 2006; Hoodless et al., 2016). Tail fins were transected at 3 dpf and immune cell recruitment quantified at the same timepoints. Similar immune cell dynamics were observed between both models, including a peak neutrophil response at 6 hpi that decreased at 24 hpi and 48 hpi, and a sustained macrophage response during 6–24 hpi, which decreased slightly by 48 hpi (Figures 2D,E). A notable difference between the two injury models was the magnitude of the immune response at 6 hpi, with a 7-fold increase in neutrophils and 2-fold increase in macrophages following tail transection. Additionally, tail inflammation resolved more slowly, with neutrophil numbers remaining relatively high at 48 hpi and macrophage numbers decreasing less steeply between 24 and 48 hpi (Figure 2E).

To determine the origin of neutrophils and macrophages recruited to the heart following injury we used two photoconvertible lines Tg(mpx:gal4;UAS:kaede) and Tg(csf1r:gal4;UAS:kaede), which allow spatiotemporal labeling of individual neutrophils and macrophages respectively (Holmes et al., 2012a). By choosing to convert the kaede fluorophore in specific regions of the larva, one can deduce at later timepoints, and in other tissues, whether any immune cells have originated from the converted region. We extended this technique by ‘semi-converting’ regions such that immune cells retain a roughly 1:1 ratio of unconverted and converted kaede, thus allowing assessment of the contribution of three regions simultaneously.

We divided each larva into three anatomical zones (1) head (proximal), (2) pericardium (local) and (3) trunk (distal) which were photoconverted fully, partially or left unconverted respectively. Cells were photoconverted one hour prior to injury and then imaged at 2 hpi and again at the peak immune response at 6 hpi (Figure 3A). At 2 hpi, the majority of both neutrophils and macrophages recruited to the heart were pericardial in origin (84 ± 6.9% and 82 ± 9.8% respectively), with a very small proportion originating from the head (10 ± 5.5% and 3.3 ± 3.3%, respectively) (Figure 3B). The most distal zone (the trunk) contributed very few neutrophils at 2 hpi, however a substantial proportion of heart recruited macrophages originated from the trunk (15 ± 7.6%). Later at 6hpi, we observed an increase in the proportion of trunk-derived neutrophils and macrophages (33 ± 7.7% and 29 ± 9.5%, respectively). Indeed, the absolute number of pericardium-derived immune cells did not increase at 6 hpi, and the overall increase in numbers for each cell type was largely due to the arrival of trunk-derived immune cells (Supplementary Figure 3-supplement 1A). Finally, whilst the proportion of neutrophils originating from the head remained low at 6 hpi, a substantial proportion of the peak macrophage response was head-derived (23 ± 9.9%, Figure 3B).

Wounding studies in larval zebrafish have previously shown that neutrophils primarily undergo reverse migration to resolve their numbers (Mathias et al., 2006; Holmes et al., 2012a,b; Ellett et al., 2015). To test the hypothesis that reverse migration contributes to resolution of immune cell numbers following heart injury, we again utilized photoconvertible lines Tg(mpx:gal4;UAS:kaede) and Tg(csf1r:gal4;UAS:kaede). In this experiment, immune cells in the pericardial region were photoconverted at the peak response at 6 hpi. Larvae were subsequently re-imaged at 24 hpi to assess the location of any neutrophils or macrophages that may have reverse migrated from the injury (Figure 3C). Summarized by the heatmaps in Figure 3D, neutrophils can be seen to disperse in a posterior and dorsal direction away from the injury. In contrast, macrophages appear to disperse more evenly in all directions. Interestingly, neither cell type moves more than approximately 300 μm from the pericardial region despite our previous analysis demonstrating they can migrate much greater distances over a shorter timeframe during recruitment (Figure 3B). Notably, neither cell type reverse-migrates to any particular organ. Following tail resection, LSFM timelapse imaging suggests that a small number of neutrophils and macrophages undergo cell death at the wound (n = 6 timelapses up to 24 hpi) (Supplementary Videos 4, 5). However, only immune cell reverse migration was observed following heart injury (n = 12 timelapses up to 24 hpi).

Following the discovery that both neutrophils and macrophages attend the heart lesion from local and distal sites, we posited that there are chemokine attractants coordinating this response. The best characterized of these chemokines in zebrafish is the Cxcl8-Cxcr1/2 axis, which is required for neutrophil mobility (Deng et al., 2013; Powell et al., 2017; Zuñiga-Traslaviña et al., 2017). We first validated a well-characterized Cxcr1/2 antagonist SB225002 following tail transection and confirmed that it decreased the peak neutrophil response but did not affect macrophage recruitment (Supplementary Figures 3-supplement 1C,D). To determine if Cxcr1/2 is involved in neutrophil or macrophage recruitment to the heart, we performed the same experiment in our heart injury model. The Cxcr1/2 antagonist decreased both neutrophil and macrophage presence at the heart lesion (Figure 3E). The neutrophil response to injury appeared entirely abolished (Figure 3F). Interestingly, macrophage dynamics were unaffected by the drug up until 6 hpi, but significantly decreased at 24 hpi and 48 hpi (Figure 3G). These later timepoints are when macrophages recruited from distal sites would normally reach the heart (Figure 3B), suggesting these immune cells are migrating to the injury site via the action of chemokine attractants.

