All experiments involving live zebrafish were carried out in compliance with Seattle Children’s Research Institute’s (IACUC protocol number ACUC00658) and University of Washington’s Institutional Animal Care and Use Committee guidelines (IACUC protocol number 2997-01). As zebrafish lateral line HCs develop by 5 days post-fertilization (dpf), experiments were conducted when fish were 5 dpf unless otherwise noted. Sex is not determined at this age.

For drug dose response testing, zebrafish of the wildtype genetic background AB (Table 1) and fish that were transgenic for GFP under the myo6b HC-specific promoter (Tg (myo6b:EGFP), Table 1) were raised as described previously (Westerfield, 2007; Farr et al., 2020). Briefly, zebrafish embryos were collected from 2 h spawning periods, washed with dilute bleach solution (0.005% sodium hypochlorite) by 6 hours post-fertilization to minimize contamination from microbes, and raised in Petri dishes in ICS water (300 mg Instant Ocean/L, 0.56 mM CaCl₂, 1.2 mM NaHCO₃, Table 1) (Linbo et al., 2009) at a density of 50 larvae per 100-mm² dish, in a dark 28.5°C incubator until 5 dpf, with fluorophore screening performed when relevant alongside dechorionation at 2–4 dpf; fish homozygous and heterozygous for fluorophore expression were both used.

For calcium testing, zebrafish expressing HC-specific GCaMP targeted to the inner mitochondrial matrix were crossed with fish expressing a HC specific calcium indicator to create double-transgenic embryos (Tg (myo6b:mitoGCaMP3;myo6b:cytoRGECO), Table 1) with both green fluorescent mitochondrial calcium and red fluorescent cytosolic calcium indicators, then raised as described previously (McQuate et al., 2023). Zebrafish embryos were collected from 2-h spawning periods and raised in Petri dishes in embryo medium (EM: 14.97 mM NaCl, 500 μM KCl, 42 µM Na₂HPO₄, 150 µM KH₂PO₄, 1 mM CaCl₂ dehydrate, 1 mM MgSO₄, 0.714 mM NaHCO₃, pH 7.2) at a density of 60 larvae per 100-mm² dish, in a dark 28.5°C incubator until 5 dpf. Larvae were screened for indicator expression at 4 dpf.

Healthy zebrafish lateral line HCs are selectively permeable to fluorescent vital dyes including YO-PRO1 (Table 1), which selectively stains lateral HC nuclei (Ou et al., 2010). The extent of drug-induced injury at different doses can thus be quantified by loss of fluorescent staining in HCs (Ou et al., 2010). Therefore, at 5 dpf, larvae were transferred to 12-well plates (5–11 fish per well, 1 well per condition) containing the relevant compound or combination diluted with ICS water, or ICS water alone or high-dose neomycin to serve as controls. Unless otherwise noted, fish were exposed to drug (either an individual compound or a pairwise combination of compounds) for 4 h, as a balance between longer exposure times for accommodating varied kill kinetics and shorter exposure times for technical tractability. Treatments with multiple drugs involved co-administering a prepared solution consisting of both drugs with defined concentrations in ICS water. Fish were then washed in fresh ICS water before being transferred to new 12-well plates containing a 2 µM solution of YO-PRO-1 for 20 min, before being washed in fresh ICS water, anesthetized with 675 µM tricaine (Table 1), and transferred to 96-well plates for imaging (1 fish per well, 60 fish per plate due to specifications of the microscope).

To facilitate the transfer of fish between exposures to drugs, fresh ICS, and YO-PRO-1 solutions, we developed custom single-use multi-well baskets (Figure 1A), inspired by the baskets described by Thisse and colleagues (Thisse and Thisse, 2008). We designed the frame for these baskets (https://www.thingiverse.com/thing:5676024), which we printed with a Dremel Digilab 3D45 3-D printer to provide a single point of manipulation for the whole plate. Nylon mesh was melted to this frame as previously described to form a basket for each well of the relevant multi-well plate (Thisse and Thisse, 2008). Each multi-well basket was disinfected with 10% bleach soak prior to use.

