The recruitment of innate immune cells to early pre-neoplastic clones and to wounds can profoundly influence cancer and repair outcomes (Feng et al., 2010; Antonio et al., 2015; Gurevich et al., 2018; Loynes et al., 2018). Detailed studies of inflammatory cell interactions and behaviours once having reached the vicinity of their target site have been hindered by a lack of suitable bespoke automated tracking software. We have developed novel algorithms to compare macrophage and neutrophil recruitment behaviours in response to growing pre-neoplastic clones vs. acute injury.

For a cancer model, we took advantage of a previously published zebrafish line, Tg(kita:HRASG12V-GFP) (Feng et al., 2010; Santoriello et al., 2010), where the kita promoter drives gene expression of a mutant human oncogene, HRASG12V, tagged with GFP, in melanoblasts and mucus-secreting goblet cells of the zebrafish larval skin. We have focused our studies on goblet cells in this cancer model because of their clarity for imaging. These HRASG12V expressing cells multiply unlike their equivalents in control larvae which express only a fluorescent marker and remain as single cells; from here on in we term the HRASG12V expressing clones as pre-neoplastic cells. For acute injury we made needle stick local wounds in the flanks of larvae.

We first compared the behaviour of innate immune cells responding to multiple clones of pre-neoplastic cells vs. wounded tissue, by live imaging neutrophils expressing cytoplasmic RFP and macrophages expressing nuclear GFP in Tg(kita:HRASG12V-GFP;lyz:DsRed;mpeg1:nls-Clover) cancerous larvae at 6 days post-fertilisation (dpf) (Hall et al., 2007; Bernut et al., 2019), and wounded Tg(lyz:DsRed;mpeg1:nls-Clover) larvae at the same developmental stage. Equivalent regions of skin in cancerous fish with pre-neoplastic clones, and in control larvae with single goblet cells fluorescently tagged with RFP, were imaged for 2 h, and these movies were compared to 2 h movies collected from wound lesions made in larvae with fluorescently labelled immune cells but no cancer burden at either 0.5 or 4 h post-wounding (hpw). Using a bespoke workflow enabling automated analysis we are able to quantify interactions between immune cells and lesions (wounds or pre-neoplastic cells) over time (Figure 1A and Supplementary Figure 1). This algorithm was designed to accurately detect and outline the plasma membrane of neutrophils, and the nuclei of macrophages, as well as the margins of both pre-neoplastic cancer clones and wounds, enabling dynamic “cell-to-cell” distance measurements between immune cells and the corresponding lesions to be gathered from large movie datasets (Figures 1Bi-iii and Supplementary Movie 1).

Using this software we quantified the number of immune cell-lesion interactions [classified as direct contacts or those within close proximity (<20 μm or <50 μm, neutrophil margin and macrophage nuclei, respectively)], and their duration (Figure 1A), in order to distinguish whether downstream consequences might be dependent on direct cell-lesion contacts, or rather, mediated by diffusible signals (e.g., growth factors or cancer cell killing molecules).

Very few neutrophil-goblet cell interactions were detected in unwounded control larvae (Figures 1D,F,F’ and Supplementary Movie 1). However, as previously described (Feng et al., 2010), if these cells express mutant HRASG12V, neutrophils are recruited to and interact with the growing pre-neoplastic clones (Figures 1E,F,F’ and Supplementary Movie 1). We see a similar level of recruitment, retention and interaction of neutrophils with larval local flank wounds at early timepoints (0.5–2.5 hpw) post-wounding (Figures 1B,F,F’ and Supplementary Movie 1). At later timepoints (4–6 hpw), the number of neutrophil-wound interactions increased considerably (Figures 1C,F and Supplementary Movie 1).

Numbers of macrophage interactions with both pre-neoplastic clones and local flank wounds are also higher than for control fish, with a progressive increase in the number of interactions observed at later timepoints post-wounding (Figures 1B–E,G and Supplementary Movie 1). Individual macrophage-lesion interaction time was similar for fish with pre-neoplastic clones and local flank wounds (Figure 1G’ and Supplementary Movie 1).

