Stress-induced iron-sulfur cluster damage as a conserved trigger of the bacterial stringent response

Domain: chemistry
Published: 2026-03-02
Editorial outcome: major_revision

Abstract
Pathogenic bacteria rely on the stringent response to adapt to hostile environments
encountered within the host. However, the mechanisms by which host-induced stress
activates this response remain poorly understood. Here, we identify iron-sulfur (Fe-S)
cluster damage as a conserved trigger of the stringent response in major Gram-negative
pathogens, including Salmonella enterica, Enterobacter cloacae, and Klebsiella
pneumoniae. We demonstrate that Fe-S cluster disruption—triggered by oxidative stress
or metal imbalance—limits intracellular pools of sulfur-containing and branched-chain
amino acids, thereby activating the (p)ppGpp synthetase RelA. We further show that
during Fe-S cluster stress, (p)ppGpp plays a dual role: enhancing bacterial fitness and
promoting virulence by upregulating the Salmonella SPI-2 type III secretion system.
These findings reveal a conserved mechanism by which pathogenic bacteria integrate
host-associated stresses into an adaptive transcriptional response that promotes fitness
and virulence, highlighting Fe-S cluster integrity as a central hub for environmental
sensing during infection.

Introduction
To survive the hostile environments encountered within the host, bacterial pathogens
have evolved sophisticated strategies to sense and adapt to host-induced stresses (1).
One of the most conserved is the stringent response, which is mediated by the alarmone
guanosine tetra- or penta-phosphate, collectively known as (p)ppGpp. This second
messenger accumulates in response to nutrient starvation and transiently reprograms
bacterial physiology by modulating transcription, translation, and DNA replication (2–6).
Tight regulation of (p)ppGpp enables bacteria to balance growth and survival, positioning
the stringent response as a key adaptive strategy (7, 8). Consistently, mutants that fail to
properly regulate (p)ppGpp struggle to proliferate in host tissues and exhibit poor survival
during infection (3).

In γ-proteobacteria such as Salmonella enterica serovar Typhimurium (henceforth
Salmonella), (p)ppGpp levels are regulated by two enzymes: RelA, which synthesizes
(p)ppGpp in response to amino acid starvation, and SpoT, which both synthesizes and
degrades (p)ppGpp in response to various stress signals, including fatty acid and carbon
source starvation (9–12). An emerging body of evidence suggests that metal availability
also influences (p)ppGpp metabolism across several species, including Escherichia coli
(13), Salmonella enterica (14), Bacillus subtilis (15), Enterococcus faecalis (16),
Streptococcus pneumoniae (17), and Staphylococcus aureus (18). However, the
molecular mechanisms by which metal availability regulates the intracellular pool of
(p)ppGpp remain poorly understood.

Here, we demonstrate that disruption of iron–sulfur (Fe–S) clusters activates the stringent
response in clinically relevant γ-proteobacteria, including Salmonella enterica,
Enterobacter cloacae, and Klebsiella pneumoniae. We show that multiple environmental
stressors, such as oxidative stress and metal imbalance, promote (p)ppGpp accumulation
via the RelA protein by depleting branched-chain and sulfur-containing amino acids. This
response reprograms transcription to enhance stress adaptation and virulence, through
upregulation of the SPI-2 type III secretion system. Together, our findings establish a
mechanistic link between Fe–S cluster damage and (p)ppGpp signaling, uncovering how
bacterial pathogens sense and respond to environmental challenges during infection by
rewiring their physiology to promote virulence.

Results
Manganese stress triggers (p)ppGpp accumulation by restricting the
pool of amino acids

Since the stringent response has been associated with metal homeostasis in numerous
bacterial species (13–18), we hypothesized that fluctuations in metal availability could
trigger (p)ppGpp accumulation. To test this, we first identified conditions where
Salmonella experiences metal stress, either through starvation or excess, using growth
as an indicator of metal-induced stress.

We initially induced metal starvation by growing Salmonella in MOPS lacking magnesium
(-Mg), iron (-Fe), zinc (-Zn), copper (-Cu), manganese (-Mn), or cobalt (-Co). Surprisingly,
only Mg depletion significantly reduced bacterial growth in our conditions (Fig. S1a-e).
Because trace metals could potentially support Salmonella growth, we used specific
chelators: DIP (Fe), TPEN (Zn), and BCS (Cu) (19–21). Each chelator impaired bacterial
growth, which was restored upon supplementation with the corresponding metal,
confirming effective metal limitation (Fig. S1b-d). For Mn and Co, we were unable to
identify any specific chelators for which the exogenous addition of the corresponding
metal could restore growth. Beyond starvation, we also assessed whether metal excess
(+Mg, +Fe, +Zn, +Cu, +Mn, +Co) was toxic to Salmonella. We found that excess Zn, Cu,
Mn and Co severely inhibited bacterial growth, while supplementation with elevated levels
of Mg or Fe (1 mM) did not affect growth under our experimental conditions (Fig. S1f).

Next, we monitored activation of the stringent response under the identified metal stress
conditions by measuring (p)ppGpp accumulation using thin-layer chromatography (TLC).
To prevent indirect effects of stress on (p)ppGpp accumulation due to reduced uptake of
radioactive ³²P, we first cultivated Salmonella with ³²P under non-stress conditions
(MOPS). This approach ensured efficient incorporation of the radiolabel into the
nucleotide pool, as evidenced by successful labeling of GTP (first lane in Fig. 1a). Then,
we diluted the radiolabeled Salmonella into stress-inducing conditions and monitored
variations in (p)ppGpp levels. Of the eight conditions tested, only the excess of Mn
triggered (p)ppGpp accumulation, independently of its associated counterion (Fig. 1a, Fig.
S1g).