Having established that a significant proportion of late-recruited immune cells are from the distal trunk region, we next tested if heart injury was able to mobilize the cells specifically from the caudal hematopoietic tissue (CHT). The CHT is the predominant source of immune cells in the trunk and is known to contribute to wound neutrophil numbers following tail fin injury (Yoo and Huttenlocher, 2011).

First, we sought to verify whether the tail fin injury, which recruits many more immune cells than our heart injury, was capable of inducing CHT emptying of immune cells. Comparison of the CHT in uninjured controls and tail transected Tg(mpx:GFP;mpeg1:mCherry) larvae highlighted a reduction in the number of macrophages and neutrophils following injury (Figure 4A). The CHT depleted of neutrophils from 6–24 hpi, replenishing by 48 hpi. Macrophage CHT depletion was detected at 24 hpi and did not recover by 48 hpi (Figure 4C). Unlike tail injury, heart injury did not appear to stimulate a detectable decrease in the presence of CHT neutrophils (Figures 4B,D). However, heart injury caused a decrease in macrophage CHT presence at 24 and 48 hpi (Figures 4B,D), suggesting that macrophages migrate out of the CHT following heart injury.

In response to cardiac and skin wounds, mammalian neutrophils and monocytes mobilize into the circulatory system in order to rapidly arrive at the site of injury (Anderson and Anderson, 1976). We tested if immune cells circulate in peripheral blood following heart injury, as this has been observed following tail transection (Zuñiga-Traslaviña et al., 2017).

Live epifluorescence imaging allowed us to easily observe and quantify the number of circulating neutrophils and macrophages following either tail or heart injury using the Tg(mpx:GFP;mpeg1:mCherry) line. Whilst there were almost no circulating macrophages or neutrophils during uninjured conditions, an increased number of both cell types were detected in circulation following tail transection at 6 hpi (4.3 ± 0.9 and 11.4 ± 2.7, respectively) (Figure 4E). Neutrophils were detected in the blood at 2 and 6 hpi whilst macrophages were only detected at 6 hpi. Similarly, we detected a number of neutrophils in the circulation of heart injured larvae, albeit fewer than in tail transected larvae (3.3 ± 0.9 vs 11.4 ± 2.7) (Figure 4F). In both injury models we observed trans-endothelial migration of neutrophils from the CHT into the cardinal vein, where they became spherical and began to roll or flow freely in the blood stream (Supplementary Video 6). We also observed rolling and egress of macrophages from the CHT following tail transection (Supplementary Video 7). Although we measured a reduction in CHT macrophages following heart injury, and acquired images of macrophages exiting the CHT into the cardinal vein (CV), there was not a statistically significant increase in circulatory macrophages at any time point (Figure 4F).

Having shown that increased macrophage numbers at the heart lesion from 6 hpi were not accompanied by increased circulating macrophages, we next sought to determine if there were other routes and modes of immune cell migration from distal tissues.

Likely candidates were lymphatic vessels and peri-vascular surfaces, as these are known to be rich in adherent proteins and represent a ready-made transport network through the trunk musculature of the larva (von Andrian et al., 1993). To image both vascular and lymphatic networks in the same larva, we crossed two endothelial reporter lines to give Tg(fli1:eGFP;kdrl:mCherry) and injected high molecular weight blue fluorescent dextran to visualize any unmarked vessels and fluid spaces (Figure 5A). The vessels, known to run anteriorly posteriorly and ventrally dorsally, were indeed marked by all three of these labels. The anterior-posterior orientated vessels are the dorsal lateral anastomotic vessel (DLAV), dorsal aorta (DA) and CV, whilst the only ventro-dorsal vessels are the intersegmental vessels (ISV) that pattern the length of the larva (Isogai et al., 2001). Additionally, there are parachordal lymphatics (PCL) positioned parallel to the larval notochord (Figure 5A), as reported previously (Jung et al., 2017).

We injected high molecular weight dextran into Tg(mpx:GFP;mpeg1:mCherry) larvae to visualize all vessels and performed whole larva epifluorescence timelapse imaging. This facilitated simultaneous observation of all neutrophils and macrophages and directly confirmed their migration patterns through the trunk musculature for both injury models (Supplementary Video 8). In steady state, neutrophil presence outside the CHT was rarely observed and only macrophages were seen patrolling the musculature (Figure 5B). Temporal maximum intensity projections derived from superimposed epifluorescence images in uninjured larvae show neutrophils and macrophages largely restricted to the CHT and head regions (Figure 5C).