As well as counting numbers of immune cell interactions and measuring their interaction times with these various lesions, we wanted to determine whether their migratory behaviour, as gleaned from their tracks, had been significantly altered. Both neutrophil and macrophage velocity and directionality towards local flank wounds increase as cells are first being recruited, after wounding (from 0.5 to 2.5 hpw), but this reverted back to control levels by 4 h post-wounding (Figures 1H,I,B’–D’,H’,I’,B”–D” and Supplementary Movie 1). By contrast, despite clear recruitment of individual immune cells to pre-neoplastic cells, we see no overall increase in neutrophil or macrophage velocity, or directionality in the vicinity of these clones (Figures 1H,I,E’,H’,I’,E” and Supplementary Movie 1), indicating that recruitment of immune cells to pre-neoplastic clones was less synchronised than to wounds and thus hidden in our analyses of these multiple independently acting clones.

Next, we investigated whether bacterial infection alters the inflammatory response to wounding. We selected the gram-negative bacterium E. coli, which is non-pathogenic, but triggers an inflammatory response when injected into zebrafish larvae (Sieger et al., 2009; Colucci-Guyon et al., 2011; Hou et al., 2016). To address how neutrophils and macrophages respond to an infected wound, Tg(lyz:DsRed;mpeg1:nls-Clover) larvae were locally injected with E. coli (or control media) into a somite at 3 dpf, and larvae were imaged from 0.5 to 2.5 hpw (Figures 2A–C and Supplementary Movie 2). Infection leads to an increase in numbers of both neutrophil and macrophage interactions with the wound lesion. For neutrophils this leads to an increased total interaction time in infected vs. uninfected wounds. However, for macrophages, individual interactions become shorter in duration so that the total duration of macrophage interactions is not significantly altered by infection (Figures 2B–E,D’,E’,D”,E” and Supplementary Movie 2). Infection also alters other behavioural aspects of immune cells, in the vicinity of wounds, increasing their migration velocity although not their directionality (Figures 2B’,C’,B”,C”, Supplementary Figures 2A,B,A’,B’, and Supplementary Movie 2). Our time-lapse movies also show that infected wounds induce robust neutrophil swarming (Supplementary Movie 2), in agreement with data reported by others in response to different infectious stimuli (Huang and Niethammer, 2018; Poplimont et al., 2020).

Because infection clearly impacts the wound inflammatory response, we questioned how this might alter wound healing per se. To study this, we used confocal and scanning electron microscopy to image wounded Tg(krt4:GFP;krt19:tdTomato-CAAX) larvae in which superficial and basal epidermal skin cells are labelled in green and red, respectively (van den Berg et al., 2019) (Figures 2F–I). We observed that infection significantly delays wound healing of needle stick local wounds. Uninfected wounds heal very rapidly within the first hours post-wounding (Gault et al., 2014; Morris et al., 2018), with 60% of wounded fish showing complete re-epithelialisation by 8 hpw (Figures 2F”,H”,J). However, none of the infected wounds are healed at this early timepoint (Figures 2G”,I”,J), and while 100% of control wounds have completely healed by 48 hpw, 40% of infected wounds still remain unhealed and disorganised (Figure 2J), although at later timepoints they heal completely (data not shown). Infection is a known risk factor for impaired healing of wounds (Holder et al., 1997; Crompton et al., 2016; Miskolci et al., 2019) and our data suggest that a key link might be, at least in part, an altered wound inflammatory response, and that inflammatory cell behaviour might serve as a prognostic indicator for wound healing status.