To determine whether (p)ppGpp production was mediated by RelA or SpoT, we monitored
(p)ppGpp levels in a relA deletion mutant (ΔrelA) and in a strain containing a synthetase-
dead version of SpoT (spoT ) during Mn intoxication (22). While no difference was
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observed between the WT and the spoT mutant, the absence of RelA completely
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abolished (p)ppGpp accumulation in response to elevated levels of Mn (Fig. 1b). Since
RelA is primarily activated during amino acid starvation by uncharged tRNAs entering the
ribosomal A-site (23, 24), we tested whether the addition of tetracycline, an antibiotic that
blocks the entry of uncharged tRNAs into the A-site, could prevent RelA activation under
our conditions (Fig. 1c). In agreement with this hypothesis, tetracycline completely
abolished (p)ppGpp accumulation in the presence of elevated Mn levels (Fig. 1c-d).
Furthermore, supplementation with amino acids completely abolished (p)ppGpp
accumulation and rescued the associated growth defect of Mn-intoxicated cells (Fig. 1d-
e). Together, these results show that excess Mn triggers RelA-dependent (p)ppGpp
production by restricting the pool of amino acids.

Disruption of Fe-S clusters leads to (p)ppGpp accumulation in Mn-
intoxicated cells

Previous studies have suggested that Mn toxicity stems from its ability to outcompete Fe
for binding sites on proteins that cannot use Mn as a cofactor (25, 26). For instance, Mn
excess has been shown to interfere with heme synthesis, leading to depletion of
cytochrome oxidase activity and ultimately to the failure of aerobic respiration (25). To
determine whether Mn intoxication triggers the stringent response by disrupting bacterial
respiration, we measured (p)ppGpp levels after treating cells with potassium cyanide
(KCN), which inhibits cytochrome oxidase by binding to its iron center (27). Similar to Mn
excess, KCN treatment led to RelA-dependent (p)ppGpp accumulation (Fig. S2a), which
was fully abolished by the addition of tetracycline or amino acids (Fig. S2b). To test
whether this accumulation resulted specifically from cytochrome oxidase inhibition, we
examined a strain lacking all three terminal cytochrome oxidases (ΔcyoAΔcydBΔappB).
Although this strain exhibited a severe growth defect (Fig. S2c), we did not observe any
increase in (p)ppGpp levels in the absence of stress (Fig. S2d). Moreover, this strain
accumulated (p)ppGpp in the presence of KCN or excess Mn (Fig. S2d), indicating that
inhibition of cytochrome oxidases is not the trigger for (p)ppGpp accumulation under
these conditions.

Beyond heme synthesis, we reasoned that Mn might also directly interfere with Fe-S
cluster-containing proteins (Fig. 2a). To explore this hypothesis, we performed aconitase
assays, as aconitase activity depends on a functional Fe–S cluster (28). In agreement
with previous work (26), Mn excess led to reduced aconitase activity, supporting a
negative impact of Mn on Fe–S cluster-containing proteins (Fig. 2b). Interestingly, it has
been shown that disruption of Fe-S clusters causes multiple auxotrophies (29), a
phenotype we also observed under Mn intoxication (Fig. 1e). This effect can be explained,
at least in part, by the inactivation of the Fe-S-dependent enzymes dihydroxyacid
dehydratase (IlvD) and isopropylmalate dehydratase (LeuC), which are involved in the
biosynthesis of the branched-chain amino acids isoleucine, leucine, and valine (ILV) (24,
30–32) (Fig. 2a). In line with this model, we observed a rapid decrease in the pool of
branched-chain amino acids in Mn-intoxicated cells (Fig. 2c). However, supplementation
with ILV only partially rescued growth under Mn stress, suggesting additional
auxotrophies (Fig. 2d). Since Fe-S cluster biogenesis requires sulfur atoms from amino
acids (Fig. 2a), we wondered whether the addition of the sulfur-containing amino acids
cysteine (C) and methionine (M) could reduce Mn toxicity. In contrast with ILV
supplementation, we observed that addition of CM substantially rescued bacterial growth
in the presence of elevated Mn levels (Fig. 2d). These results suggest that sulfur-
containing amino acids mitigate Mn toxicity by promoting the regeneration of a functional
pool of Fe-S clusters. To test this hypothesis, we deleted hscA, which encodes a
chaperone involved in Fe-S cluster maturation (33, 34), and tested whether CM
supplementation could still rescue bacterial growth under Mn excess in this genetic
background. As expected, the growth defect of ΔhscA under Mn excess was not rescued
by supplementation with sulfur-containing amino acids (Fig. 2e), supporting that cysteine
and methionine mitigate Mn toxicity by supplying sulfur atoms required for Fe-S cluster
assembly. In addition, the hscA mutant also displayed a higher susceptibility than the WT
to Mn toxicity (Fig. S3a-b), leading to (p)ppGpp accumulation at lower doses (Fig. S3c),
which emphazise the importance of Fe-S assemblRy during Mn excess. Remarkably, the
combined supplementation of both branched-chain (ILV) and sulfur-containing (CM)
amino acids provided the most effective protection against Mn-induced growth inhibition
(Fig. 2d). These findings suggest that Mn-induced damage to Fe-S clusters results in
multiple auxotrophies: one arising from the loss of Fe-S-dependent enzymes required for
ILV biosynthesis, and another reflecting increased cellular demand for sulfur donors to
support Fe-S cluster synthesis.