Tail fin transection resulted in marked mobilization of macrophages and neutrophils from the CHT (Figure 5C). While the CHT of uninjured larvae appears as an intense white region of macrophage and neutrophil co-localization, transected larvae have neutrophils liberated dorsally and ventrally and migrating toward the tail transection. Quantification of vessel usage show that both cell types predominantly use the CV for migration in both uninjured and tail transection settings (Figure 5D and Supplementary Figure 5-supplement 1B). Neutrophils increase their use of PCL and the DA following injury to reach the tail wound. In contrast, macrophages take a more dorsal route, increasing their use of the PCL and the DLAV (Figures 5C,D and Supplementary Video 8).

Following heart injury, we observed more anterior-directed immune cell migration than in tail transected larvae (Figure 5C). In contrast to tail transection, macrophages begin to increase their use of the CV, taking a ventral route to the heart, occasionally using other vessels and the yolk sac (Figures 5C,E). Interestingly, neutrophils did not significantly increase their use of anterior-posterior oriented vessels in our quantification area (Figure 5E and Supplementary Figure 5-supplement 1B). Analysis of pseudotracks revealed this is because, following egress from the anterior pole of the CHT, neutrophils move dorsally via ISVs. It is only after that we observed neutrophils moving anteriorly via the DLAV and then through the perinephric region to the heart (Figure 5C and Supplementary Video 8). Close inspection of timelapses revealed that both macrophages and neutrophils migrate along the abluminal surface of vessels rather than inside them (Figure 5F).

In addition to vessel usage, we tested if other aspects of immune cell motility changed following injury, namely meandering and speed. Although macrophage speed only increased after tail transection, neutrophils significantly increase their speed following tail transection and to a lesser extent following heart injury (Figure 5G and Supplementary Figure 5-supplement 1A). Meandering index (MI) was unchanged for both cell types and in both injury settings (Figure 5H), indicating the increase in neutrophil speed is not an artifact of directionality. Taken together our data confirm that immune cells indeed use vessels as routes of migration and that there are unique patterns of use for each cell type and injury setting.

Having shown that most neutrophils and macrophages are recruited to the heart locally (Figures 3A,B), we next wanted to identify how these cells migrate to the ventricle at a local scale. We used our optical gating system coupled with LSFM to acquire computationally frozen high-resolution 3D images of the beating heart (Taylor et al., 2011, 2012, 2019). We injected Tg(kdrl:mCherry) larvae intravenously with fluorescent dextran and applied our heartbeat-synchronized imaging to search for existing lymphatic or coronary vessels that could play a role in guiding immune cells to the injury site. We did not find the heart to have any supporting lymphatics or coronary vessels, only a thin layer of endocardium (Figures 6A,B). We next utilized the pan-chromatin Tg(h2a:GFP) line which labels all nuclei to visualize the whole pericardium. Analysis of 3D fluorescence image stacks by surface rendering confirmed no other cellular structures or routes between the pericardium and heart (Figure 6C).

We next performed heartbeat-synchronized imaging in injured Tg(kdrl:mCherry;mpeg1:mCherry;mpx:GFP;h2a:GFP) larvae, allowing neutrophil and macrophage chemotaxis to be tracked in 3D over several hours (Taylor et al., 2019). Timelapse imaging revealed that both cell types patrol the pericardium, with the majority of tracks concentrated around the bulbous arteriosus (Figure 6D and Supplementary Video 9). Tracking analysis also revealed that neutrophils and macrophages migrate to the injury site via adjacent points on the pericardial wall, typically on the ventricular side (Figure 6D and Supplementary Video 9).

To improve our understanding of neutrophil and macrophage behavior specifically at the heart lesion, we acquired 3D timelapse videos of Tg(myl7:GFP;mpx:mCherry) (Figure 6E) and Tg(myl7:GFP;mpeg1:mCherry) (Figure 6F) larvae up to 24 hpi. These timelapse videos demonstrated neutrophil wound swarming and macrophage accumulation at the wound, followed by reverse migration of both cell types (Supplementary Videos 10, 11). Quantification of individual cell behavior revealed that neutrophils migrated faster on the ventricle compared to macrophages following injury (4.3 ± 0.2 μm/min vs 2.1 ± 0.2 μm/min) and in uninjured larvae (4.1 ± 0.3 μm/min vs 2.4 ± 0.2 μm/min) (Figure 6G). However, neutrophil and macrophage speed following injury was no different to uninjured larvae (Figure 6G). Both neutrophils and macrophages reside on the ventricle for significantly longer periods of time following injury (Supplementary Figure 6-supplement 1). The duration of individual macrophage residency on the ventricle is 3-fold higher than neutrophils following injury (545 ± 28 min vs 178 ± 37 min) (Supplementary Figure 6-supplement 1). The speed and duration in part explain the turnover of immune cells on the ventricle and therefore contribute to the overall recruitment dynamics following injury (Figure 2). Furthermore, neutrophils and macrophages recruited to the ventricle displayed greater meandering behavior following injury compared to uninjured larvae (0.48 ± 0.03 MI vs 0.71 ± 0.04 MI and 0.11 ± 0.003 MI vs 0.26 ± 0.04 MI). Additionally, macrophages were more meandering than neutrophils following injury (0.11 ± 0.003 MI vs 0.48 ± 0.03 MI) (Figure 6G). Taken together, these data demonstrate that both immune cells have distinct behavioral characteristics which become altered following heart injury.