Prior to our infection studies in cancerous larvae, we investigated how bacterial infection modulates the number and behaviour of immune cells in otherwise healthy zebrafish skin. Tg(lyz:DsRed;mpeg1:nls-Clover) larvae were either systemically injected with E. coli (or control media) at 2 dpf, or locally injected at 3 dpf, and the resulting behaviour of innate immune cells at the local injection site was quantified at 2 days post-injection (dpi) (Supplementary Figures 3A,F). Systemic E. coli infection triggers an increase in both numbers of macrophages and their velocity in skin, but does not appear to alter neutrophil numbers or their behaviour (Supplementary Figures 3B–E,B’–E’,B”–E” and Supplementary Movie 3). Local E. coli infection leads to increased numbers of both macrophages and neutrophils in the skin, and analysis of their tracks shows that both lineages exhibit increased velocity, with neutrophils also showing increased directionality, as if to an acute wound (Supplementary Figures 3G–J,G’–J’,G”–J” and Supplementary Movie 4).

Next, we examined how innate immune cells respond to pre-neoplastic cells in the skin, in the presence of a local or systemic E. coli infection, due to the potential clinical relevance of both infection strategies in the treatment of local primary cancers or dispersed metastatic cancers, respectively. Therefore, Tg(kita:HRASG12V-GFP;lyz:DsRed;mpeg1:nls-Clover) cancerous larvae were injected with E. coli (or control media), as previously described (Figures 3A,F). Both systemic and local infection experiments showed that immune cells are recruited in higher numbers to the cancerous skin (Supplementary Figures 4A–D) and that the number of occasions when leukocytes came within close proximity of a clone of pre-neoplastic cells is significantly increased in E. coli injected-fish compared with uninfected fish at 2 dpi (Figures 3B–E,G–J and Supplementary Movies 5, 6). However, for neutrophils, each of these interaction times are shorter so that total duration of neutrophil interactions is not significantly altered by infection (Figures 3D’,I’,D”,I”). By contrast, individual macrophage:pre-neoplastic cell interactions are of similar duration time, leading to an overall increase in interaction time in the infected fish (Figures 3E’,J’,E”,J”). Both neutrophils and macrophages exhibit an increased velocity, but no alteration in their directionality, when cancerous larvae are systemically or locally infected with E. coli compared with uninfected fish at 2 dpi (Figures 3B’,C’,G’,H’,B”,C”,G”,H”, Supplementary Figures 4A’–D’,A”–D”, and Supplementary Movies 5, 6).

Our automated cell tracking algorithm allows us to distinguish between direct contacts and close interactions between neutrophils and pre-neoplastic cancer clones. When we quantify number and duration of neutrophil:pre-neoplastic cell direct contacts we see no significant difference between infected and control larvae, in both systemic and local experiments, and similar is true for macrophage:pre-neoplastic cell direct contacts (Figures 3D,E,I,J,D’,E’,I’,J’,D”,E”,I”,J”) suggesting that any immune cell influence on cancer progression is not entirely dependent on direct cell:cell contacts, and rather is likely to be, at least in part, mediated by diffusible signals. Previous live imaging studies in zebrafish have indicated that direct contacts occur and can even lead to phagocytosis of pre-neoplastic cells (Feng et al., 2010; Chia et al., 2018), or to “donation” of cytoplasmatic material to the cancer cells (Roh-Johnson et al., 2017). However, murine studies have shown that infection-mediated tumour growth suppression is mediated by pro-inflammatory cytokines secreted by tumour-associated macrophages (Kim et al., 2015).

As previously described, a combination of heat-killed bacteria (S. pyogenes and S. marcescens), termed Coley’s toxins, has previously been shown to trigger cancer regression when administered to cancer patients (Coley, 1910; Felgner et al., 2016). This cancer “dissolving” effect was thought to be mediated by the activation of the host immune system following toxin treatment (Wiemann and Starnes, 1994). Therefore, we wondered whether Coley’s toxins might reproduce the behavioural effects of immune cells observed when E. coli was systemically injected in cancerous larvae. Indeed, we find that both neutrophils and macrophages alter their numbers and behaviour in the cancerous skin, and their interactions with pre-neoplastic cells upon systemic injection of Coley’s toxins, in ways that mimic our E. coli data (Figures 3D,E,D’,E’,D”,E” and Supplementary Figures 4A,B,A’,B’,A”,B”).