Since reducing environments promote Fe-S cluster assembly and stability in vitro (35,
36), we hypothesized that the addition of the reducing agent thiourea might help bacteria
preserve a functional pool of Fe-S cluster-containing proteins, thereby limiting the
subsequent activation of RelA. Consistent with this hypothesis, we observed that addition
of thiourea abolished (p)ppGpp accumulation in Salmonella during Mn stress (Fig. 2f).
Interestingly, thiourea also prevented the elevation of (p)ppGpp levels in response to KCN
(Fig. S3d), which also interferes with Fe-S cluster-containing proteins due to its strong
binding to iron atoms (37). As a control, we confirmed that thiourea had no effect on
(p)ppGpp accumulation induced by serine hydroxamate (SHX), a serine analog that
triggers amino acid starvation by inhibiting seryl-tRNA synthetase (38) (Fig. 2f). In line
with these assays, thiourea specifically alleviated the growth defects associated with
excess Mn, supporting the functionality of Fe-S cluster-containing proteins under these
conditions (Fig. 2g, S3e). Likewise, another reducing agent — ascorbic acid — also
effectively suppressed Mn-induced growth defects (Fig. S3f). Thus, these data support
the role of Fe-S cluster status in regulating (p)ppGpp levels in Salmonella.

Next, we investigated if other clinically relevant Gram-negative pathogens could modulate
the stringent response in response to Fe-S cluster damage. To test this, we measured
(p)ppGpp levels in two other pathogenic γ-proteobacteria, Enterobacter cloacae and
Klebsiella pneumoniae, in the presence or absence of Mn excess. Similar to our findings
in Salmonella, we observed that Mn excess and SHX induced (p)ppGpp accumulation in
these species (Fig. 2h-i, S3g-h). Moreover, supplementation with thiourea completely
abolished (p)ppGpp accumulation during Mn stress, but not in the presence of SHX (Fig.
2h-i, S3g-h). Collectively, these results indicate that the regulation of the stringent
response by Fe-S cluster damage is not limited to Salmonella but is also conserved
across other clinically relevant pathogens.

Iron limitation promotes the stringent response upon conditions
inducing Fe-S cluster damage

Having identified that the disruption of Fe-S clusters homeostasis can elevate (p)ppGpp
levels, we wondered why iron starvation did not lead to (p)ppGpp accumulation under our
experimental conditions (Fig. 1a). One possibility is that pre-existing Fe–S clusters are
sufficient to sustain amino acid metabolism during iron starvation, thereby preventing
RelA activation. To test this hypothesis, we quantified branched-chain amino acids under
conditions of iron limitation and manganese excess. Although both conditions restricted
bacterial growth (Fig. S1b,f), the intracellular BCAA pool decreased only in Mn-intoxicated
cells and not in iron-starved bacteria (Fig. 3a). These data explain why bacteria fail to
stimulate RelA activity during iron starvation, in contrast to Mn excess.

Since iron is required for Fe–S cluster assembly, we reasoned that restricted iron
availability could influence the stringent response under conditions that destabilize Fe–S
clusters and necessitate their de novo biogenesis. To investigate this hypothesis, we first
identified a condition that induces a transient disruption of Fe-S clusters which allows
bacteria to resume growth after stress. We found that the addition of 0.5 mM Mn
significantly extends the lag phase of Salmonella but allows recovery, supporting that
bacteria successfully restored a functional pool of Fe-S clusters (Fig. 3b). Under these
conditions, (p)ppGpp levels rise rapidly in response to Mn excess and return to their pre-
stress levels within two hours (Fig. 3c, S4). In contrast, higher concentrations of Mn (1
mM) were bacteriostatic and led to the maintenance of elevated levels of (p)ppGpp over
time (Fig. 3b-c). Next, we determined how iron availability might affect the recovery of
Salmonella after mild Mn excess. To reduce iron availability in the medium, we used a
concentration of the Fe-chelator DIP that does not affect bacterial growth in the absence
of stress (Fig. 3d). Strikingly, limiting iron availability using DIP drastically increased the
lag phase following mild Mn excess and promoted the maintenance of the stringent
response, as observed at higher concentrations of Mn (Fig. 3d-e).

We next wondered whether iron limitation might also extend the stringent response under
infection-relevant stresses that destabilize Fe-S clusters. To explore this, we examined
the role of iron availability during oxidative stress, which destabilizes Fe-S clusters (39,
40) and elevates ppGpp levels via RelA by generating an amino acid starvation (41) (Fig.
S5a-d). In line with our model, iron limitation drastically delayed bacterial regrowth
following mild H₂O₂ stress and led to the maintenance of elevated levels of ppGpp over
time (Fig. 3f-g). Remarkably, both phenotypes were also observed during more severe
H₂O₂ stress (Fig. S5e-f). Given the similar response of Salmonella treated with Mn
excess or H₂O₂ , we examined whether Mn excess induces oxidative stress under our
experimental conditions. Using the PkatG_gfpOVA ROS-specific biosensor (42) in the WT
strain, we observed robust GFP accumulation following H₂O₂ treatment but no increase
after Mn exposure (Fig. S5g), indicating that Mn stress does not generate oxidative stress
in our experimental conditions.