We next tested if there were neutrophil-macrophage interactions on the heart following injury, such as macrophage efferocytosis of neutrophils as previously observed in other injury models (Meszaros et al., 1999; Ellett et al., 2011). LSFM timelapse experiments (n = 6 up to 24 hpi) using Tg(mpx:GFP;mpeg1:mCherry) larvae did not show any notable neutrophil-macrophage interactions on the heart (Figure 6H and Supplementary Video 12). Interestingly, we identified immune cells that were co-expressing the transgenes mpx:GFP and mpeg1:mCherry (Figure 6I). This observation prompted us to investigate these co-positive cells further as neutrophils are generally thought to be a homogenous cell type.

We observed cells expressing both mpx:GFP and mpeg1:mCherry at and around the injured heart using both LSFM timelapse and epifluorescence microscopy (Figure 7A). This subset of cells represents 2.3 ± 1.0% of mpx:GFP+ or mpeg1:mCherry+ cells on the injured ventricle (Figure 7B). Co-positive cells are observed more frequently at tail transection wounds (Figure 7C and Supplementary Figure 7-supplement 1A), where they make up a much higher proportion of cells 14.4 ± 2.2% (Figure 7D). Hence, herein we chose the tail transection model to characterize the nature of these cells.

An important question is whether these cells are neutrophils or macrophages We first found indirect evidence that co-positive cells might be neutrophils through comparison with a similar reporter line with different versions of the same transgene Tg(mpx:mCherry;mpeg1:GFP). Using this combination of transgenes, we observed very low numbers of wound-associated co-positive cells (1.9 ± 1.6%) (Figure 7D). Comparisons of the proportions of each cell type between these transgenic lines showed that whilst macrophage proportions were very similar between lines, the co-positive cell population observed in Tg(mpx:GFP;mpeg1:mcherry) arises at the expense of its neutrophil population. Likewise, it follows that some mpeg1-mpx+ cells observed in Tg(mpx:mCherry;mpeg1:GFP), might be this same population of co-positive cells, albeit unmarked in this line.

Next, we assessed if co-positive cells were csf1r+, a gene not expressed in neutrophils and required for macrophage development (Sweet and Hume, 2003; Chitu and Stanley, 2006). Using Tg(csf1r:gal4;UAS:mCherry-NTR;mpx:GFP) larvae, we showed no co-expression of mpx:GFP and csf1r:mCherry-NTR in recruited cells following tail transection (Figures 7E,F). We can therefore deduce that co-positive cells also do not express csf1r, again suggesting that co-positive cells are more neutrophil-like in their fluorophore markers. Finally, we utilized our finding that the pharmacological Cxcr1/2 antagonist (SB225002) inhibits the recruitment of neutrophils but not macrophages following tail transection specifically (Supplementary Figures 3-supplement 1C,D). We reasoned that if co-positive cells were neutrophils then SB225002 should decrease their number at the wound but not if they are macrophages. Tail transected larvae treated with SB225002 did indeed exhibit decreased numbers of co-positive recruited cells at the wound, again suggesting that the co-positive cells are likely neutrophils (Figure 7G and Supplementary Figure 7-supplement 1B).

