1. Microbiology and Infectious Disease

Reactive oxygen detoxification contributes to Mycobacterium abscessus antibiotic survival

  1. Nicholas A Bates
  2. Ronald Rodriguez
  3. Rama Drwich
  4. Abigail Ray
  5. Sarah A Stanley
  6. Bennett H Penn  Is a corresponding author
  1. Department of Internal Medicine, University of California, Davis, United States
  2. Graduate Group in Immunology, University of California, Davis, United States
  3. Department of Molecular and Cell Biology, University of California, Berkeley, United States
  4. Department of Plant and Microbial Biology, University of California, Berkeley, United States
  5. Microbiology Graduate Group, University of California, Davis, United States
  6. Department of Medical Microbiology and Immunology, University of California, Davis, United States
https://doi.org/10.7554/eLife.104944.4
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  1. Nicholas A Bates
  2. Ronald Rodriguez
  3. Rama Drwich
  4. Abigail Ray
  5. Sarah A Stanley
  6. Bennett H Penn
(2026)
Reactive oxygen detoxification contributes to Mycobacterium abscessus antibiotic survival
eLife 14:RP104944.
https://doi.org/10.7554/eLife.104944.4
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eLife Assessment

Using a transposon sequencing (TN-seq) approach, the authors identified key genetic determinants of drug tolerance in Mycobacterium abscessus. Given that M. abscessus is inherently resistant to multiple antibiotics, this valuable study makes a significant contribution by uncovering how antibiotic tolerance is linked to reactive oxygen species (ROS) in this non-tuberculous mycobacterial (NTM) species. The solid findings further strengthen the growing evidence that ROS play a central role in the mechanism of antibiotic action and tolerance in mycobacteria. However, the use of words persistence or tolerance should follow the consensus definition given in the Balaban 2019 Nat Rev Micro paper.

https://doi.org/10.7554/eLife.104944.4.sa0

Abstract

When a population of bacteria is exposed to a bactericidal antibiotic, most cells die rapidly. However, a subpopulation of antibiotic-tolerant cells known as ‘persister cells’ can survive for prolonged periods. In addition, antibiotic tolerance can be broadly induced throughout the population by stresses such as nutrient deprivation. However, the pathways required to maintain viability in this setting and how stress induces antibiotic tolerance are both poorly understood. To identify genetic determinants of antibiotic tolerance in mycobacteria, we carried out transposon insertion sequencing (Tn-Seq) screens in Mycobacterium abscessus (Mabs) exposed to bactericidal translation-inhibiting antibiotics. This analysis identified genes essential for the survival of both spontaneous persister cells, as well as for stress-induced tolerance, allowing the first genetic comparison of these states in mycobacteria. Pathway analysis identified multiple genes involved in the detoxification of reactive oxygen species (ROS), including the catalase-peroxidase katG, which contributed to survival in both unstressed and nutrient-starved cells. In addition, we found that endogenous ROS were generated by translation-inhibiting antibiotics, and that hypoxia impaired bacterial killing. KatG specifically contributed to survival following exposure to transcription or translation inhibitors, but not other antibiotic classes tested. Thus, the lethality of some antibiotics is amplified by toxic ROS accumulation, and antibiotic-tolerant cells require detoxification systems in order to remain viable. These findings further demonstrate that antibiotic-induced ROS plays a broad role in mediating antibiotic lethality across diverse organisms.

Introduction

A key goal of antibiotic therapy is, in conjunction with the immune system, to eradicate the infecting bacteria. While many common bacterial infections respond rapidly to antibiotics, with 1–2 weeks of therapy sufficient to achieve high cure rates, there are also infections where bacterial clearance is slow and often incomplete (Stevens et al., 2014; Metersky and Kalil, 2018). This challenge is exemplified by mycobacterial infections. Fully susceptible Mycobacterium tuberculosis (Mtb) requires multiple antibiotics for 4 months or longer (Nahid et al., 2016), and infections by non-tuberculous mycobacteria, such as Mycobacterium abscessus (Mabs), are even more difficult to eradicate; Mabs often requires treatment for 12–18 months, and even then has a 50% relapse rate (Griffith and Daley, 2022; Griffith et al., 2007).

While the ability of mycobacteria to escape antibiotic-mediated killing is multifactorial, the phenomenon of antibiotic tolerance is likely an important contributor (Meylan et al., 2018; Namugenyi et al., 2017; Liu et al., 2016; Gold and Nathan, 2017). Studies dating from the 1940s noted that when a population of susceptible bacteria were exposed to a bactericidal antibiotic such as penicillin, the majority of the population died within a few hours, but a small subpopulation of cells remained viable for days (Bigger, 1944). Importantly, these antibiotic-tolerant cells referred to as ‘persister cells’ had not acquired a mutation conferring heritable antibiotic resistance, and do not grow in the presence of the antibiotic. Rather, they had entered into a readily reversible phenotypic state where, despite antibiotic-mediated inhibition of critical processes, they were able to survive (Ronneau et al., 2021; Dhar and McKinney, 2007; Grant et al., 2012). In addition, a number of physiologic stresses increase antibiotic tolerance in a population, as bacterial cell death is markedly slowed by stresses such as nutrient deprivation or acidic pH (Gold and Nathan, 2017; Bigger, 1944; Baker and Abramovitch, 2018; Saito et al., 2017). Notably, these same stresses are encountered in the lysosome of an activated immune cell (Hipolito et al., 2018), and studies of pathogens isolated from activated macrophages indeed show a strong immune-mediated increase in antibiotic tolerance (Liu et al., 2016; Sukumar et al., 2014). Thus, paradoxically, the immune system may actually impede bacterial eradication by antibiotics.

Antibiotic tolerance has been studied extensively in model systems such as Escherichia coli, which has provided important insights, but also highlighted uncertainties of current paradigms. Several different regulators of antibiotic tolerance have been identified in E. coli, including the HipBA toxin-antitoxin system (Schumacher et al., 2009), guanosine pentaphosphate ((p)ppGpp) synthesis by RelA/SpoT enzymes (Kusser and Ishiguro, 1987; Rodionov and Ishiguro, 1995; Bokinsky et al., 2013; Korch et al., 2003), and Lon protease (Harms et al., 2017). In each of these models, the postulated mechanism is to slow metabolism or cell division and render the process targeted by antibiotics nonessential. However, important questions remain. It remains unclear how cells remain viable when critical processes, such as transcription or translation, are blocked by antibiotics, as well as how antibiotic tolerance is induced by stress. Even the mechanism of cell death following antibiotic exposure itself has been a matter of debate – originally antibiotics were presumed to kill bacteria as a direct result of inhibition of their target molecule, such as β-lactam antibiotics disrupting cell wall integrity, directly leading to mechanical cell lysis (Wong et al., 2021). However, a number of studies, largely from E. coli, have demonstrated that in addition to the initial target inhibition, which may be bacteriostatic, bactericidal antibiotics can also cause secondary lethal reactive oxygen species (ROS) accumulation, leading to cell death (Grant et al., 2012; Kohanski et al., 2007; Dwyer et al., 2014; Zeng et al., 2022; Shee et al., 2022; Saito et al., 2021; Vilchèze et al., 2017).