To extend our findings to other pathogens, we performed the same approach for
Enterobacter cloacae and Klebsiella pneumoniae, both of which accumulating (p)ppGpp
in response to Fe-S cluster damage (Fig. 2h-i, S3g-h). As shown for Salmonella, we
observed that both species accumulate ppGpp – but not pppGpp – in response to H₂O₂
exposure and that limiting iron availability with DIP delayed bacterial recovery and
promoted the stringent response, as observed when H₂O₂ concentration was higher (Fig.
3h-i, S6a-b). Collectively, these findings demonstrate that (p)ppGpp levels are regulated
by iron availability, which governs the ability of bacteria to regenerate a functional pool of
Fe–S clusters following stress exposure, especially during oxidative stress.

Elevated (p)ppGpp levels reprogram bacterial transcription in response
to Fe-S cluster damage

Our previous data demonstrated that Fe–S cluster damage dynamically modulates
(p)ppGpp levels. However, whether activation of the stringent response contributes to
bacterial fitness under these conditions remained unclear. To address this, we first
compared WT and ΔrelA strains under Mn excess. High Mn concentrations exerted a
bacteriostatic effect on both strains (Fig. S7a). While WT and ΔrelA displayed similar
growth in the absence of stress, the ΔrelA mutant failed to grow at Mn concentrations that
still supported WT growth (Fig. 4a, S7b). Similarly, under oxidative stress, ΔrelA was
unable to grow at concentrations that allowed WT growth (Fig. 4a), supporting the idea
that (p)ppGpp contributes to bacterial fitness under conditions that damage Fe–S
clusters. We also tested the ability of both strains to produce an inducible GFP in the
presence or absence of stress. While GFP production was comparable between strains
in the absence of stress, both Mn excess and H₂O₂ completely abolished GFP synthesis
in ΔrelA but not in the WT strain, which sustained substantial GFP expression under
stress (Fig. 4b). Together, these results demonstrate that (p)ppGpp accumulation
enhances bacterial fitness following Fe–S cluster damage and allows the maintenance of
essential cellular functions such as transcription and translation.

Next, to elucidate how (p)ppGpp facilitates adaptation under Fe-S cluster damaging
conditions, we performed RNA-seq on WT and ΔrelA strains exposed to Mn excess. We
selected Mn over H₂O₂ to avoid confounding effects from ROS-specific genes (e.g., katG)
and used a mild Mn concentration (0.5 mM) that induces (p)ppGpp accumulation (Fig.
3b) while still permitting transcriptional activity in the ΔrelA mutant (Fig. S7c),
thereby minimizing transcriptomic artifacts. Under these conditions, the WT strain significantly
upregulated 255 coding sequences (CDS) and downregulated 55 CDS, whereas the
ΔrelA mutant only upregulated 33 CDS and downregulated 32 CDS (Fig. 4c-d, S7d-f;
Supplementary Data 1-4). As expected, both strains similarly upregulated mntP
(formerly yebN), which encodes the main bacterial Mn efflux pump and is under the control of the
MntR regulator (43) (Fig. 4e). This confirmed that both strains experienced Mn stress and
validated that our experimental conditions still allowed the ΔrelA strain to mount a
transcriptional response to environmental cues. Additionally, both strains upregulated the
iscR regulon (Fig. 4e), which governs Fe-S cluster biogenesis (33, 34) and is activated
under conditions that compromise Fe-S cluster integrity (44). Together, these data ruled
out the possibility that the increased Mn susceptibility of ΔrelA results from defective
expression of mntP or the iscR regulon.

Despite both strains upregulating mntP and the iscR regulon, the WT exhibited a broader
transcriptional response (Fig. 4c-d, S7d-f; Supplementary Data 1-4). Our analysis
revealed significant upregulation of genes involved in substrate transport, metabolism,
signal transduction, and stress responses (Fig. 4f). In accordance with previous work (45–
47), we also observed increased expression of the SPI-2 type III secretion system (SPI2
T3SS) apparatus (Fig. 4g-h), which is essential for intracellular survival within
macrophages and the establishment of systemic infection by Salmonella (48, 49). This
induction was exclusive to the WT strain and absent in the relA mutant (Fig. 4h),
suggesting that perturbation of Fe-S cluster homeostasis may serve as a (p)ppGpp-
mediated signal to promote SPI2 T3SS assembly during infection. In agreement with this
hypothesis, a similar trend was observed under mild H₂O₂ stress (Fig. S7g). Together,
these findings highlight how (p)ppGpp enhances bacterial fitness by reprogramming
transcription to support stress adaptation and virulence.