In order to be confident that co-positive cells represent a subset of neutrophils, we excluded the most likely alternative explanations of their mpx:GFP+ mpeg1:mCherry+ expression. One such explanation is that co-positive cells represent neutrophils that have ingested mpeg1:mCherry+ macrophage cellular material. However, analysis of LSFM-acquired images at subcellular resolution refuted this hypothesis. We found co-positive cells to have a uniform intensity distribution of both fluorophores throughout the cytosol and found no phagosomes, suggesting endogenous expression (Supplementary Figure 7-supplement 1C). Next we tested if co-positive cells could represent activated or else developmentally immature neutrophils. Scans of different regions of 3 dpf larvae found these cells in non-hematopoietic tissues such as the perinephric region and brain in addition to the CHT (Supplementary Figure 7-supplement 1D). Furthermore, flow cytometry analysis of mpx:GFP+ and mpeg1:mCherry+ positive cells isolated from transected tailfins demonstrated that both mpx:GFP+ mpeg1:mCherry- and co-positive neutrophils degranulate following injury as evidenced by a trend for their side scatter to decrease (Supplementary Figure 7-supplement 2C). Taken together with the fact that co-positive cells attend wounds, it seems unlikely these cells are immature neutrophils. Furthermore, careful analysis of LSFM timelapse videos showed no instances of mpx:GFP+ mpeg1:mCherry- neutrophils transitioning to co-positive cells (Supplementary Video 13), nor was there any difference in forward scatter between cell types (Supplementary Figure 7-supplement 2B), suggesting that one is not simply an activated form of the other.

Having excluded likely alternative explanations, we proceeded to investigate differences in phenotype between single-positive neutrophils, macrophages and co-positive cells, and whether they might have a specialized role during inflammation. Our flow cytometry analysis did not show any difference in size (FSC) or granularity (SSC) between single-positive or co-positive neutrophils in steady state or injury setting (Supplementary Figures 7-supplement 2A–C). Hence, we took advantage of our unique ability to analyze the behavior of cells in vivo to assess if there were obvious behavioral or physical differences between single positive neutrophils, macrophages and co-positive cells. By tracking all three cell types in 3D timelapse to the transected tail fin, we were able to precisely measure speed, sphericity, meandering index and volume (Supplementary Figures 7-supplement 3A–D). No differences were found between co-positive cells and single-positive neutrophils for any of the measures (Figure 7H). However, several differences between macrophages and the other two cell types were found, again indicating that co-positive cells are neutrophils and not macrophages. Specifically, macrophages were found to be more meandering, less spherical, slower and tended to be larger than the other two cell types (Figure 7H). Though our data does not show any obvious structural or behavioral differences between single-positive and co-positive neutrophils, their unique molecular signature and presence at the wound indicate that they are playing a role in wound healing that is yet to be elucidated.

Zebrafish husbandry, embryo collection and maintenance were conducted as per standard operating procedures. This was in accordance with the Animals (Scientific Procedures) Act, 1986 and approved by The University of Edinburgh Animal Welfare and Ethical Review Board in a United Kingdom Home Office-approved establishment. All experiments were performed on staged animals aged between 72–120 hpf (Kimmel et al., 1995). The following transgenic zebrafish were used: Tg(myl7:eGFP)^twu26 (Huang et al., 2003), Tg(myl7:h2b-GFP)^zf52 (Mickoleit et al., 2014), Tg(myl7:DsRed2-NLS)^f2 (Rottbauer et al., 2002), Tg(nfkb:eGFP)ⁱ²³⁵ (Feng et al., 2012), Tg(mpx:mCherry)^uwm7 (Yoo et al., 2010), Tg(mpx:GFP)ⁱ¹¹⁴ (Renshaw et al., 2006), Tg(mpeg1:mCherry)^gl23 (Ellett et al., 2011), Tg(mpx:gal4;UAS:Kaede)ⁱ²²² (Ellett et al., 2015), Tg(fms:Gal4.VP16)ⁱ¹⁸⁶, referred to as csf1r:gal4 (Gray et al., 2011), Tg(UAS-E1b:NfsB-mCherry)^c264, abbreviated to UAS:mCherry-NTR (Davison et al., 2007), Tg(fli1:eGFP)^y1tg (Lawson and Weinstein, 2002), Tg(kdrl:mCherry)^ci5 (Proulx et al., 2010), Tg(kdrl:GFP)^la116 (Choi et al., 2007), and Tg(h2a:GFP) (Pauls et al., 2001). Adults were day-crossed as appropriate to yield desired combinations of transgenes in embryos. Embryos were treated with 0.003% phenylthiourea (Fisher Scientific, Hampshire, New Hampshire) at 7 hpf to prevent pigment formation and enhance image clarity (Karlsson et al., 2001). Fish were housed at 28.5°C in conditioned media and imaged at room temperature (23°C) on various microscopes (details below). When necessary, larvae were periodically anesthetized using 40 μg/ml tricaine methanesulfonate (Sigma Aldrich, St Louis, Missouri) before being transferred back to conditioned media.