Mycobacterial persister cells are particularly resilient, as Mycobacterium smegmatis (Msmeg) and Mtb persisters can endure many weeks of antibiotic exposure, and stress-induced antibiotic tolerance develops readily (Gold and Nathan, 2017; Grant et al., 2012; Shee et al., 2022). Mabs is a species of rapidly growing mycobacteria, with a doubling time of ~4 hr in rich media (Hunt-Serracin et al., 2019), and while often environmental, it causes opportunistic infections in patients with structural lung disease such as cystic fibrosis. It is also among the most difficult of all bacterial pathogens to treat because, in addition to forming persister cells, it is also intrinsically resistant to many classes of antibiotics, leaving few treatment options (Griffith et al., 2007). This leads to the use of antibiotics with greater toxicity to patients and a need to use these agents for prolonged periods to prevent relapse. Thus, identifying the genes that Mabs persister cells rely on for survival, as well as the genes involved in the induction and maintenance of stress-induced antibiotic tolerance, might highlight pathways that could be targeted therapeutically to eliminate antibiotic-tolerant cells.

Previous genetic screens have studied antibiotic responses in mycobacteria, with some evaluating heritable resistance and others investigating tolerance. Several studies of resistance have successfully used either transposon mutagenesis with insertion site sequencing (Tn-Seq) or CRISPR-based transcriptional repression with high-throughput sequencing of guide RNAs (CRISPRi) to identify genes promoting growth in subinhibitory concentrations of antibiotic. These studies have provided insights, such as highlighting the importance of cell membrane permeability as a mechanism controlling antibiotic penetration into the cytoplasm (Li et al., 2022; Carey et al., 2018; Rodriguez et al., 2023).

Persister formation has proven challenging to study, likely because the low frequency of persisters leads to population bottlenecks that confound genetic analysis. Although screens in Mtb have been conducted in macrophages and mice, and genes such as glpK and cinA identified, overall the number of mutants isolated in these screens has been low (Kreutzfeldt et al., 2022; Bellerose et al., 2019). There has been one effective in vitro Tn-Seq study examining antibiotic tolerance in Mtb exposed to starvation and rifampin that isolated over 100 mutants (Saito et al., 2021), demonstrating the feasibility of genetic screening in this context. However, whether these phenotypes seen with rifampin in Mtb extend to other mycobacteria and other antibiotics remains to be determined.

Here, we study antibiotic tolerance in Mabs and describe the results of genome-wide Tn-Seq screens seeking to identify the genes required for both spontaneous persister cell survival and starvation-induced antibiotic tolerance following exposure to translation-inhibiting antibiotics. We identified several discrete processes contributing to survival and observed a prominent role for ROS detoxifying factors, such as the catalase-peroxidase enzyme KatG, which contributed to both spontaneous persister survival and starvation-induced antibiotic tolerance. Consistent with the protection conferred by KatG, we found that endogenous ROS accumulated following antibiotic exposure and that the removal of oxygen significantly impaired bacterial killing. Taken together, these findings support a model in mycobacteria where the lethality of translation-inhibiting antibiotics is amplified by a secondary accumulation of toxic ROS, and survival requires active detoxification systems.

Results

Starvation-induced antibiotic tolerance in mycobacteria

We first sought to develop conditions suitable for genetic analysis of persister cell survival and stress-induced antibiotic tolerance in mycobacteria. Genetic screens examining persister cell physiology face two inherent obstacles. First, these cells are rare in unstressed bacterial populations, and antibiotic-mediated cell death creates population bottlenecks that obscure mutant phenotypes. Second, most mycobacterial populations contain spontaneous drug-resistant mutants that can expand if the population is exposed to a single antibiotic. To overcome these obstacles, we sought to establish large-scale, high-density culture conditions to prevent genetic bottlenecks, and used multiple antibiotics to suppress spontaneous drug-resistant mutants. We began by assessing the feasibility of this approach using wild-type Msmeg. We exposed the cells either to the combination of rifampin, isoniazid, and ethambutol (RIF/INH/EMB) used to treat Mtb, or to the combination of tigecycline and linezolid (TIG/LZD), two translation-inhibiting antibiotics frequently used to treat Mabs (Griffith et al., 2007; Kumar et al., 2022), and empirically determined the minimum inhibitory concentrations (MICs) and minimum bactericidal concentrations for each antibiotic. Both antibiotic combinations reduced the bacterial population >1000-fold within 72 hr (Figure 1A). We then evaluated both spontaneous persister formation and stress-induced tolerance under these conditions in Msmeg. We compared logarithmically growing (mid-log) cultures in 7H9 rich media to cultures starved for 2 days in phosphate-buffered saline (PBS) prior to the addition of antibiotics. Consistent with expectations, we found a marked increase in antibiotic tolerance in starved cultures, with a 100-fold increase in survival following TIG/LZD exposure and a 10,000-fold increase following RIF/INH/EMB exposure (Figure 1A).

Figure 1
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Starvation induces antibiotic tolerance in diverse mycobacteria.

(A) M. smegmatis (Msmeg), (B) M. tuberculosis (Mtb), or (C) M. abscessus (Mabs) were grown in 7H9 rich media or starved in phosphate-buffered saline (PBS) prior to the addition of antibiotics, and surviving colony-forming units (CFUs) enumerated. For the rapidly growing mycobacteria, Msmeg and Mabs, cells were allowed to adapt for 48 hr prior to antibiotics; for slow-growing Mtb, cells were allowed to adapt for 14–21 days prior to antibiotics. Samples without pre-adaptation were washed and placed directly into PBS with antibiotics. Antibiotic concentrations were: Msmeg – Isoniazid (INH) 32 μg/ml (8× minimum inhibitory concentration [MIC]), rifampin (RIF) 32 μg/ml (8× MIC), ethambutol (EMB) 4 μg/ml (8× MIC), tigecycline (TIG) 1.25 μg/ml (8× MIC), linezolid (LZD) 2.5 μg/ml (8× MIC). Mtb – RIF 0.1 μg/ml (4× MIC), INH at 0.1 μg/ml (4× MIC), EMB at 8 μg/ml (4× MIC). Mabs – TIG 10 μg/ml (8× MIC), LZD 100 μg/ml (20× MIC). Antibiotics with half-lives shorter than the duration of the experiment were re-added at the following intervals: TIG, EMB every 3 days; RIF, INH every 6 days. Error bars represent SEM; statistical significance is calculated at each time point using Student’s t test. ****: p<0.0001, ***: p<0.001, **: p<0.01, *: p<0.05, ns: p>0.05. Data are combined from 3 independent experiments.