Fluorescence microscopy was performed using a Keyence BZ-X800 microscope imaging system, which enables high-throughput semi-automated imaging of 96-well plates. Using a GFP filter (525/50 nm emission, 470/40 nm excitation), each YO-PRO-1-stained fish in the 96-well plate was imaged under a ×2 objective to capture the whole organism in brightfield, green fluorescence, and red fluorescence channels.

The resulting images were analyzed for dose-response and drug interaction characteristics with the PEPITA software package, which can be found on GitHub (https://github.com/ma-lab-cgidr/PEPITA-tools). Images did not have to be consistent in exposure or aperture used, as values were postprocessed, making use of the fact that received signal is directly proportional to the exposure time and inversely proportional to the square of the aperture f-stop (42, 2019). Each image was masked using automated object detection to include only the fish itself. Manual masks were created on occasion for avoidance of fluorescent contamination, adjusted segmenting for myo6b::gfp fish to remove inner ear HC fluorescence, or exclusion of dead or damaged fish. Each fish was then adjusted for autofluorescence using the fluorophore-free red channel and scored based on the sum of green fluorescence pixel values surrounding 10 of the top 15 brightest pixels in the masked image (Figures 1B–E). These scores were standardized by comparison with the median score of wells containing untreated fish and a score representing no remaining HC fluorescence, both derived for each plate. The standardized relative fluorescence unit (RFU) scores were fitted against a log logistic model, as described previously (Ritz, 2010), to estimate dose response properties (e.g., EC₅₀, the effective concentration of eliciting 50% of maximal HC damage).

To prepare the fish for confocal microscopy, fish were fixed in 2% paraformaldehyde for 1 hour at room temperature as described previously (Philip et al., 2018), before being transferred to fluoromount and mounted between two glass coverslips. To avoid crushing the fish, a dot of nail polish was placed on each corner of the coverslip so that the top coverslip sat slightly above the bottom coverslip where the fish was mounted. Fluorescent confocal microscopy was performed using a Leica Stellaris 8 microscope. Cranial lateral line neuromasts of each fish were imaged under an HC PL APO CS2 40x/1.30 oil objective with a 405 nm laser and 541/47 emission filter. Images were taken as z-stacks in 0.66 µm steps. Stacks were transformed into average intensity projections and prepared for visual analysis in ImageJ.

For hair cell survival quantification from individual neuromasts, trained observers counted surviving hair cells in confocal images of neuromasts of larvae that had been treated with various doses of neomycin. Two to eight neuromasts were scored per condition, and counts for each neuromast were averaged between two scorers. These counts were divided by previously characterized mean hair cell counts (Harris et al., 2003), matched by anatomical position, to yield a position-scaled measure of HCs present in each neuromast. These position-scaled values were then converted to estimated percent remaining HCs by dividing by the average position-scaled value for untreated neuromasts of the same strain and experiment.

To further explore the mechanism of macrolide and aminoglycoside antagonism, we fluorescently labeled the aminoglycosides neomycin and gentamicin with Texas Red-X succinimidyl ester to track HC uptake with and without macrolide treatment (Table 1). To avoid breakdown of fluorescent vital dyes over time, we used larvae with the transgene Tg(myo6b:EGFP); myo6b::gfp, that expressed GFP in their HCs. Drug-induced injury was quantified by loss of fluorescence in HCs. Fish were exposed to the fluorescently-labeled drug with or without macrolide co-administration for 30 min, before being washed in fresh ICS water and anesthetized with 675 µM tricaine. Five fish per condition were transferred to 96-well plates for imaging, as per the drug response testing experiments, while another five were euthanized on ice for 20 min, then fixed in 2% paraformaldehyde for 1 hour at room temperature, to prepare for confocal microscopy. Samples were prepared and GFP fluorescence was acquired following the same confocal imaging procedure as described in Section 2.3; TexasRed fluorescence was acquired with a 595 nm laser and 675/75 emission filter.

For the fish transferred to 96-well plates for imaging, fluorescence microscopy was performed using the Keyence BZ-X800. Using the GFP filter and a TexasRed Filter (630/75 nm emission, 560/40 nm excitation), each myo6b::gfp fish was imaged under a ×2 objective to capture the whole organism in brightfield, green, and red fluorescence channels. Each fish was then imaged under a ×40 objective with z-stacking to track the uptake of the fluorescently labeled aminoglycoside into the HCs in the head of the fish.