A Zeiss Photo Activated Laser Microdissection (PALM) laser system (Zeiss, Oberkochen, Germany) (Supplementary Figure 1-supplement 1) was used to induce a localized injury at the ventricular apex of anesthetized 72 hpf larvae as initially reported recently (Taylor et al., 2019). Larvae were laterally mounted on a glass slide in 20 μl anesthetized conditioned media and the laser was fired through a 20X objective. Injuries were deemed successful when ventricular contractility noticeably decreased, the apex had shrunk, and the myocardial wall had swollen without causing cardiac rupture and subsequent erythrocyte leaking (Figure 1B). A successful injury resulted in the segment of dysfunctional tissue losing fluorescent myocardial transgenic signal (Figure 1D). Uninjured (control) larvae were treated in the same manner up to the point of laser injury, when they were individually separated into single wells of a 24-well plate and maintained in the same environmental conditions as injured fish.

The tail fin of anesthetized 72 hpf larvae was transected using a sterile scalpel, avoiding damage to the end of the notochord and vasculature (as depicted in the Figure 2 schematic), and as previously reported (Hoodless et al., 2016). Uninjured (control) fish were treated in the same manner up to the point of transection, when they were separated into a 24-well plate and maintained in the same environmental conditions as injured fish.

A Leica M205 FA stereomicroscope (Leica, Wetzlar, Germany) with GFP, mCherry and BFP filters was used for all serial timepoint epifluorescence imaging experiments. To visualize neutrophil or macrophage presence at heart or tail wounds, larvae were anesthetized and mounted laterally on a glass slide in 50 μl of conditioned media. The number of immune cells on the heart were quantified by manually observing and counting cells moving synchronously with the beating heart. Heart images were acquired using 16X objective. The number of immune cells at the tail were quantified by counting from the caudal end of the vascular loop to the wound edge as performed by others (Miskolci et al., 2019). Tail images were acquired using 8X objective. CHT images were acquired using a 6X objective. Whole larvae images were acquired using 2.5X objective. The number of circulating immune cells were quantified by manually observing whole larvae for liberated cells which can be detected in real time migrating through or around the vasculature.

An EVOS Auto2 system (ThermoFisher, Waltham, MA, United States) with GFP, RFP and DAPI filters was used to image whole larvae in epifluorescence timelapse, in an automated manner at 28.5°C. Larvae were anesthetized and mounted laterally in a 6-well plate in 1% agarose. Three larvae were mounted per well. To ensure larvae remain immobilized, 500 μl of anesthetic solution was added to each well. Images of each well were acquired using a 2X objective at 1-minute intervals up to 24 hpi.

Individual larvae were prepared for LSFM by embedding in 1% low melting-point agarose (ThermoFisher, Waltham, Massachusetts) in anesthetized conditioned media inside FEP tubes (Adtech Polymer Engineering, Stroud, United Kingdom). This embedding reduced gradual drift of the embryo in the FEP tube, without causing developmental perturbations during long-term imaging. Larvae were used only once for a timelapse imaging experiment, and any repeats shown come from distinct individuals. Larvae were mounted head down such that the heart faces toward both illumination and imaging objectives to improve image clarity. All LSFM experiments were performed at room temperature (23°C). The setup of our custom-built LSFM system has been previously reported in detail (Taylor et al., 2019).

Real time prospective optical gating and more recent adaptive prospective gating methods in conjunction with LSFM have been previously published (Taylor et al., 2011, 2012, 2019). In summary, the software permits real-time 3D imaging of the normally beating heart by determining the phase of the cardiac cycle using images acquired from a separate bright-field camera. The software checks subsequently acquired bright-field images against this reference image-set in real-time and activates the imaging laser at a user-designated phase of the cardiac cycle. This ensures the lightsheet only strikes the heart when it is in that desired phase of the cardiac cycle, illuminating each z-plane for a few milliseconds and limiting the impact of phototoxicity and photobleaching. Synchronization is maintained over tens of hours by periodically updating the reference images to account for changes in appearance of the heart during development/injury (Taylor et al., 2019). For timelapse imaging, the entire heart is scanned in 3D every 3 mins, with a z-plane spacing of 1 μm, and each image stack is stored as a.tif file. These images can be viewed as a maximum intensity projection images during acquisition in order to, if necessary, optimize the quality of subsequently acquired images.

To detect cell death at the injured ventricle, whole-mount larval TUNEL staining was performed. Larvae were fixed in 4% PFA for 30 mins and transferred to 1:10 dilution of PBS. Larvae were subsequently digested in 1 μg/ml Proteinase K for 1 h. Larvae were re-fixed in 4% PFA for 20 mins and subsequently washed in PBT. TUNEL staining was performed using ApopTag Red In situ kit (MilliporeSigma, Burlington, MA, United States) to label apoptotic cells, as described in (Buckley et al., 2017). Stained hearts were imaged using LSFM.

To corroborate these findings acridine orange staining was performed. Larvae were incubated in 10 ng/μl of Acridine orange solution (ThermoFisher, Waltham, MA, United States) in the dark for 20 min. Larvae were subsequently washed three times in conditioned media for 10 min and imaged using heartbeat synchronized LSFM.