We next examined two species of pathogenic mycobacteria to assess starvation-induced antibiotic tolerance. Both Mabs and Mtb have been shown to display this response, and we sought to determine whether this could be observed under the conditions needed to conduct a Tn-Seq screen (Yam et al., 2020; Berube et al., 2018; Lee et al., 2021; Betts et al., 2002). We again compared cells starved in PBS to logarithmically growing cells in 7H9 and found that, under these conditions, cultures of wild-type Mabs (ATCC 19977) and Mtb (Erdman) displayed dramatic increases in antibiotic tolerance in nutrient-deprived cultures (Figure 1B and C). Notably, for Mabs and Msmeg, the development of tolerance required an adaptation period of several days under starvation conditions, as survival was dramatically impaired if cells were shifted immediately into nutrient-deficient conditions with antibiotics, suggesting that a regulated process needed to be completed. Surprisingly, Mtb tolerance developed rapidly without pre-adaptation, suggesting that this organism might have additional response pathways enabling more rapid adaptation.

Identification of pathways needed for antibiotic tolerance in Mabs

We used these conditions to carry out Tn-Seq screens in Mabs to identify genes necessary for both the survival of spontaneous persister cells and starvation-induced antibiotic tolerance. We conducted the screen using a Mabs Himar1 Tn library comprised of ~55,000 mutations across ~91,000 possible TA insertion sites covering all 4992 Mabs genes in strain ATCC 19977 (Rodriguez et al., 2023). To study spontaneous persister cells, cultures were maintained in continuous log-phase in 7H9 rich media for 48 hr prior to antibiotic exposure and then exposed to TIG/LZD for 6 days (Figure 2A), a point at which spontaneous persister cells comprise the majority of the population (Figure 1C). To study starvation-induced tolerance, cultures were starved in PBS for 48 hr prior to antibiotic exposure in PBS. Following antibiotic treatment, cells were then washed and resuspended in antibiotic-free liquid media to recover and passaged 1:100 three times in continuous log-phase to expand surviving cells. We then isolated genomic DNA, sequenced the Tn insertion sites, and used TRANSIT software (DeJesus et al., 2015) to quantify the abundance of each Tn mutant across different conditions to identify genes with statistically significant differences in distribution. We identified 277 Mabs genes required for surviving TIG/LZD exposure in rich media, 271 genes required for survival during starvation, and 362 genes required to survive the combined exposure to antibiotics and starvation (log2 fold-change >0.5 and Benjamini-Hochberg adjusted p-value (p-adj.) ≤0.05) Of the genes required for survival, ~60% were required in both nutrient-replete and starvation states, although condition-specific determinants were also seen (Figure 2F). As expected, we identified genes with already-established functions in antibiotic responses, including MAB_2752 and MAB_2753, which are both homologs of known antibiotic transporters in Mtb, as well as tetracycline-responsive transcription factors like MAB_4687 and MAB_0314c (Supplementary file 1), indicating an ability of these Tn-Seq conditions to identify physiologically relevant genes known to mitigate antibiotic stress.

Figure 2
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Tn-Seq identifies genes required for antibiotic tolerance in M. abscessus (Mabs).

(A) Experimental design. (B–E) Tn-Seq analysis showing relative abundance of individual genes under the indicated conditions. For (B–D) gene abundance in each condition is measured relative to the input, with negative values for genes depleted in each experimental condition relative to the input. Log2 fold-change is on the x-axis with -log10 of the p-value on the y-axis. All cultures were fully aerated throughout the experiment, and cultures without antibiotics received an equal volume of DMSO. In (E), an additional comparison is made for phosphate-buffered saline (PBS) with antibiotics relative to the PBS condition. Genes with significant decreases in abundance are shown in color (p-adj.<0.05 and log2 fold-change>0.5) using the Benjamini-Hochberg adjustment for multiple hypothesis testing. (F) Number of genes essential in each condition relative to the input population. (G) Pathway enrichment analysis of the essential genes in each condition using the DAVID knowledgebase (p<0.05). Screens were run as 3 independent experiments, and the combined results analyzed. Antibiotic conditions were as described above. Created with BioRender.com.

To identify other cellular processes necessary for survival, we performed pathway enrichment analysis on the set of genes identified by Tn-Seq. We used the DAVID (Huang et al., 2009) analysis tool to perform systematic queries of the KEGG, GO, and UniProt databases to identify overrepresented processes and pathways. Interestingly, although cells were exposed to translation-inhibiting antibiotics, and no exogenous oxidative or nitrosative stress was applied, we identified a number of factors needed to combat these stresses in spontaneous persister cells. This included bfrB (bacterioferritin), ahpE (peroxiredoxin), and katG (catalase/peroxidase), as well as five components of the bacterial proteasome pathway, known to mediate resistance to nitrosative stress in Mtb (Darwin et al., 2003; Figure 2G, Supplementary file 2). We also identified multiple members of DNA-damage response pathways, including recF, recG, uvrA, uvrB, and uvrC. Examining genes required for starvation-induced tolerance, a number of the same pathways were again seen, and the mutant with the greatest survival defect in this context was mntH, a redox-regulated Mn2+/Zn2+ transporter implicated in peroxide resistance in other organisms (Shi et al., 2019; Hohle and O’Brian, 2009).

To independently confirm a role in antibiotic tolerance for a set of genes from diverse pathways that were identified by Tn-Seq, we selected a set of genes required for survival, representing several of the functional pathways identified, and used oligonucleotide-mediated recombineering (ORBIT) (Murphy et al., 2018) to disrupt their open reading frames. The initial genes selected were pafA (proteasome pathway), katG (catalase-peroxidase), recR (DNA repair), blaR (β-lactam sensing), and MAB_1456c (cobalamin synthesis). To control for nonspecific effects of antibiotic selection during the recombineering process, we created a control strain using ORBIT to target a non-coding intergenic region downstream of a redundant tRNA gene (MAB_t5030c). We then individually screened each of these mutants to determine if they displayed deficits in survival by exposing cells to TIG/LZD, either in rich 7H9 media or under starvation conditions, as had been done in the Tn-Seq screen. For four out of five mutants, we observed defects concordant with the Tn-Seq findings. For ΔkatG, we detected clear defects in survival as soon as 3 days after antibiotic exposure in either rich media or under starvation conditions, corroborating the results of our Tn-Seq analysis (Figure 3A). We observed similar, albeit smaller, defects in the ΔpafA, ΔMAB_1456c, and ΔblaR mutants under the conditions predicted by the screen (Figure 3B–D). We saw no survival defect in the ΔrecR mutant (Figure 3E). Additionally, we observed that the ΔblaR mutant, as well as the ΔpafA mutant, displayed a marked defect in resumption of growth after removal of antibiotics (Figure 3—figure supplement 1).

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Validation of Tn-Seq results.

(A–E) ORBIT homologous recombination was used to delete the indicated genes or to generate a control strain targeting a distant intergenic region distal to the nonessential tRNA gene MAB_t5030c. Each strain was either grown in 7H9 rich media or starved in phosphate-buffered saline (PBS) for 48 hr prior to the addition of antibiotics as indicated. The conditions tested here correspond to the conditions in the Tn-Seq analysis where a phenotype was observed. Comparisons in panels A–C are made to the same control strain but plotted independently for clarity. Error bars represent SEM; statistical significance is calculated at each time point using Student’s t test. ****: p<0.0001, ***: p<0.001, **: p<0.01, *: p<0.05, ns: p>0.05. Antibiotics were added as described above. Data are representative of 4 independent experiments.