FM1-43 experiments were performed with myo6b::gfp fish, raised to 5 dpf as above. Fish were exposed to drug conditions for 30 min, with 4 µM FM1-43 stain added into the drug treatment solution at minute 29, for a 1-min co-treatment stain exposure followed by simultaneous washout of all drugs and stain in fish water and anesthesia in 675 µM tricaine (selection of staining concentration and exposure duration was informed by (Hernandez et al., 2006; Van Trump et al., 2010; Thomas et al., 2013; Monroe et al., 2016; Hailey et al., 2017; Majumder et al., 2017; Rocha-Sanchez et al., 2018; Stawicki et al., 2019; Parkinson and Stawicki, 2021; Lee et al., 2022; Derudas et al., 2023; Schrauwen et al., 2023)). Four to seven fish per condition were transferred to 96-well plates for imaging. Using the Keyence BZ-X800 with GFP filter and a custom filter (605/70 nm emission, 470/40 nm excitation), each fish was imaged with a ×2 objective in brightfield and green and red fluorescence channels as above. FM1-43 uptake was validated using benzamil, a known uptake inhibitor (Rusch et al., 1994).

Calcium imaging was performed using an inverted Marianas spinning disk confocal system (Intelligent Imaging Innovations, 3i) with an Evolve 10 MHz EMCCD camera (Photometrics) and a Zeiss C-Apochromat 63x/1.2 numerical aperture water objective. Larvae were 5-6 dpf at the time of imaging. Larvae were first anesthetized in embryo media containing 800 µM tricaine, then stabilized on their sides under a harp, so that posterior neuromasts were exposed to the surrounding media. Imaging was performed at ambient temperature, approximately 25°C. GCaMP fluorescence was acquired with a 488 nm laser and 535/30 emission filter, with an exposure time of 100 ms, and RGECO fluorescence was acquired with a 561 nm laser and 617/73 emission filter and exposure time of 200 ms. Images were taken every 2 minutes as z-stacks through neuromasts in 2 µm steps. Neomycin and azithromycin were dissolved as a 4X stock in EM (described in Section 2.1: Zebrafish Husbandry), then added to the bath to achieve final working concentration after a 10-min baseline. Imaging of neuromasts continued for 50 min. Images were analyzed in ImageJ. Mean fluorescence intensity was measured for ROIs of individual randomly selected HCs (2–3 HCs per NM, see example ROI in Figure 4). For each HC, values were normalized to the average of baseline using Microsoft Excel.

For bacterial drug interaction testing, bacterial strains Staphylococcus aureus ATCC 29213, Escherichia coli ATCC 25922, were grown from frozen stocks on 5% sheep blood agar for 16 h at 37°C, and Mycobacterium abscessus ATCC 19977 was grown from frozen stocks on Middlebrook 7H10 agar for 3 days at 37°C (CLSI, 2020). On the day of inoculation, serial dilutions of the appropriate drugs were performed in separate plastic troughs and then combined in a clear, round bottom, cell-culture treated 96 well plate. Macrolide serial dilutions ascended in concentration row-wise (left to right) and aminoglycoside serial dilutions ascended in concentration column-wise (top to bottom). A bacterial inoculum of 0.5 (±10%) McFarland units was prepared in sterile saline and then diluted 1:100 in the appropriate media. The drug dilution plate was inoculated with 100 µL of the bacterial inoculum, and the plate was sealed and incubated at 37°C for 18 h to 3 days, depending on the strain. After incubation, plates were read on an indirect mirror box by eye for inhibition of all visible growth and with a SpectraMax i3x microplate reader for absorbance at 600 nm.