For live staining with propidium iodide, larvae were injected intravenously with a 1 nl volume of 1 mg/ml PI (ThermoFisher, Waltham, MA, United States) in PBS immediately following laser injury (∼15 minutes post injury) and imaged using heartbeat synchronized LSFM.

We established a specific protocol for photoconversion of neutrophils and macrophages following laser heart injury, using Tg(mpx:gal4;UAS:kaede) and Tg(csf1r:gal4;UAS:kaede) larvae respectively on a Leica M205 FA epifluorescence stereomicroscope (Leica, Wetzlar, Germany). To increase throughput, we generated a digital reticule informing us of the beam location on the larva. The reticule was specifically positioned to target one of two different regions; the head and/or pericardium. Larvae were mounted laterally in 50 μl of conditioned media on a glass slide prior to photoconversion. The beam was focused through a Leica PLAN APO 2.0x CORR Objective with an eye piece magnification of x16. A Mercury Vapor Lamp (Leica, Wetzlar, Germany) at 50 W power was used in conjunction with a BFP filter to photoconvert kaede-labeled immune cells. Depending on the experiment, larvae were either differentially photoconverted at 1 h prior to heart injury and imaged at 2 and 6 hpi (immune cell tissue origin assay), or their pericardiums were fully photoconverted at 6 hpi and imaged at 24 hpi (immune reverse migration assay). For the immune cell tissue origin experiment, the head was first fully photoconverted from green to red by exposing larvae for 60 s (until no green kaede signal was detectable above background). Next, the pericardium was semi-converted from green to brown (red and green) by exposing larvae for 30 s (immune cells retain 1:1 ratio of unconverted vs converted kaede fluorophore). The remainder of the larvae (which we term trunk) maintained endogenous green kaede fluorophore, hence producing three differentially labeled immune cell populations in the same larvae. Larvae were not imaged beyond 24 hpi because, shortly after this elapsed time, converted kaede fluorophore became difficult to detect in semi-converted cells. For the immune cell reverse migration experiment, the pericardium was fully photoconverted from green to red by exposing larvae for 60 s (until no green kaede signal was detectable above background). We confirmed that 93 ± 2.7% of pericardial immune cells photoconverted at 6 hpi were able to be traced at 24 hpi following their reverse migration, therefore validating the sensitivity of this technique (Supplementary Figure 3-supplement 1B). Larvae were imaged using both GFP and mCherry filters to detect level of photoconversion.

Larvae were preincubated in 5 μM SB225002 (Sigma Aldrich, St. Louis, MO, United States) or 0.1% DMSO vehicle (Sigma Aldrich, St. Louis, MO, United States) dissolved in conditioned media at 70 hpf for two hours prior to heart or tail injury. Following injury, larvae were continuously bathed in drug or vehicle throughout the duration of the experiment.

Custom-synthesized molecular weight (500 kDa) pacific blue fluorophore-labeled dextran (Fina Biosolutions, Rockville, MD, United States) was injected into larvae at 1 hpi. Injections were administered in a 1 nL volume of 5% (w/v) dextran dissolved in phosphate-buffered saline and injected into the cardiac sinus venosus as described in more detail previously (Rider et al., 2018).

Unless otherwise stated, images were prepared, processed and analyzed using ImageJ (Fiji) software (National Institutes of Health, Bethesda).

Tg(myl7:GFP) hearts were imaged using a Leica M205 FA epifluorescence stereomicroscope (Leica, Wetzlar, Germany) to capture when the ventricle was in diastole and systole. The ventricular area in diastole and systole was measured and ventricular ejection fraction calculated using the formula 100 X [(Diastolic Area – Systolic Area)/Diastolic Area] (Matrone et al., 2013).

Epifluorescence images of photoconverted larvae were analyzed to quantify the number of immune cells that were fully converted (red), semi-converted (red and green) or unconverted (green) on the heart or to identify immune cell locations in the whole larvae following heart injury. More specifically, for the latter reverse migration (immune cell location) assay, each larva was divided into 48 equally sized square zones (3 rows of 16, individual zone size = 31000 μm²). The number of photoconverted immune cells within each square zone at 24 hpi was quantified per larvae, averaged and normalized per zone to generate a heat map (Figure 3D).

The number of immune cells specifically within the CHT (as depicted in Figure 4) were quantified across timepoints and normalized to baseline preinjury (0 hpi) for each larva. Quantification was performed in a semi-automated fashion using a custom FIJI. In brief, a rectangular region of interest (766 μm × 151 μm) is generated and positioned over the CHT. This region is cropped, and brightness/contrast enhanced to identify all neutrophils or macrophages. Background signal is subtracted, then an unsharp mask and watershed segmentation are applied. The ‘Analyze Particles’ plugin is run to measure the area of segmented neutrophils or macrophages in the CHT.