To further confirm the role of katG and pafA, and exclude off-target effects of recombineering, we performed genetic complementation analysis by restoring a wild-type copy of each gene into the respective ΔpafA and ΔkatG mutants. In each case, we integrated a single copy of the wild-type gene, under the control of its endogenous promoter, into the genome at the L5 attB site (hereafter pafA+, katG+ strains), and constructed isogenic control strains with an empty vector integrated at the same site (hereafter pafA-, katG- strains). We confirmed expression of the re-introduced copy of each gene by RT-qPCR in the pafA+, and katG+ strains, and found expression within roughly 2-fold of endogenous wild-type levels (Figure 4A and D). We then challenged these strains with TIG/LZD as before. In rich media, where the ΔkatG mutants have a moderate survival defect, the katG+ strain had roughly a 50-fold increase in viable cells relative to the katG- strain. We then exposed cells to antibiotics under starvation conditions, where the ΔkatG mutant phenotype is more severe. Under these conditions, the katG- cells succumbed rapidly between 3 and 10 days after antibiotic exposure, with a 1000-fold decrease in viable cells relative to control cells, whereas the katG+ strain showed a near-complete restoration of antibiotic tolerance (Figure 4B). We analogously examined complementation of ΔpafA mutants, and although the phenotype of the ΔpafA mutant is less severe overall than a ΔkatG mutant, we saw a similar restoration of survival in pafA+ cells relative to pafA- cells (Figure 4E). We next evaluated whether the pafA- and katG- strains were overall more sensitive to the growth inhibitory effects of TIG/LZD, or whether they had specific defects in survival above the mean bactericidal concentration. We performed MIC determination for TIG and LZD individually for each strain, comparing the katG+/katG- and pafA+/pafA- strains. We found that the MICs for each of these strains were unchanged, demonstrating that these mutants were not more readily inhibited by these antibiotics (Figure 4C and F). Instead, they have more rapid kinetics of cell death at bactericidal concentrations, consistent with a specific defect in survival, and supporting a model whereby an initial growth-arresting inhibition of the direct antibiotic target can be uncoupled mechanistically from a distinct cell-death step, as has been seen with other antibiotic classes (Shee et al., 2022).

Figure 4
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Complementation analysis of katG and pafA mutants confirms their role in antibiotic tolerance.

(A) RT-qPCR analysis of katG expression in katG- (ΔkatG::pmv306), katG+ (ΔkatG::pmv306 katG), and control strain (ORBIT intergenic::pmv306). (B) Colony-forming unit (CFU) over time for katG+/katG- strains. (C) Minimum inhibitory concentrations (MICs) for katG+/katG- strains. (D) Expression of pafA in pafA- (ΔpafA::pmv306), pafA+ (pafA::pmv306 pafA), and control strain. (E) CFU over time for pafA+/pafA- strains. (F) MICs for pafA+/pafA- strains. Antibiotic concentrations in (A, B, D, E) are as described above. Error bars represent SEM; statistical significance is calculated at each time point using Student’s t test between katG+/katG- strains in (B) and between pafA+/pafA- strains in (E). ****: p<0.0001, ***: p<0.001, **: p<0.01, *: p<0.05, ns: p>0.05. Antibiotics were added as described above.

Reactive oxygen contributes to antibiotic lethality in Mabs

We next investigated the role of KatG and reactive oxygen in antibiotic tolerance more broadly. We began by assessing whether KatG conferred protection from other antibiotics with diverse mechanisms of action, selecting antibiotics that are used clinically for mycobacterial infections. Because katG- mutants showed the greatest defects in starvation-induced tolerance, we analyzed survival of katG+ and katG- strains in starvation-adapted cultures exposed to a panel of different antibiotics. Because both TIG and LZD act by inhibiting translation, we began by exposing cells to either TIG or LZD alone. As expected, the degree of bacterial killing was significantly less with either agent alone than when they are added in combination. Upon exposure to either of these antibiotics, the katG- cells died more rapidly than katG+ cells, though the final proportion of persister cells in the population was unchanged in katG- cells (Figure 5A). When we exposed cells to rifabutin, an RNA polymerase inhibitor, we saw a similar effect, with a 100-fold loss of viability in katG- cells relative to the katG+ cells (Figure 5B). In contrast, when we exposed cultures to either levofloxacin (topoisomerase inhibitor) or cefoxitin (β-lactam inhibitor of peptidoglycan cross-linking), katG had little to no effect on cell viability (Figure 5C and D). Thus, the role of KatG is context-dependent, suggesting that, in Mabs, some antibiotics generate oxidative stress that is ameliorated by KatG, while others do not.

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Reactive oxygen species (ROS)-mediated toxicity following antibiotic exposure.

(A–D) Analysis of katG+/katG- cells challenged with different antibiotics. Cells were starved in phosphate-buffered saline (PBS) for 48 hr and then exposed to the indicated antibiotic. (E) Flow cytometry of control cells exposed to tigecycline and linezolid (TIG/LZD) (4 hr in 7H9 media or 72 hr in PBS) and then stained with DAPI and the ROS-sensitive dye CellROX green; percentage CellROX-positive cells are indicated. (F) Survival over time for aerated and hypoxic cultures of M. abscessus (Mabs) after exposure to TIG/LZD. For hypoxia, cultures were allowed to gradually deplete oxygen until methylene blue dye became colorless on day 5, with antibiotics added 48 hr later. (G) Survival over time for bipyridyl-treated cells after exposure to TIG/LZD. Error bars represent SEM; statistical significance is calculated at each time point using Student’s t test. ****: p<0.0001, ***: p<0.001, **: p<0.01, *: p<0.05, ns: p>0.05. (A–D, F) display combined data from 3 independent experiments. (E, G) are representative data from 3 independent experiments.

The identification of katG as essential for cells to survive exposure to TIG/LZD suggests that ROS are present and causing damage. Although TIG and LZD are translation inhibitors that do not directly generate ROS, we evaluated whether they might nonetheless be triggering ROS accumulation as a secondary effect. We examined ROS levels in control Mabs using the ROS indicator dye CellROX, which is retained in cells when it becomes oxidized (McBee et al., 2017). At baseline, during log-phase growth in rich media, <2% of cells had ROS accumulation (Figure 5E). We saw a moderate increase in ROS accumulation in starved cultures, with roughly 7% of the population CellROX+. However, when cells were exposed to antibiotics, we saw a dramatic accumulation of ROS, with 57% of cells becoming CellROX+ when exposed to TIG/LZD in rich media and 33% of PBS-starved cells becoming CellROX+ when exposed to TIG/LZD. Taken together, these data indicate that translation inhibition does indeed have important downstream effects on cellular redox balance, with ROS accumulation that could be contributing to the lethal effects of antibiotics.