We quantified drug interactions with the excess over Bliss (EOB) metric (Berenbaum, 1989). Given a combination of drugs A and B, EOB was calculated for each individual well exposed to doses of both drugs based on monotherapy and combination responses with the formula E O B = R a × R b − R a b (1) (Berenbaum, 1989). Wells where the expected response ( R a × R b ) and observed response ( R a b ) were both less than 10% or greater than 90% were excluded from aggregation to reduce the effect of our choice of dose range. The remaining wells were summarized by averaging into a composite interaction score for the combination; we refer to this metric as the “windowed excess over Bliss” (wEOB).

Error bars, for both point estimates and line plots, indicate 95% confidence intervals, calculated by bootstrapping, as a nonparametric measure of uncertainty (DiCiccio and Efron, 1996). All zebrafish fluorescence data are included except for dead fish, fish too out of plane to view enough neuromasts for robust analysis, and experiments in which untreated controls are dimmer than several conditions that should have reduced HC fluorescence based on past data or literature. All bacterial data are included except for experiments in which uninhibited bacterial growth controls are less than the 60th percentile of measured wells or media only controls are greater than the 40th percentile of measured wells. Values plotted with no error bars depict individual measurements for the given conditions; when depicted with error bars, points represent the arithmetic mean of all valid measurements. For dose-response curve shift values, effective doses are estimated by interpolation on a logarithmic scale, and confidence intervals are estimated similarly based on bootstrapped point estimates. Shift p-values are calculated by extra sum-of-squares F test using the drc package in R (Ritz et al., 2015; Team, 2021). Elsewhere, p-values are calculated with Welch’s unequal variances t-test (West, 2021). Multiple testing is adjusted for with Benjamini-Hochberg FDR correction when noted (Benjamini and Hochberg, 1995).

We have developed PEPITA, a novel, semi-automated workflow for streamlined quantification of ototoxicity in zebrafish (Figure 1). The PEPITA workflow builds upon previous work that demonstrated that damage to zebrafish larval lateral line HCs could be quantified by evaluating the brightness intensity of fluorescently stained HCs using vital dyes such as YO-PRO-1 (Harris et al., 2003; Owens et al., 2008; Ou et al., 2009; Coffin et al., 2010; Thomas et al., 2015). Our platform enumerates relative residual brightness of YO-PRO-1-stained HCs after exposure of larvae to doses of individual or combinations of drugs. We quantify this remaining HC fluorescence as a proxy measure that is inversely proportional to the damage elicited by the ototoxic treatments.

PEPITA enables quantification of hundreds of individual YO-PRO-1-stained fish per experiment. This high-throughput quantification of ototoxic damage in zebrafish larvae enables us to perform granular, reproducible characterizations of ototoxic dose-response curves for each drug of interest (Figure 2; Supplementary Figures S1, S2).

To compare PEPITA’s ototoxic dose response characterization with the gold-standard approach of quantifying ototoxic damage (Chiu et al., 2008; Owens et al., 2008; Philip et al., 2018), we also performed side-by-side characterizations with manual HC counting of individual neuromasts in both YO-PRO-1–stained AB fish and myo6b::gfp fish (Figure 2, Supplementary Figure S1). Importantly, we find that dose response parameters derived from PEPITA correspond closely with estimates calculated by manual HC counting in both fish lines (Figure 2, Supplementary Figure S1). We also find that AB larvae stained with YO-PRO-1 and myo6b::gfp larvae present very similar neuromast appearance when untreated, at both high and low magnification, and decrease in fluorescence in a comparable way when treated with increasing doses of ototoxic drug. The two strains exhibit differences in doses necessary to achieve comparable levels of fluorescence inhibition. For instance, in our hands, the neomycin dose required to elicit 50% of maximal HC damage (EC₅₀, see Methods for details) was 20 μM in myo6b::gfp fish and 2.5 μM in AB fish stained with YO-PRO-1 (Figure 2, Supplementary Figure S1). Even in myo6b::gfp fish, this is lower than what has been observed previously, likely due to salinity differences, especially in calcium and magnesium, between our fish water and that of other investigators (Coffin et al., 2009; Linbo et al., 2009).