Methods
Bacterial strains and plasmids
Oligonucleotides, strains, and plasmids used in this study are listed in Supplementary
Tables 1, 2, and 3. Additional construction details are provided in the Supplementary
Methods. E. coli EC100D pir-116 was used for cloning purposes with pTOX2 and grown
aerobically at 37°C in Luria–Bertani (LB) broth (Sigma) supplemented with 2% glucose.
Salmonella strains were grown aerobically at 37°C in either LB or MOPS minimal medium
(40 mM MOPS buffer, 0.4 mM tricine, 0.4 mM K₂HPO₄, 10 µM FeSO₄•7H₂O, 9.5 mM
NH₄Cl, 276 µM K₂SO₄, 500 nM CaCl₂, 525 µM MgCl₂, 50 mM NaCl, 2.9 nM
(NH₄)₆Mo₇O₂₄•4H₂O, 400 nM H₃BO₃, 30 nM CoCl₂, 9.6 nM CuSO₄, 80.8 nM MnCl₂,
and 9.74 nM ZnSO₄; pH 7.2), supplemented with 0.2% glucose as the sole carbon source
(referred to as MOPS throughout the manuscript). When indicated, the medium was
supplemented with additional compounds at the following concentrations: amino acid (aa)
mixture (40 µg/ml of each aa), thiourea ( 100 mM), reduced glutathione (50 mM), ascorbic
acid (50 mM), serine hydroxamate (SHX, 0.4 mg/ml), MnSO₄ (0.5 or 1 mM), H₂O₂ (0.5,
1, or 2 mM), MgCl₂ (1 mM), FeSO₄ (1 mM), ZnSO₄ (1 mM), CuSO₄ (1 mM), CoCl₂ (1
mM), MnCl₂ (1 mM), N,N,N',N'-tetrakis(2-pyridylmethyl)ethylenediamine (TPEN,
200µM), bathocuproinedisulfonic acid disodium salt (BCS, 100 mM) and 2,2'-dipyridyl
(DIP, 0.1 mM or 1 mM). Electrocompetent cells were used for the transformation of E. coli
and Salmonella. Antibiotics were used at the following concentrations where appropriate:
ampicillin (100 µg/ml), kanamycin (50 µg/ml), and chloramphenicol (34 µg/ml).
Genomic mutations were construct with pTOX2 vectors as previously described (56).
Briefly, the E. coli donor strain was mixed with the Salmonella recipient strain at a 1:5 or
1:20 ratio in a total volume of 1 ml. Cells were centrifuged at 6,000 g for 2 minutes, and
the supernatant was discarded. The remaining 100 µl was plated on LB agar containing
0.3 mM diaminopimelic acid (DAP) and 2% glucose and incubated at 37°C for 4 hours.
Subsequently, cells were scraped and restreaked on LB plates containing 2% glucose
and chloramphenicol. Single Salmonella colonies were then restreaked on LB with 2%
rhamnose. Finally, chloramphenicol-sensitive (CamS) clones were screened by PCR.

Growth assays
Bacteria were grown overnight in MOPS. The overnight culture (10 µl) was diluted into
500 µl of fresh MOPS, supplemented with additional compounds when indicated. 200 µl
of each sample was transferred into a flat-bottom 96-well plate (Greiner). Optical density
at 600 nm (OD₆₀₀ ) was measured every hour for 15 hours at 37°C using a plate reader
(BioTek Epoch 2). For panel 4a, Salmonella strains (WT or ΔrelA) were grown overnight
in MOPS. Then, 10 µl of the overnight culture were diluted in 500 µl of MOPS
supplemented with MnSO₄ (0, 0.5 or 1 mM) or H₂O₂ (0, 1 or 2 mM) in 1.5 ml eppendorf.
Samples were incubated in thermal shaker at 37°C with shaking for 15 hours before
OD₆₀₀ measurement.

Measurement of (p)ppGpp
Bacteria were grown overnight in MOPS. The overnight culture was then diluted 1:50 in
fresh MOPS (100 µl of overnight culture into 5 ml) and incubated aerobically at 37°C for
90 min. Next, 20 µl of a 1 mCi KH₂³²PO₄ solution was added to 480 µl of bacterial culture,
and the cells were incubated aerobically at 37°C for 60 min. Following incubation, cells
were pelleted by centrifugation at 16,000 g for 3 min and resuspended in 25 µl of MOPS.
For stress treatment, 5 µl of resuspended cells were diluted in 100 µl of MOPS containing
the indicated stress conditions and incubated at 37°C with shaking for 30 min. After
incubation, 40 µl of ice-cold 50% formic acid was added to each sample, thoroughly
mixed, followed by an additional 30-minute incubation on ice. Samples were then
centrifuged at 16,000 g for 5 minutes and then returned to ice. For thin-layer
chromatography (TLC), 2.5 µl x4 of each sample was spotted onto a polyethyleneimine
(PEI) cellulose plate (Macherey-Nagel). The PEI plates were developed in 1.25 M
KH₂PO₄ (pH 3.4) at room temperature. Finally, TLC plates were air dried, wrapped in
plastic and exposed against MS Storage Phosphor Screen (GE Healthcare) overnight.
Phosphor screen were visualized using an Amersham Typhoon (Cytiva). Spot intensities
were quantified with ImageJ software. Background was always subtracted from the
original value before further calculation.

Aconitase assays
Aconitase activity was measured using an Aconitase Activity Assay Kit (Abcam) 
according to the manufacturer’s instructions with minor modifications. Briefly, WT bacteria
were grown in MOPS medium, and 1 mL of culture was diluted into 10 mL of fresh MOPS
and incubated for 90 min at 37 °C with shaking. Cultures were then divided into two 5 mL
aliquots, and 1 mM MnSO₄ was added to one aliquot while the other served as the
untreated control. After 30 min incubation at 37 °C with shaking, 1 mL of cells from each
condition was harvested, washed once with cold PBS, and resuspended in 100 µL of
assay buffer 7. Following a 20 min incubation on ice, samples were supplemented with
10 µL of aconitase activation solution and incubated on ice for 60 min. Activated samples
(50 µL) were mixed with 50 µL of reaction mix and incubated at 25 °C for 60 min, after
which 10 µL of developer II was added and samples were incubated for an additional 10
min at 25 °C. Reactions were centrifuged for 3 min at 16,000 g, and 50 µL of the
supernatant was transferred to a 96-well plate for measurement at 450 nm. Blank values
were subtracted from raw OD readings, and results were normalized to the control.