We next tested whether ROS were contributing to cell death by reducing ROS production and then assessing the impact on cell viability. A well-established system for studying hypoxia in mycobacteria is the Wayne model of gradual-onset hypoxia, whereby low-density cultures are inoculated in sealed vessels with minimal headspace. As the culture slowly grows, the soluble oxygen is consumed, resulting in the slow onset of hypoxia over several days, a process that can be monitored by the decolorization of methylene blue dye in the media (Wayne and Hayes, 1996). Under aerobic conditions in rich media, we observed the expected rapid killing of Mabs over the first 5 days with the combination of TIG/LZD, with more rapid loss of viability in KatG- cells. However, under hypoxic conditions, where ROS production is suppressed, we saw much slower bacterial killing. Importantly, under hypoxic conditions, katG- cells no longer had a survival defect relative to katG+ cells, supporting the hypothesis that translation-inhibiting antibiotics also cause secondary accumulation of lethal ROS in antibiotic-treated cells that need to be detoxified by KatG (Figure 5F).

We also evaluated whether other methods of alleviating ROS damage might enhance survival. The iron chelator 2,2’-bipyridyl has been shown in other contexts to reduce ROS-mediated damage by suppressing the reaction of H2O2 with Fe2+ that generates highly oxidizing hydroxyl radicals (Fenton reaction), and which has been shown to mitigate oxidative damage in other bacteria following antibiotic exposure (Kohanski et al., 2007; Shee et al., 2022; Winterbourn, 1995). As seen in other bacteria, we find that in Mabs, 2,2’-bipyridyl does indeed improve bacterial survival following exposure to bactericidal translation inhibitors, further supporting a role in ROS in cell death following translation inhibition (Figure 5G).

We also assessed whether free radical scavengers like thiourea and 4-hydroxy-2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) ameliorated antibiotic toxicity, although similar thiol antioxidants had previously been shown in Mtb to increase respiration and ROS generation and to paradoxically decrease bacterial survival upon INH exposure (Vilchèze et al., 2017). When we treated Mabs simultaneously with TIG/LZD in combination with either thiourea or TEMPO, we did not observe a restoration of antibiotic tolerance, and, similar to observations in Mtb, actually observed increased bacterial cell death (Figure 5—figure supplement 1).

Antibiotic-induced ROS accumulation is conserved, but reliance on KatG is variable among Mabs strains

To test whether ROS accumulation was an effect occurring more broadly across different Mabs strains, we obtained two clinical strains, exposed them to TIG/LZD in 7H9 media, and measured ROS accumulation with CellROX as above. We found that similar to ATCC 19977, both clinical Mabs strains had elevated ROS levels following translation inhibition (Figure 6A), suggesting that this is a conserved process in Mabs. Next, we tested the role of KatG in these Mabs clinical strains. We used ORBIT to disrupt the katG locus and evaluated the ability of these ΔkatG clinical strains to survive exposure to TIG/LZD under both stressed and unstressed conditions. Unlike ROS accumulation, where the responses across strains were consistent, we saw a variable dependency on katG. Clinical strain-1 behaved differently overall, with no appreciable starvation-induced antibiotic tolerance, and no contribution of katG to survival. In contrast, for clinical strain-2, katG contributed significantly to starvation-induced antibiotic tolerance, behaving similarly to the ATCC 19977 reference strain. However, unlike the reference strain, katG was not required for survival of clinical strain-2 when exposed to antibiotics in 7H9 media (Figure 6B). Thus, although antibiotic-induced ROS accumulation was observed across all three Mabs strains, the ΔkatG phenotype displays incomplete penetrance, suggesting that in some Mabs strains alternative pathways exist that are able to compensate for the loss of katG.

Figure 6
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Conserved antibiotic-induced reactive oxygen species (ROS) production but variable protection by KatG among different M. abscessus (Mabs) strains.

(A) The indicated strains of Mabs were cultured in 7H9 media, exposed to tigecycline and linezolid (TIG/LZD) for 4 hr and then analyzed by CellROX staining. (B) Colony-forming unit (CFU) over time following TIG/LZD exposure. Error bars represent SEM; statistical significance is calculated at each time point using Student’s t test. ****: p<0.0001, ***: p<0.001, **: p<0.01, *: p<0.05, ns: p>0.05. Combined data from 4 independent experiments are shown for persister survival experiments. Representative data from 2 independent experiments are shown for flow cytometry experiments. Antibiotics were added as described above.

Discussion

The results of these studies point to an important effect of ROS in amplifying the lethality of transcription and translation-inhibiting antibiotics in Mabs. Through genetic analysis, we identified a number of ROS detoxification factors, including KatG, as necessary for survival in this context. This suggested that antibiotics induced an oxidative state in cells, and direct measurement of ROS following antibiotic exposure indicated that this was indeed the case. Further supporting the toxic effects of ROS in this context, we found that removal of oxygen both slowed bacterial killing and rendered KatG dispensable. Taken together, these results suggest that in Mabs antibiotic lethality is accelerated by ROS accumulation, and that survival requires active detoxification systems.

Pathways necessary for antibiotic tolerance in Mabs

The phenomenon of antibiotic tolerance has been recognized for decades and has been observed in a broad array of bacterial species (Bigger, 1944; Zeng et al., 2022; Moyed and Bertrand, 1983; Viducic et al., 2006; Geiger et al., 2014; Dutta et al., 2019; Bhaskar et al., 2018; Wu et al., 2015) but without identification of a singular underlying mechanism conserved among species, suggesting that different pathways may play roles in different physiologic contexts. For example, the pathways identified in one bacterial species may not contribute to tolerance in another. In E. coli, relA plays an important role in stress-induced tolerance, as it does in Pseudomonas aeruginosa (Viducic et al., 2006), Staphylococcus aureus (Geiger et al., 2014), and Mtb (Dutta et al., 2019). However, its role is not universal. Deletion of relA had no effect on antibiotic tolerance in Msmeg (Bhaskar et al., 2018), and in our Tn-Seq analysis, Mabs relA Tn mutants had no survival defect. In the case of Mabs, this may be due to genetic redundancy, as a prior study of the Mabs relA mutant demonstrated that this strain still synthesizes (p)ppGpp (Hunt-Serracín et al., 2022). In addition, even within a single species, there can be differences in the critical survival mechanisms depending on the context. In E. coli, RelA contributes strongly to persister formation following exposure to β-lactams, but not aminoglycosides (Wu et al., 2015), and in our study, we find KatG to be essential for tolerance to transcription and translation inhibitors but not to a β-lactam (cefoxitin) or a quinolone (levofloxacin).

Mechanisms of antibiotic lethality

Our findings strongly support the idea that antibiotic-induced ROS can be a significant contributor to bactericidal activity in Mabs and contribute to the growing evidence that this phenomenon is conserved across diverse types of bacteria. In mycobacteria, other groups have observed that hypoxia reduced antibiotic-mediated killing in Mabs, Mtb, and Msmeg, and in Mtb, exposure to rifampin or moxifloxacin also generates ROS, with katG contributing to survival in rifampin-treated cells (Shee et al., 2022; Saito et al., 2021). Notably, we found evidence for ROS-mediated bactericidal activity with the translation-inhibiting antibiotics tigecycline and linezolid, as well as the transcription-inhibiting antibiotic rifabutin. This contrasts with findings in E. coli where the rifamycins and tetracyclines are not bactericidal and do not induce ROS (Kohanski et al., 2007; Dwyer et al., 2014), suggesting that mycobacteria-specific responses may exist that result in lethal ROS production.