The shift between YO-PRO-1–stained AB and myo6b::gfp fish might potentially be due to a combination of factors, including differences in genetic background, an altered susceptibility to HC damage conferred by GFP (Monroe et al., 2016), and/or a subtle difference in the target of the assays’ direct measurement: HC survival (myo6b::gfp) versus HC functionality (YO-PRO-1–stained AB). The myo6b::gfp fish express GFP in HC cytoplasm on the myosin 6 promoter, so stresses should not affect cell fluorescence up to the point of membrane rupture. In contrast, AB fish are stained with YO-PRO-1 after drug treatment, and this dye is taken up by the cell and fluoresces when it binds DNA (Santos et al., 2006). This means that, in addition to cell death, changes in uptake, trafficking, and DNA organization—all important signs of HC functionality that could be impaired even with mild, sublethal ototoxic effects—can affect fluorescence (Chiu et al., 2008). Aminoglycosides cause damage at even relatively low doses, and at sufficient doses induce cell death by various pathways (Coffin et al., 2013). While HC death would result in reduced fluorescent signal for both myo6b::gfp and AB fish, sub-lethal HC damage affecting cell functionality would only reduce fluorescence for YO-PRO-1–stained AB fish. This implies two important caveats with regard to screening individual compounds with PEPITA: 1) ototoxic dose response profiles for individual drug treatments may vary depending on the genetic background of larvae tested, and 2) compounds that block YO-PRO-1 uptake without causing ototoxic damage may yield false positive indications for HC death when using AB fish stained with YO-PRO-1 alone, as we have observed with benzamil (Supplementary Figure S3). Complementary characterization with myo6b::gfp or other fish lines with transgenically labeled HCs will help to resolve these false positives. While our post-processing is currently optimized for reading out AB staining data, the platform is flexible to the use of other transgenic or stained fish as well.

Despite these differences in the underlying realities being measured, and the resulting difference in effective concentrations from individual drug exposure, it is important to note that observed drug-drug interaction effects appear to be comparable. When detected, antagonism between drug pairs as quantified by windowed excess over Bliss (wEOB, see Methods for detailed description) is observed to equivalent degrees in both assays (Supplementary Figure S4).

The high-throughput nature of PEPITA enables screening of ototoxic interactions experienced by fish by concomitant administration of combinations of drug treatments. In an initial pairwise screen of neomycin (NEO) against 13 compounds reported in the literature to impact HC survival and function (Rusch et al., 1994; Himeno et al., 2002; Rybak and Whitworth, 2005; Granowitz and Brown, 2008; Crumling et al., 2017; Lanvers-Kaminsky et al., 2017; Sheth et al., 2017), we found that azithromycin (AZM) was one of the strongest antagonizing compounds to ototoxicity (Supplementary Figure S5). To study the impact of this antagonism on the extent of otoprotection conferred by co-administration of AZM, we compared the extent of HC damage at varying doses of NEO exposure, with and without co-treatment with varying doses of AZM (Figures 3A–C). Although administration of high doses of AZM confers ototoxic damage (exposure to 380 µM AZM for 4 h resulted in 48% residual HC fluorescence in YO-PRO-1-stained larvae, as quantified by relative fluorescence units (RFU), Figure 3A), co-administration of 96 µM of azithromycin rescued HC viability at concentrations of neomycin that were otherwise toxic to HC (exposure to 6.4 µM NEO for 4 h resulted in 10% RFU in the absence of AZM, but 88% RFU when co-administered with 96 µM AZM, Figure 3A), and shifted the dose of neomycin needed to elicit 75% maximal HC damage (EC₇₅) by 13-fold (3.3 µM–42 μM, Figure 3C). This corresponded to wEOB score of −0.36, indicating strong antagonism (Figure 3B). This antagonism was observable in both AB and myo6b::gfp experiments (Supplementary Figure S4).

We wondered at the extent to which the antagonistic interaction between AZM and NEO observed with ototoxic response generalized to other aminoglycosides. We therefore tested ototoxic interactions between AZM and 5 aminoglycosides (neomycin (NEO), amikacin (AMK), gentamicin (GEN), tobramycin (TOB), and kanamycin (KAN)) (Figure 3D, Supplementary Figure S6; Table 1). Among interactions with AZM, co-administration with each of the 5 aminoglycosides exhibited otoprotective antagonistic interactions. For doses of each aminoglycoside that reduced functional HC survival by at least 70% when treated alone, co-administration with AZM resulted in 62%pt. protection in HC survival on average (improving from 15% survival to 77% survival on average; Figure 3D). In comparing the ototoxic HC damage dose response, the EC₇₅ of each aminoglycoside shifted at least 8-fold with AZM co-administration (Table 2, Supplementary Figure S7).