Since administration of live bacteria or Coley’s toxins to larvae with pre-neoplastic lesions clearly alters the behaviour of immune cells and their interactions with these pre-neoplastic cells, we investigated what might be the longer term consequences of these changes. A single systemic, or local injection of E. coli or Coley’s toxins at 3 dpf, results in no long term effect in numbers of pre-neoplastic cells (Figures 4A–C,F), but when cancerous larvae were given consecutive local injections of E. coli or Coley’s toxins at 3, 4, and 5 dpf, we observe that the number of pre-neoplastic cells is significantly reduced in 6 dpf larvae compared with fish multiply injected with control media (Figures 4A,D–F).

As a first step in characterising this infection-triggered blocking influence on immune cells we decided to investigate how multiple infections might alter leukocyte phenotype in ways that differ from a single infection timepoint. Tumour necrosis factor α (tnfα) expression is a useful proxy for the pro-inflammatory or M1 macrophage phenotype (Nguyen-Chi et al., 2015; Gurevich et al., 2018), and has been linked to cancer cell killing (Laster et al., 1988; Balkwill, 2009; Kim et al., 2015; Póvoa et al., 2021). We combined a zebrafish tnfα reporter line, Tg(tnfα:GFP) (Marjoram et al., 2015), with Tg(kita:HRASG12V-GFP;mpeg1:mCherry) cancerous fish, to reveal macrophages with a pro-inflammatory (tnfα-positive) phenotype in the vicinity of pre-neoplastic cells. Our data indicate that single injections of E. coli or Coley’s toxins lead only to transient tnfα expression by skin macrophages but daily injections lead to chronic tnfα expression maintained from 1 to 3 days post-first injection (dpfi) (Figures 4G–K,G’–J’). We speculate that this prolonged pro-inflammatory state exhibited by macrophages after multiple local infections may prompt the reduced pre-neoplastic cell numbers that we observe, although experiments transiently inhibiting these chronically activated tnfα-positive macrophages are needed to definitively confirm this. If proven, this would suggest a threshold response which we have seen also when investigating how wounding impacts on cancer cell growth, where only wounds above a threshold size, and triggering a sufficiently large inflammatory response, impact on clonal growth (Antonio et al., 2015).

Our study provides a new approach for quantifying how infection may alter the inflammatory response to a wound and to cancer cells in vivo, and how this might trigger immune cells to inhibit cancer growth or encourage cancer killing (Supplementary Table 1). Clearly, in the longer term it will be more useful to develop therapies that avoid delivery of infective particles. In this regard, a recent study showing how bacterial antigens can be mimicked by specific Toll-Like Receptor 2 (TLR2) agonists to switch macrophages into an anti-tumour phenotype indicates that such approaches may lead us towards therapies for the clinic (Feng et al., 2019).

Husbandry of adult zebrafish (Danio rerio) was performed as previously described (Westerfield, 2007). We used transgenic lines including: Tg(kita:Gal4;UAS:mCherry;UAS:HRASG12V-GFP) (Feng et al., 2010; Santoriello et al., 2010) which were in-crossed to obtain siblings either cancerous Tg(kita:HRASG12V-GFP), or control Tg(kita:mCherry); Tg(lyz:DsRed) (Hall et al., 2007); Tg(mpeg1:nls-Clover) (Bernut et al., 2019); Tg(mpeg1:mCherry) (Ellett et al., 2011); Tg(krt4:GFP;krt19:tdTomato-CAAX) (van den Berg et al., 2019); Tg(tnfα:GFP) (Marjoram et al., 2015). Animal experiments were ethically approved by the University of Bristol Animal Welfare and Ethical Review Body (AWERB) and conducted in accordance with the UK Home Office regulations.