Exactly how transcription or translation blockade leads to increased ROS is not known. In principle, any of several derangements could lead to ROS accumulation. One of the major sources of cellular ROS is oxidative phosphorylation, as hydrogen peroxide and superoxide are natural by-products. Thus, increased ROS generation by oxidative phosphorylation is an attractive hypothesis. Alternatively, particularly under starvation conditions, it is possible that antioxidants and ROS scavengers may become depleted, creating a more oxidizing environment. Our Tn-Seq analysis provides additional insight on this. We noted a small class of Tn mutants that were paradoxically protected from antibiotic lethality (Figure 2B). Prominent among this class of mutants were several independent components of the NADH dehydrogenase complex. Also known as Complex I of the electron transport chain, it is one of the key entry points for electrons into the oxidative phosphorylation pathway. The observation that mutants lacking this complex are protected suggests that decreasing flux through oxidative phosphorylation, with a concomitant decrease in ROS generation, may enhance survival during antibiotic exposure. A mechanistic understanding of how blockade of either transcription or translation leads to deranged oxygen utilization is an unresolved question that will require further study.

ROS accumulation is not universal following exposure to bactericidal antibiotics. While antibiotic-induced ROS is well documented, under some conditions, such as higher concentrations of antibiotic, multiple studies have also observed antibiotic lethality without ROS accumulation (Liu and Imlay, 2013; Keren et al., 2013; Mahoney and Silhavy, 2013; Ezraty et al., 2013). Similarly, prior studies have found that under certain conditions, E. coli mutants lacking catalase have defects in persistence (Goswami et al., 2006; Wang and Zhao, 2009; Hong et al., 2020), whereas under other conditions they do not (Liu and Imlay, 2013). In Mabs, the role of katG was also not uniform, as it had no impact on survival following exposure to levofloxacin or cefoxitin. Additional studies will be needed to determine whether levofloxacin and cefoxitin kill without generating ROS, or whether ROS is generated but effectively detoxified by other systems in the absence of katG. This latter possibility is suggested by our findings in Mabs clinical strains. While we saw ROS accumulation in all strains after TIG/LZD exposure, the role of katG was variable between the strains. This suggests that compensatory pathways likely exist and that in Mabs they can overcome the loss of katG.

Therapeutic implications

Mabs infections are particularly challenging to treat and frequently have poor outcomes (Griffith and Daley, 2022). Our results highlight several bacterial processes, such as the bacterial proteasome and ROS detoxification, which might be targeted therapeutically to reduce the survival of antibiotic-tolerant bacteria in patients with Mabs infection. Agents targeting these processes might not have any intrinsic antimicrobial activity alone but might act to disrupt the unique physiology required to survive antibiotics. This would represent a new therapeutic class of ‘persistence inhibitors’ that might act synergistically with traditional antibiotics to eliminate the subpopulation of cells that would otherwise remain viable, despite prolonged antibiotic treatment, in patients with Mabs and other chronic infections (Shee et al., 2022; Vilchèze et al., 2017).

Limitations

Tn-Seq has inherent drawbacks, including an inability to identify mutants in essential genes or in cases of genetic redundancy. Thus, there are likely genes needed for antibiotic tolerance in Mabs that were not identified in this study. In addition, we studied the response to a single class of antibiotic, focusing on the translation inhibitors often used to treat Mabs infections, and we studied only spontaneous persister cells and starvation-induced antibiotic tolerance. It is likely that examining other antibiotics, with different mechanisms of action, or different stresses that induce tolerance would identify additional genes contributing to survival and would allow identification of core pathways that might be shared in differing physiologic contexts of antibiotic and stress.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Gene (Mycobacterium abscessus)katGGenBank Accession CU458896MAB_2470c
Gene (M. abscessus)pafAGenBank Accession CU458896MAB_2183
Gene (M. abscessus)MAB_1456cGenBank Accession CU458896MAB_1456c
Gene (M. abscessus)blaRGenBank Accession CU458896MAB_2414c
Gene (M. abscessus)recRGenBank Accession CU458896MAB_0320
Strain, strain background (M. abscessus ATCC 19977)MabsATCC19977
Strain, strain background (M. abscessus)Mabs clinical strains 1 and 2This paperObtained from the Sacramento County Department of Public Health Mycobacteriology Laboratory
Strain, strain background (Mycobacterium smegmatis MC2 155)MsmegATCC700084
Strain, strain background (Mycobacterium tuberculosis Erdman)MtbATCC35801
Recombinant DNA reagentpkm444 (plasmid)Addgene108319ORBIT recombineering plasmid
Recombinant DNA reagentpkm496 (plasmid)Addgene109301ORBIT payload plasmid
Recombinant DNA reagentpmv306 (plasmid)Snapper et al., 1988Mycobacteria shuttle vector
Chemical compound, drugTigecycline (TIG)Chem Impex29737
Chemical compound, drugLinezolid (LZD)Chem Impex29723
Chemical compound, drugLevofloxacinSigma-Aldrich28266
Chemical compound, drugCefoxitinChem Impex1490
Chemical compound, drugRifabutinCayman Chemical16468
Chemical compound, drugRifampin (RIF)Sigma-AldrichR7382
Chemical compound, drugIsoniazid (INH)SupelcoI3377
Chemical compound, drugEthambutol (EMB)Thermo ScientificJ6069506
Chemical compound, drugCellROX greenInvitrogenC10444
Chemical compound, drugDAPIInvitrogenD9542
Chemical compound, drug2,2′-Bipyridyl-2,2′-Bipyridine (Bipyridyl)Sigma-AldrichD216305
Chemical compound, drugThioureaSigma-AldrichT7875
Chemical compound, drug4-Hydroxy-2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)Sigma-Aldrich176141
Software, algorithmTRANSITTRANSITRRID:SCR_016492
Software, algorithmDAVIDDAVIDRRID:SCR_001881

Bacterial strains and culture conditions

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Mabs ATCC 19977, clinical Mabs strains, and Msmeg (MC2 155) were grown in BD Middlebrook 7H9 media (liquid) or 7H10 media (solid) supplemented with 0.5% glycerol (Sigma) and 0.2% Tween-80 (Fisher) but without any OADC supplementation except for transformations. Sacramento clinical isolates were obtained from the Sacramento County Department of Public Health Mycobacteriology Laboratory. Confirmation of clinical isolates as Mabs was performed by amplifying the 16S rRNA locus and Sanger sequencing (Supplementary file 4). Mtb (Erdman) was grown in 7H9 (liquid) or 7H10 (solid) supplemented with 0.5% glycerol, 0.1% Tween-80, and 10% OADC (BD). All cultures were grown at 37°C with gentle shaking. Except for specific hypoxia conditions, all liquid cultures were grown with 90% container headspace or using a gas permeable cap to ensure culture oxygenation. PBS starvation was achieved by washing OD 0.5–1.0 Mabs 1× in DPBS (-Ca/Mg, Gibco) and resuspending in DPBS supplemented with 0.1% tyloxapol (Sigma) in 1/10th of the original culture volume. Colony-forming unit enumeration of all mycobacterial samples was done by taking 100 μl aliquots and disaggregating by sonication for 30 s at 80% amplitude in a Q500 sonicator with a cup horn attachment (Qsonica). Disaggregated samples were then serially diluted, and 2 μl spots of the dilution series were plated on solid 7H10 agar in triplicate. After incubation at 37°C for 3 days (Msmeg), 4 days (Mabs), or 20 days (Mtb), colonies were enumerated.