We also tested the impact of AZM co-administration on protection of ototoxicity with neomycin (NEO) and gentamicin (GEN) at two different time points: 1 h (acute) and 4 h (extended) of treatment. These timepoints were selected because they had previously been shown to convey differences in protection between NEO and GEN when co-administered with different cell death inhibitor compounds (Coffin et al., 2013). We found that AZM elicited significant protection against both NEO and GEN after 1 h and 4 h of treatment (for all conditions in which monotherapy induced a significant level of damage, AZM co-treatment conferred a significant level of otoprotection, Supplementary Figures S8A–D).

To evaluate the specificity of AZM-mediated otoprotective antagonism, we measured the ototoxic interactions of AZM coadministration with non-aminoglycoside drugs that convey ototoxicity clinically and share similarities in their modes of toxicity and action: cisplatin and capreomycin (Table 1). Cisplatin (CIS) was selected because of the similarity of the drug uptake mechanism in HCs relative to aminoglycosides (both sets of drugs require mechanoelectrical transduction (MET) channel activity for HC uptake) (Barrallo-Gimeno and Llorens, 2022). Capreomycin (CAP) was selected because it is an ototoxic antibiotic with a similar mode of action compared to aminoglycosides, but has a chemical structure with distinct chemical properties (Akbergenov et al., 2011; Krause et al., 2016; Rybak et al., 2021).

We found that AZM co-administration conferred significant but less pronounced protection from CAP-associated damage, (Figure 3D, Supplementary Figure S7). Exposure to 25 μM CAP yielded 90% HC inhibition in the absence of azithromycin (CI 83%–96%) and 60% HC inhibition in the presence of azithromycin co-administration (CI 45%–76%) (Figure 3D). In comparing the ototoxic HC damage dose response, the EC₇₅ of CAP shifted 2.8-fold (Table 2, Supplementary Figure S7). Notably, this protection only seems to be present in highly damaging doses of CAP as the CAP EC₅₀ shift was not significant (1.9-fold; CI −1.5–3.8 fold).

Similarly, AZM co-administration conferred significant but modest protection against damage caused by higher doses of CIS. Exposure to 600 μM CIS yielded 81% HC inhibition (CI 78%–83%) in the absence of AZM and 57% HC inhibition (CI 46%–68%) in the presence of AZM co-administration. As with CAP, AZM co-administration conferred stronger protection under conditions of high HC damage (EC₇₅ of CIS shifted 1.8-fold (CI 1.4 to 2.2-fold)) than lower HC damage (EC₅₀ of CIS shifted 1.4-fold, CI -1.9 to 2.8-fold) (Table 2, Supplementary Figure S7).

To evaluate the extent to which AZM’s otoprotective antagonism against aminoglycosides extends to other drugs in its class, we also tested two other commonly used macrolide antibiotics, erythromycin (ERY) and clarithromycin (CLM), on drug interactions with aminoglycosides. Based on our preliminary experiments, we found antagonistic interactions between CLM and each of AMK, GEN, KAN, and NEO (Supplementary Figure S6); however, we estimated that the optimally protective dose of CLM would be higher than the solubility threshold in water, so we chose to focus our characterization on ERY. We found that ERY also conveyed antagonistic otoprotection broadly against aminoglycoside ototoxicity during co-administration, although the most otoprotective dose of ERY was significantly higher than AZM (Supplementary Figure S7). The EC₇₅ of NEO shifted 8-fold (CI 4.0 to 17-fold) with co-administration of ERY (Table 2, Supplementary Figure S7).

Given that macrolide co-administration appeared to confer comparable otoprotection against neomycin after both acute (1-h) and extended (4-h) exposure, we hypothesized that the mechanism of macrolide-associated protection involved influencing drug uptake.