Branched-Chain Amino Acids (BCAA) quantification
Branched-chain amino acids (BCAAs) were quantified using a Branched-Chain Amino
Acid Assay Kit (Abcam) according to the manufacturer’s instructions, with minor
modifications. Briefly, wild-type (WT) bacteria were grown in MOPS medium, and 1 mL
of culture was diluted into 10 mL of fresh MOPS and incubated for 90 min at 37 °C with
shaking. Cultures were then treated with or without 1 mM MnSO₄ or 1 mM 2,2′-dipyridyl
(DIP) and further incubated at 37 °C with shaking. At the indicated time points, 1 mL of
cells from each condition was harvested, washed once with cold PBS, resuspended in
200 µL of assay buffer 4, and lysed using a FastPrep instrument (2 × 30 s at 6.0 m s⁻¹).
Lysates were centrifuged for 3 min at 16,000 g, and 50 µL of the resulting supernatant
was mixed with 50 µL of reaction mix in a 96-well plate and incubated for 30 min at room
temperature. Absorbance was measured at 450 nm. Blank values were subtracted from
raw OD readings, and results were normalized to the untreated control.

Fluorescence accumulation in Salmonella
Salmonella strains (WT or ΔrelA) containing the pFCcGi reporter were grown overnight
in MOPS with ampicillin. Bacteria were then diluted (1:50) in MOPS containing 0.2 %
glycerol instead of glucose and grow aerobically for 90 min at 37°C. Then, media was
supplemented with MnSO₄ (0.5 or 1 mM) or H₂O₂ (0.5 or 1 mM). After 30m of stress, 0.2
% arabinose was added to the media to induce the production of GFP. Each sample was
collected after 30 min of induction and stored at 4°C in PBS prior analysis on an Attune
NxT flow cytometer.

Promoter activity assay
Salmonella strain containing the PkatG_gfpOVA was grown overnight in MOPS and
ampicillin. Bacteria were then diluted in MOPS (20 µl overnight in 1 ml) and grow
aerobically for 90 min at 37°C. Then, media was supplemented with 0.5 mM H₂O₂ and/or
0.1 mM DIP. Each sample was collected after 30 min of stress exposure and stored at
4°C in PBS prior analysis on an Attune NxT flow cytometer.

Survival assay
Salmonella strains (WT or ΔrelA) were grown overnight in MOPS. Bacteria were then
diluted in MOPS (1:50) and grow aerobically for 90 min at 37°C. Then, media was
supplemented with 1 mM MnSO₄ for 4 hours. Ten-fold serial dilutions in PBS were
performed and drops of 20 μl were plated on LB agar to determine the number of CFU
before (T0) and after Mn treatment (T4).

RNA-Seq and analysis
Salmonella strains (WT or ΔrelA) were grown overnight in MOPS in three biological
replicates. Bacteria were then diluted in MOPS (1:50) and grow aerobically for 90 min at
37°C to reach an OD of 0.2-0.3 in 50 ml. Then, media was supplemented with 0.5 mM
MnSO₄. After 30 min of stress, bacteria were centrifuged and the pellets froze at -80°C.
RNA extraction was performed using the zymo kit for quick RNA extraction. DNase
treatment was carried out using the Turbo DNase kit from Invitrogen. After quality
checking with a TapeStation (Agilent), RNA samples were sent to Genewiz for rRNA
depletion, followed by cDNA library preparation and strand-specific RNA sequencing.
Raw data were paired, trimmed, and mapped against the reference genome of
Salmonella enterica serovar Typhimurium (accession numbers CP001362 and
CP001363) using CLC software (Qiagen). Differential expression analysis (DE) and
volcano plots were generated using CLC, with a chosen cutoff of log2 fold change and
FDR < 0.05 to narrow down the deregulated transcripts. Unsupervised heatmaps were
generated using the mean of Transcript Per Million (TPM) in log of each condition. RNA-
seq analysis comparing MOPS medium to excess manganese (0.5 mM MnSO₄) is
presented in Supplementary Data 1 (WT) and Supplementary Data 2 (ΔrelA). RNA-seq
analysis comparing WT to ΔrelA is presented in Supplementary Data 3 (MOPS medium)
and Supplementary Data 4 (0.5 mM MnSO₄). For qRT-PCR validation, expression levels
of selected mRNA targets were quantified by one-step quantitative reverse transcription
PCR (qRT-PCR) using the Power SYBR® Green RNA-to-CT™ 1-Step Kit (Thermo Fisher
Scientific), according to the manufacturer’s instructions. Primer sequences are listed in
Supplementary Table S1. Relative transcript levels were calculated using the ΔΔCt
method and normalized to the housekeeping gene rfaH.