Mabs antibiotic experiments

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For PBS starvation experiments, stocks of Mabs were grown for 48 hr in 7H9, passaging continuously in log-phase, then either PBS starved or passaged in log-phase for an additional 48 hr. Log-phase or PBS-starved Mabs were then resuspended in antibiotic-containing media at OD 1.0. For experiments with hypoxia, Mabs in mid-log aerobic growth were adjusted to OD 0.001 in media with 1.5 μg/ml methylene blue and added to a rubber septum sealed glass vial with 50% headspace. Methylene blue discoloration was observed on day 3 and antibiotics were added on day 5. For thiourea and TEMPO experiments, these were added to the cultures at the time of antibiotic administration. For bipyridyl experiments, 62.5 μM bipyridyl was added to the cultures 2 hr prior to antibiotic administration. We empirically determined the half-life of each antibiotic in 7H9 media at 37°C and for those with half-lives shorter than the experiment, supplemented cultures with additional antibiotic to maintain the concentration of active antibiotic. Antibiotics were used at the following concentrations: tigecycline (Chem-Impex) at 10 μg/ml (8-fold above MIC, re-administered every 3 days), linezolid (Chem-Impex) at 100 μg/ml (20-fold above MIC), levofloxacin (Sigma) at 40 μg/ml (8-fold above MIC), cefoxitin (Chem-Impex) at 80 μg/ml (8-fold above MIC, re-administered every 3 days), and rifabutin (Cayman) at 40 μg/ml (4-fold above MIC). After antibiotic administration, colony-forming units over time were measured. For experiments where growth recovery time in liquid media was quantified, 100 μl of sample was removed at day 6 after antibiotic administration and washed 2× in antibiotic-free media. The samples were resuspended in 5 ml of antibiotic-free media, and OD 620 measurements were taken with a FilterMax F3 plate reader (Molecular Devices) until maximum cell density (OD of ~5.0) was reached.

Msmeg antibiotic experiments

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Individual colonies were picked and grown for 48 hr in log-phase before being PBS-starved or passaged in log-phase for 48 hr. Log-phase or PBS-starved Msmeg were then resuspended in antibiotic-containing media at OD 1.0. Antibiotics were used at the following concentrations: tigecycline (Chem-Impex) at 1.25 μg/ml (8-fold above MIC, re-administered every 3 days), linezolid (Chem-Impex) at 2.5 μg/ml (8-fold above MIC), rifampin (Sigma) at 32 μg/ml (8-fold above MIC, re-administered every 6 days), isoniazid (Sigma) at 32 μg/ml (8-fold above MIC, re-administered every 6 days), and ethambutol (Thermo) at 4 μg/ml (8-fold above MIC, re-administered every 3 days). After antibiotic administration, colony-forming units over time were measured.

Mtb antibiotic experiments

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Freezer stocks of Mtb were thawed and grown for 5–7 days in log-phase before being starved for 14 days or longer. Non-starved control Mtb were thawed such that they were also grown for 5–7 days in log-phase before experimental use. Log-phase or PBS-starved Mtb was then resuspended in antibiotic-containing media and adjusted to OD 1.0. Antibiotics were used at the following concentrations: rifampin (Sigma) at 0.1 μg/ml (4-fold above MIC, re-administered every 6 days), isoniazid (Sigma) at 0.1 μg/ml (4-fold above MIC, re-administered every 6 days), and ethambutol (Thermo) at 8 μg/ml (4-fold above MIC, re-administered every 6 days). After antibiotic administration, colony-forming units over time were measured.

Transposon insertion sequencing

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The construction of this Himar1 transposon Tn library has been described previously (Rodriguez et al., 2023). Screening was performed by growing a freezer stock of the library for 2.5 days in log-phase before 48 hr PBS starvation or further continuous log-phase growth. Samples were then resuspended in media containing either tigecycline/linezolid or an equal volume of DMSO solvent and incubated for 6 days, with a re-administration of tigecycline or matching DMSO on day 3. Cultures were aerated by culturing in a vented cap bottle with gentle agitation at 40 revolutions per minute throughout the experiment. The samples were then washed 2× in antibiotic-free liquid media, resuspended in antibiotic-free liquid media (10× the original culture volume), and grown until OD = 0.5–1.0. Subsequently, the samples underwent three more rounds of 100-fold passaging in liquid media to amplify surviving bacteria before the samples were collected in TRIzol (Invitrogen). A sample taken at the time of the commencement of PBS starvation was collected in TRIzol and used as the input control. Three independent trials of this experiment were submitted to the UC Davis DNA Technologies Core, where Tn insertion site flanking sequences were amplified as described previously (Rodriguez et al., 2023) and sequenced on an Element Biosciences AVITI. Sequence reads were mapped to the ATCC 19977 genome and analyzed using TRANSIT software with the following parameters: 0% of N/C termini ignored, 10,000 samples, TTR normalization, LOESS correction, inclusion of sites with all zeros, site-restricted resampling. Genes with significant changes were defined as those with adjusted p-value (p-adj.)<0.05 and log2 fold change>0.5. p-adj. was calculated using the Benjamini-Hochberg correction.

Pathway enrichment analysis

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To improve gene annotation, Mabs orthologs to Mtb genes were identified. Mabs genes were first converted into protein sequences using Mycobrowser, and protein sequences were then used to perform reciprocal BLASTp searches. Mabs genes and Mtb genes that mapped to each other using independent one-way BLASTp searches with a maximum e-value cutoff of 0.1 were considered orthologs. For pathway analysis, gene lists (Mtb orthologs) were then imported into the DAVID knowledgebase (Huang et al., 2009), and pathway enrichment analysis was performed for Gene Ontology biological process, UniProt keyword, and KEGG databases with statistical analysis assessed using Fisher’s exact test and nominal p-values reported.

Gene deletion and complementation

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Knockout strains were generated using ORBIT (Murphy et al., 2018). Briefly, Mabs was transformed with the kanamycin-resistant ORBIT recombineering plasmid pkm444. 20 ml Mabs at OD 0.5–1.0 was washed 2× in 10% glycerol and resuspended in 200 μl 10% glycerol. 500 ng plasmid was added and electroporated at 2.5 kV in 0.2 cm cuvettes. The bacteria were allowed to recover overnight before plating on 150 μg/ml kanamycin plates. Clones were selected and regrown in liquid media supplemented with 150 μg/ml kanamycin and 10% OADC (BD) to OD 0.5–1.0. For recombineering, the pkm444-Mabs was grown to mid-log, then diluted to OD 0.1 and 200 mM glycine (Fisher) was added to the media. 16 hr later, 500 mM sucrose (Sigma) and 500 ng/ml anhydrotetracycline (Cayman) were added and incubated for an additional 4 hr. Subsequently, the Mabs was washed 2× in ice-cold 10% glycerol+500 mM sucrose. 200 µl of 10× concentrated Mabs was then electroporated with 600 ng of the zeocin-resistance ORBIT payload pkm496 plasmid and 2 μg of targeting oligonucleotide (Supplementary file 3) at 2.5 kV in 0.2 cm cuvettes. The Mabs was then allowed to recover overnight in liquid media with 10% OADC and 500 ng/ml anhydrotetracycline before being plated on 150 μg/ml zeocin plates. Mutants were then selected and screened for gene deletion by PCR amplification and Sanger sequencing. For genetic complementation, the endogenous loci including promoter and terminator sequences were amplified by PCR and cloned into the EcoRV site of pmv306 with kanamycin resistance (Snapper et al., 1988). In the case of katG, the upstream gene furA was also included in the complementation construct to achieve optimal katG expression.