Timelapse images were analyzed using the FIJI plugin Trackmate (Tinevez et al., 2017) automating the tracking of neutrophils and macrophages. Detection parameters: LOG detector, diameter 14 μm and threshold 5 μm. Tracking was performed using Simple Linear Assignment Problem (LAP) algorithms with parameters: linking distance 27 μm, max closing distance 15 μm and gap closing max frame gap 2. The dataset was then handled one of two ways depending on the analysis.

Analysis 1 - vessel use incidence: the incidence of use of each vessel for lasered datasets was obtained manually by plotting a line along the dorso-ventral axis one somite anterior to the cloaca and counting how many cells pass the line over the time frame 1–12 hpi for each vessel. Detecting and ringing each cell using Trackmate aids counting. The same method was used for tail transection datasets except the dorso-ventral line was drawn four somites back from the tail fin. The reasoning behind using different sites for quantification is that the majority of migrating cells will be coming from the CHT, which is located between the two different wound sites we studied, and hence cells are expected to move in opposite directions depending on the injury model.

Analysis 2 - cell behavior: tracked cells were filtered to a range of 1.5–8 hpi and restricted to the trunk region of the larva. Non-migrating cells were then excluded from the analysis based on displacement. Remaining tracks were used for plots of speed and meandering index. Meandering index was calculated using the Trackmate output data ‘Displacement’, ‘Duration’ and ‘Speed.’ Where Meandering index = Displacement/(Duration/Speed).

Light sheet fluorescence microscopy z-stacks of the myocardium, endocardium, immune cells and nuclei were surface-rendered using Imaris software (Bitplane, Zurich, Switzerland). Rendered immune cells were tracked during the indicated time course using an autoregressive motion algorithm, and individual tracks were surface rendered for display using Imaris.

To distinguish kdrl:mCherry fluorescence from mpeg1:mCherry fluorescence, a sequential subtraction of two frames difference was performed across the image sequence to produce a magenta channel where only moving cells were visible. This distinguished moving macrophages (magenta) from the static endothelium (blue). To distinguish mpx:GFP fluorescence from h2a:GFP fluorescence, a threshold was applied across the image sequence, creating a mask for brighter mpx:GFP neutrophils only. The brightness/contrast of h2a:GFP fluorescence (gray) was altered so that it was visible when overlaid with the mpx:GFP fluorescent mask (green). All channels were combined to create a composite image displayed in Figure 6D.

Light sheet fluorescence microscopy timelapses of the myocardium and neutrophils or macrophages were processed as maximum intensity projections. The Fiji plugin MTrackJ (Meijering, 2006) was used to manually track the migration of immune cells from the moment they migrate onto the ventricular myocardium until the moment they reverse-migrate off the ventricular myocardium or, as is commonly the case for macrophages, until the end of the timelapse.

LSFM timelapses of the transected tail fin acquired at scan intervals of 1 min were analyzed using Imaris (Bitplane, Zurich, Switzerland). Default and suggested parameters were used for supervised tracking by the autoregressive motion algorithm. Co-positive cells were designated as cells with a mpx:mpeg1 ratio less than 3:1 and greater than 1.33:1. Gating the cells by ratios overcomes the variability in absolute intensity as cells move through different area of tissue and take on different shapes. Plotted values are calculated from the averages of all cells in a particular larva 2–3 hpi following tail transection.

LSFM z-stacks of transected tail fins were analyzed in Fiji using the plot profile function to measure the intensity of the desired fluorophore across a manually drawn line.

Larvae were euthanized using 0.3 mg/ml tricaine methanesulfonate at 24 h post injury (4 dpf) and transferred into 1 ml of enzyme digestion mix consisting of Collagenase V (Sigma Aldrich, St. Louis, MO, United States), Collagenase D (Roche, Basel, Switzerland), Dispase (ThermoFisher, Waltham, MA, United States) and DNase (Roche, Basel, Switzerland). A single-cell suspension in RPMI+ 10% FBS was achieved through mechanical homogenization and filtering through a 40 μm cell strainer. The cells were resuspended in HBSS (−/−)+ 15 mM HEPES+ 25 μM D-Glucose) and filtered through a 40 μm cell strainer. Lastly, DAPI (1:1000) was added to the sample which was subsequently analyzed by flow cytometry. Samples were kept on ice throughout and were analyzed by flow cytometry at 4°C. Analysis and visualization of data was performed using FCS Express 7 software (De Novo Software, Pasadena, CA, United States).

Graphs and statistics were curated in GraphPad Prism 8 software (GraphPad Software, San Diago, CA, United States). Data were analyzed by student t-test, one-way ANOVA or two-way ANOVA followed by an appropriate multiple comparison post hoc test. All statistical tests, p-values and n numbers used are given in figure legends.