Data availability
Raw and processed RNA-seq data have been deposited in the Gene Expression
Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI)
under accession number GSE305564
(https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE305564). Data generated in
this study are provided in the source data file. Biological materials are available upon
request to the corresponding author.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Michaud et al report disruption of iron-sulfur clusters as a mechanism by which the stringent response is elicited. The\ninvestigators show that the overload of manganese stimulates the RelA-dependent production of the (p)ppGpp. Induction of\nppGpp by Mn2+ overload is reversed by treatment with reducing agents thiourea and ascorbic acid as well as by the\naddition of cysteine, methionine, and branch-chain amino acids to the growth media. Based on these observations, the\nauthors conclude that Mn2+ triggers the stringent response by poisoning iron-sulfur clusters, an idea that is supported by the\nactivation of ppGpp production noted after peroxide treatment as well as by the use of an iron chelator. This research\nidentifies a critical signal by which the stringent response is activated in Salmonella. Importantly, the findings in\nSalmonella seem to be applicable to other Gram-negative bacteria, suggesting the mechanism in question is universal among bacteria. I\nhave the following suggestions:\n1. Thiourea and ascorbic acid are used as reducing agents. The authors should consider that thiourea is also a scavenger of\nROS, raising the possibility that Mn2+ overload may induce the stringent response by inducing ROS production. Does Mn2+\ninduce ppGpp production in cells grown anaerobically?\n2. The conclusion that excess Mn2+ damages [Fe-S] clusters of enzymes key in the production of branch-chain amino acids\nshould be backed up by direct measurements of amino acid pools after treatment with the divalent cation.\n3. Among all the divalent cations tested, only Mn2+ elicited the stringent response. What is special about Mn2+ and\npoisoning of [Fe-S] clusters that does not seem to be share by the other divalent metals?\n4. The authors propose that Mn2+ poisons [Fe-S] clusters. This is idea is very plausible. Direct measurements of iron-sulfur\nclusters or enzymatic activity of metalloproteins bearing essential [Fe-S] clusters would strengthen the model put forward by\nthe authors.\n5. The model should be directly measured by testing the degree that Mn2+ and H2O2 activate ppGpp production in bacteria\neither are defective in [Fe-S] biogenesis or in [Fe-S] repair.\n6. Selected targets identified in the transcriptomic RNA seq analyses should be validated by independent methods (e.g., RT-\nPCR).", "reviewer_2": "The Stringent Response is a universal bacterial stress mechanism triggered by various nutritional and environmental\nstresses enabling bacteria to adapt and survive unpredictable fluctuating conditions. This global reprogramming of bacterial\ncell physiology is driven by the accumulation of the alarmones (p)ppGpp, which are synthesized by RelA/SpoT homologue\nproteins in salmonella. Importantly, (p)ppGpp has emerged as a key regulator not only of the bacterial stress response but\nalso of many other aspects of bacterial physiology, including virulence, immune evasion, and antibiotic tolerance. In the\npresent study the authors show that Iron-sulfur (Fe-S) cluster damage serves as a conserved trigger of the stringent\nresponse in pathogenic bacteria. Indeed disruption of Fe-S clusters by oxidative stress or metal imbalance restricts the\navailability of branch chain and sulfur containing amino acid therefore activating RelA-dependent (p)ppGpp synthesis.\nIn turn, this activation can reprograms global gene expression to promote bacterial fitness adaptation and virulence. The\nmanuscript is clearly written and supported by well-organized figures. Overall the research is relevant and addresses an\nimportant topic. However, the following points outline clarifications and additional experiments necessary to strengthen the\nmanuscript.\nSpecific comments\n1) the authors claim that Iron starvation (with DIP chelator) does not induce (p)ppGpp accumulation in Salmonella on the\ncontrary to what observed in E. coli. However, the method used in the present study is completely different. (p)ppGpp\naccumulation after DIP addition is a slow process that take hours in E. coli. The authors only present screenshot of (p)ppGpp\nproduction 30 min after chelators addition.\n-The authors should show that this time is indeed enough to induce starvation. The final drop in the OD observed after 6H of\ntreatment (Fig S1B) is not sufficient, a proper growth curve should be added to see what happens during the first 30 min.\n- The authors should perform time points experiments over an extended period. Note that the method used in Fig1A can only\nreflect rapid accumulation of (p)ppGpp since radiolabeled GTP is completely consumed during 30 min in absence of stress\n(Fig1A).\n2) The claim that excess of Mn leads to Fe-S cluster damage is supported by growth rescue experiments with amino acid\nsupplementation and reducing agents. It would be important to confirm this assumption by measuring the activity of an Fe-S\ncluster-dependent enzyme (such as the aconitase) under the conditions where (p)ppGpp accumulate (30 min after 1mM Mn\naddition)\n3) Both Mn excess and H2O2 stress cause Fe-S cluster damage that triggers the stringent response. However, the final\nmodel linking Fe-S cluster damage to the activation of specific virulence programs relies solely on transcriptomic data\nobtained from Mn excess. Consequently, this model may not be fully applicable to other more physiologically relevant Fe-S\ndamaging conditions such as oxidative stress. The authors should at least follow expression of virulence genes in WT and\nΔrelA strains exposed to mild oxidative stress (0.5 mM H₂O₂). This will directly test whether SPI-2 T3SS upregulation, are\nconserved across different Fe-S cluster-damaging conditions. Alternatively, targeting an essential FeS biogenesis (ie\nCRISPRi) would also be an interesting approach to reveal the transcriptional response to Fe-S cluster damage itself.