MIC determination

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Twofold serial dilutions of antibiotics were prepared in a 96-well plate in 100 µl volume. 100 µl of 2× bacteria were added (for Mabs: used a final OD of 0.001, Msmeg: OD 0.001, Mtb: OD 0.01), making a final volume of 200 μl. The plates were incubated until there was visible growth in the no-antibiotic control well. At this time, the bacteria were transferred to a new plate with 20 μl of 40% paraformaldehyde, and OD 620 measurements were taken with a FilterMax F3 plate reader (Molecular Devices). MIC values for wild-type ATCC 19977 under these conditions are listed in Supplementary file 5.

Flow cytometry

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A culture of OD = 1.0 Mabs was stained with CellROX green (Invitrogen) at a final concentration of 5 μM for 1 hr at 37°C. The cells were then washed in PBS and resuspended in PBS with 4% paraformaldehyde and 5 μg/ml DAPI (Sigma). The samples were run on an LSRII flow cytometer (BD). Fluorophores were excited with the 405 nm (DAPI) and 488 nm (CellROX) lasers. Detection was performed using the 450/50 (505LP) filter for DAPI and a 525/50 (555LP) filter for CellROX. Data were analyzed with FlowJo software (BD).

DNA/RNA purification

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Samples were resuspended in five volumes of TRIzol, and bead beat with 0.1 mm zirconia beads (Biospec) 6×2 min at 4°C in a Mini-Beadbeater-16 (Biospec). Chloroform was added, and RNA in the aqueous phase removed. For DNA isolation, a second RNA extraction was performed with 0.8 M guanidine thiocyanate and 0.5 M guanidine hydrochloride, 60 mM acetate pH 5.2, 1 mM EDTA. DNA was then isolated with back-extraction buffer (4 M guanidine thiocyanate, 50 mM sodium citrate, 1 M Tris base [without pH adjustment ~pH 11]) and purified using a PureLink RNA Mini Kit (Invitrogen).

RT-qPCR

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RNA was purified using PureLink RNA Mini Kit per the manufacturer’s instructions. The samples were DNAse I (NEB) treated for 15 min at 37°C before stopping the reaction by adding 3.5 mM EDTA and heating for 10 min at 75°C. cDNA was synthesized from 500 ng total RNA using random hexamers and Maxima H minus reverse transcriptase (Thermo). No reverse-transcription controls were also included and used to confirm the lack of genomic DNA-driven amplification. qPCRs used Taq polymerase (NEB) and EvaGreen (Biotium) and were run on Bio-Rad CFX Opus 96 Real-Time PCR System. Melt curves were included for each sample to confirm uniform amplicon identity between samples. Gene-specific amplification was quantified by comparison to a standard curve generated from 3-fold serial dilutions of a control sample, then normalized to 16S rRNA within each sample.

Data availability

Numerical source data for all figures has been deposited at Dryad.

The following data sets were generated
    1. Penn BH
    2. Bates N
    3. Rodriguez R
    4. Drwich R
    5. Ray A
    6. Stanley S
    7. Penn B
    (2026) Dryad Digital Repository
    Reactive oxygen detoxification contributes to Mycobacterium abscessus antibiotic survival.
    https://doi.org/10.5061/dryad.4xgxd25pv

References

Article and author information

Author details

  1. Nicholas A Bates

    1. Department of Internal Medicine, University of California, Davis, Davis, United States
    2. Graduate Group in Immunology, University of California, Davis, Davis, United States
    Contribution
    Conceptualization, Formal analysis, Visualization, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared

  2. Ronald Rodriguez

    1. Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    2. Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  3. Rama Drwich

    Department of Internal Medicine, University of California, Davis, Davis, United States
    Contribution
    Formal analysis, Visualization
    Competing interests
    No competing interests declared

  4. Abigail Ray

    Microbiology Graduate Group, University of California, Davis, Davis, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared

  5. Sarah A Stanley

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Contribution
    Methodology, Writing – review and editing
    Competing interests
    Scientific advisory board member for X-biotix Therapeutics
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4182-9048

  6. Bennett H Penn

    1. Department of Internal Medicine, University of California, Davis, Davis, United States
    2. Department of Medical Microbiology and Immunology, University of California, Davis, Davis, United States
    Contribution
    Conceptualization, Formal analysis, Funding acquisition, Validation, Methodology, Writing – original draft, Writing – review and editing
    For correspondence
    bhpenn@health.ucdavis.edu
    Competing interests
    Scientific advisory board member for X-biotix Therapeutics
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2458-5202

Funding

National Institute of Allergy and Infectious Diseases (R01AI144149)

  • Bennett H Penn

National Institute of Allergy and Infectious Diseases (R01AI143722)

  • Sarah A Stanley

National Heart Lung and Blood Institute (HL007013)

  • Abigail Ray

National Institutes of Health (1S10OD010786-01)

  • No recipients declared.

National Cancer Institute (P30CA093373)

  • No recipients declared.

Pew Charitable Trusts (Pew Biomedical Scholars Fellowship)

  • Bennett H Penn

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We would like to thank Nick Campbell-Kruger for his technical insights on identifying Mabs/Mtb orthologs, Jonathan Van Dyke for his assistance with flow cytometry analysis, Emily Kumimoto and Siranoosh Ashtari for their assistance with Tn-Seq library preparation and sequencing, and Jessie Li and Bradley Jenner for their assistance with Tn-seq bioinformatics. We would also like to thank Caroline Dominic at the Sacramento County Department of Public Health for providing clinical isolates of Mabs for analysis. This work was supported by a Pew Biomedical Scholars Fellowship BHP; NIH R01 1R01AI144149 BHP; NIH R01 1R01AI143722 SAS; NIH T32 HL007013 AR; NIH Shared Instrumentation Grant 1S10OD010786-01 DNA Technologies and Expression Analysis Core, UC Davis Genome Center; and NCI Cancer Center Support Grant P30CA093373 Flow Cytometry Shared Resource, UC Davis.

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  1. Nicholas A Bates
  2. Ronald Rodriguez
  3. Rama Drwich
  4. Abigail Ray
  5. Sarah A Stanley
  6. Bennett H Penn
(2026)
Reactive oxygen detoxification contributes to Mycobacterium abscessus antibiotic survival
eLife 14:RP104944.
https://doi.org/10.7554/eLife.104944.4

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