To test the effect of macrolide co-administration on aminoglycoside uptake, we adopted two complementary approaches: 1) measuring the effect of AZM administration on MET channel activity via HC uptake of FM1-43, a dye whose transport is mediated by MET channel (Gale et al., 2001) (Figure 4A); and 2) testing the effect of AZM co-administration on HC uptake of fluorescently-conjugated neomycin (Figure 4B).

We measured accumulation of FM1-43 in lateral line HCs in the presence vs. absence of AZM (190 µM) in myo6b::gfp larvae. AZM administration for 30 min prior to and during FM1-43 administration did not significantly change FM1-43 accumulation in HCs, whereas administration with the positive control, benzamil (BZM, 50 μM, a known MET channel blocker (Rusch et al., 1994)), for the same period showed significant inhibition of FM1-43 uptake (Figure 4A). These data suggest that MET channel activity is not impaired by AZM administration.

We also measured accumulation of TexasRed-conjugated neomycin (NEO-TR, 50 µM) in lateral line HCs in the presence vs. absence of AZM (190 µM) in myo6b::gfp larvae. AZM co-administration yielded reduced HC accumulation of NEO-TR (indicated by reduced TexasRed labeling in HCs after 30 min of exposure to TexasRed-conjugated drug), which was concomitant with reduced HC damage (indicated by increased GFP labeling in the same HCs) (Figures 4B, D, E). These data suggest that neomycin uptake is inhibited by azithromycin co-administration.

Should macrolides block aminoglycoside uptake into HCs, we expected downstream cell signaling pathways associated with aminoglycoside exposure would also be blocked. For example, it has been previously shown that once taken up by HCs, NEO induces a large spike in mitochondrial calcium, and subsequently in cytoplasmic calcium in HCs that go on to die (Esterberg et al., 2014). To test if AZM blocks these effects, we measured HC mitochondrial and cytoplasmic calcium responses in response to both NEO alone (50 µM) and co-administration of NEO (50 µM) with AZM (190 µM) in mitoGCaMP3; cytoRGECO larvae. Consistent with the previous findings, we demonstrated NEO induced an increase in mitochondrial (Figures 4C, F, Supplementary Figure S9; n = 4 fish, 9 neuromasts) and cytoplasmic calcium in HCs that went on to die (66% of those analyzed). Co-administration of NEO with AZM, however, blocked increases in mitochondrial and cytoplasmic calcium (Figures 4C, G, Supplementary Figure S9; n = 5 fish, 10 neuromasts). Although we occasionally observed increases in mitochondrial calcium and low levels of cell death with AZM administration alone (Supplementary Figure S9), there was no cell death observed with NEO and AZM co-administration. These results suggest that AZM co-administration and subsequent NEO uptake inhibition further blocks the downstream signaling pathways associated with NEO-induced death, namely, changes in HC calcium handling.

Given that both the macrolides and aminoglycosides that we tested are antibiotic agents, we investigated whether they antagonized each other’s antimicrobial activity during co-administration. Checkerboard assay experiments in S. aureus, E. coli and Mycobacterium abscessus (representing gram-positive, gram-negative, and atypical bacteria, respectively, Table 1), between AZM and 5 separate aminoglycosides (amikacin (AMK), gentamicin (GEN), kanamycin (KAN), neomycin (NEO), and tobramycin (TOB)) showed no pattern of antagonism (Figure 5). Average windowed excess over Bliss scores were 0.02 in E coli, −0.03 in M. abscessus, and −0.07 in S. aureus, suggesting on little interaction to even slight synergy. In comparing the interaction of these aminoglycosides with AZM, for AMK this represents a 31%pt. shift toward antagonism in lateral line HC damage as compared to inhibition of these bacterial species on average; for GEN 37%pt. toward antagonism, for KAN 45%pt. toward antagonism, for NEO 44%pt. toward antagonism, and for TOB 15%pt. toward antagonism. These values suggest that treating a bacterial infection with a regimen comprising AZM and any of these aminoglycosides would cause on average less ototoxicity relative to treatment with the aminoglycoside alone, without antagonizing the antimicrobial activity of the antibiotics.