E. coli infection experiments were performed using E. coli (BL21), expressing red fluorescent protein DsRed (kindly provided by Will Wood, University of Edinburgh) or blue fluorescent protein BFP (Thermo Fisher Scientific). Injection inoculum was prepared from an overnight LB culture in the log-phase of growth resuspended in 2% polyvinylpyrrolidone40 (PVP40) solution (Sigma) and phenol red (Sigma). For systemic infection, zebrafish larvae were anaesthetised at 2 days post-fertilisation (dpf) by immersion in 0.16 mg/mL Tricaine (Sigma) and injected with 2 nL containing 400–500 colony forming units (CFUs) of E. coli into the caudal vein, as previously described (Takaki et al., 2013). This bacterial concentration was selected as sub-lethal from our own titration experiments, and in accordance with previous studies (Colucci-Guyon et al., 2011). For localised infection, 1.5 nL containing 1,500–1,600 CFUs of E. coli were injected subcutaneously in the somite above the cloaca of anaesthetised 3 dpf zebrafish larvae, as previously described (Benard et al., 2012).

Coley’s toxins infection experiments were performed using Coley Fluid (MBVax Bioscience, Canada) which contains a combination of heat-killed S. pyogenes and S. marcescens equivalent to the preparation used by W. Coley in the past (Wiemann and Starnes, 1994), resuspended in 2% PVP40 solution. Zebrafish larvae were injected with 2 nL of this preparation for systemic infection or 1.5 nL for localised infection.

For repetitive local infections experiments, E. coli or Coley’s toxins were locally injected in the same somite (above the cloaca) on consecutive days (3, 4, and 5 dpf).

For localised wounding experiments, zebrafish larvae were anaesthetised in 0.16 mg/mL Tricaine prior to wounding their flanks in the somite directly adjacent the cloaca using a glass needle, following the protocol previously described (Gurevich et al., 2018). Larvae were harvested at appropriate times post-wounding and analysed by confocal and scanning electron microscopy (see below). Timepoints for analysis of immune cell-wound interactions were restricted to up to 6 h post-wounding to capture the early inflammatory response before the neutrophils leave the wounded area and a healthy skin wound entirely seals.

Zebrafish larvae were anaesthetised and fixed in primary fix (2.5% glutaraldehyde, 4% paraformaldehyde, 0.1 M sodium cacodylate) at 4°C overnight. These samples were washed in 0.1 M sodium cacodylate (3 × 10 min) and then transferred to 1% osmium tetroxide, at room temperature for 2 h. After fixation, samples were rinsed in 0.1 M sodium cacodylate before serial dehydration in EtOH and critically point dried and sputter coated with Gold/Palladium (Au/Pd) prior to imaging with a FEI Quanta 200 FEG scanning electron microscope.

Anaesthetised zebrafish larvae were mounted in 1% low-melting point agarose (Sigma) in a glass-bottomed dish, filled with Danieau’s solution with 0.1 mg/mL of Tricaine anaesthetic. Images were collected using a Leica TCS SP8 AOBS confocal laser scanning microscope attached to a Leica DMi8 inverted epifluorescence microscope with a 20× glycerol lens, maintained at 28°C. Movies were recorded at an interval time of 2 min per frame and a total time of 1.5 or 2 h and were exported from Fiji as QuickTime movies to play at 10 frames per sec.

Statistical analyses and graph generation were performed using GraphPad Prism 8. Data were confirmed to be normally distributed via D’Agostino-Pearson omnibus or Shapiro-Wilk tests prior to further comparisons. When the data was normally distributed, Student’s unpaired two-tailed T-test or ordinary one-way ANOVA with Tukey’s multiple comparison post-test were used to compare two groups or more than two groups, respectively. For non-normally distributed data, Mann-Whitney test or Kruskal-Wallis with Dunn’s multiple comparison post-test were used for comparison between two groups or more than two groups, respectively. Fisher’s exact test was used in the analysis of contingency tables to compare proportions between two groups. In column scatter plots, each dot represents one fish, except for those representing interaction time, velocity or directionality ratio where each small dot represents one cell and larger dots are the mean from one fish. In XY graphs, each dot represents the mean of all fish. In all graphs, which are representative of three independent experiments, the mean is used to calculate the average (horizontal bar), SEM (errors bars) and p-value. Statistical significance is indicated on graphs using standard conventions, as follows: n.s., non-significant, p > 0.05; ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001; ^****p < 0.0001. The number of fish or cells/fish used in the experiments is indicated for each graph in the figures.