\n4) The results shown in Fig 3 argue that iron starvation promotes the stringent response under conditions inducing Fe-S\ndamage. An intriguing observation which is not discuss is the differential pattern of (p)ppGpp accumulation observed during\nMn excess and H2O2+DIP treatment. The kinetic is similar but H202 only induce ppGpp but not pppGpp. It is reminiscent of\nthe old phenotype associated with the spoT1 allele. Do the authors have an explanation? This should be at least discussed.\nMinor comments\n-A growth curve with all amino acid should be add in Fig2B to show that ILV+CM are not sufficient to fully restore bacterial\ngrowth.\n-Representative TLC should be provide for the Fig 2G and H\n-When possible, the authors should provide proper growth curve experiments rather than simply providing the final optical\ndensity value.\n- The RNASeq data (Fig 4 EH and S7) are convincing, however, the scaling is not clear. Are they normalized globally or\nlocally.\n-It would be also interesting to provide analysis and to present volcano plot comparing WT to RelA before and after stress in\nthe supplementary data\n-The authors state that 1mM of Mn is bacteriostatic for the WT strain. Does it become bactericidal in the ∆relA strain?"}, "author_response": "Point-by-Point Response to Reviewers\nWe would like to thank both reviewers for their thoughtful evaluation of our\nmanuscript and are grateful for their suggestions, which we believe have helped us\nimprove its clarity and quality. We have provided responses to each of their\ncomments below in blue.\nReviewer #1 (Remarks to the Author):\nMichaud et al report disruption of iron-sulfur clusters as a mechanism by which the\nstringent response is elicited. The investigators show that the overload of manganese\nstimulates the RelA-dependent production of the (p)ppGpp. Induction of ppGpp by\nMn2+ overload is reversed by treatment with reducing agents thiourea and ascorbic\nacid as well as by the addition of cysteine, methionine, and branch-chain amino acids\nto the growth media. Based on these observations, the authors conclude that Mn2+\ntriggers the stringent response by poisoning iron-sulfur clusters, an idea that is\nsupported by the activation of ppGpp production noted after peroxide treatment as\nwell as by the use of an iron chelator. This research identifies a critical signal by\nwhich the stringent response is activated in Salmonella. Importantly, the findings in\nSalmonella seem to be applicable to other Gram-negative bacteria, suggesting the\nmechanism in question is universal among bacteria. I have the following suggestions:\n1. Thiourea and ascorbic acid are used as reducing agents. The authors should\nconsider that thiourea is also a scavenger of ROS, raising the possibility that Mn2+\noverload may induce the stringent response by inducing ROS production. Does\nMn2+ induce ppGpp production in cells grown anaerobically?\nWe thank the reviewer for this insightful comment. Performing radioactive\nexperiments under anaerobic conditions is technically extremely challenging, as all\nsteps—including growth and labeling—would need to be carried out entirely within an\nanaerobic chamber. Moreover, anaerobic conditions themselves have been reported\nto modulate RelA activity through nitrate reductase NirD (PMID: 34323689), which\nwould complicate the interpretation of such experiments.\nTo address the reviewer’s concern and assess whether Mn²⁺ excess induces ROS\nproduction, we instead used a well-established fluorescent ROS reporter, a pkatG-\nGFP fusion (PMID: 24439899). In contrast to H₂O₂ treatment, Mn²⁺ exposure did not\ninduce reporter expression (lines 225–228, Fig. S5g).\nConsistent with these results, our RNA-seq analysis revealed no induction of katG\nexpression under Mn stress (Table 4). Likewise, other canonical oxidative stress\nmarkers, including ahpC, ahpF, and sodA (PMID: 26279566), were not upregulated\n(Table 4).\nIn addition, Mn excess led to the accumulation of both ppGpp and pppGpp, whereas\noxidative stress selectively induced ppGpp. This distinction is likely linked to the\nimpact of ROS on the cellular GTP pool and is now discussed in the revised\nmanuscript (lines 320–330).\nFinally, to further test whether ROS contribute to the Mn-induced stringent response,\nwe examined the effect of Mn excess in an hpxF mutant lacking five ROS-detoxifying\nenzymes (PMID: 19447905), which is highly sensitive to oxidative stress. As\nexpected, this mutant was hypersensitive to H₂O₂ (panels A–B below) but did not\nexhibit increased sensitivity to Mn excess compared to the WT (panels C–D below).\nTogether, these data support the conclusion that Mn excess triggers (p)ppGpp\naccumulation independently of ROS under our experimental conditions.\n2. The conclusion that excess Mn2+ damages [Fe-S] clusters of enzymes key in the\nproduction of branch-chain amino acids should be backed up by direct\nmeasurements of amino acid pools after treatment with the divalent cation.\nWe thank the reviewer for this helpful suggestion. As recommended, we quantified\nbranched-chain amino acid (BCAA) levels using a commercial BCAA assay kit\n(Abcam). In support of our model, we found that exposure to 1 mM Mn rapidly and\nsignificantly reduced intracellular BCAA levels. These data have now been\nincorporated into the main figure (Fig. 2b and 3a) and are discussed in the revised\nmanuscript (lines 137–138).\n3. Among all the divalent cations tested, only Mn2+ elicited the stringent response.\nWhat is special about Mn2+ and poisoning of [Fe-S] clusters that does not seem to\nbe share by the other divalent metals?\nWe thank the reviewer for this insightful question. Mn²⁺ and Fe²⁺ share similar ionic\nradii, chemical properties, and coordination preferences, allowing Mn²⁺ to compete\nfor binding sites normally occupied by Fe²⁺ in metalloproteins (PMID: 34037759).\nHowever, unlike Fe²⁺, Mn²⁺ cannot support the electron-transfer functions required for\nthe activity of redox-active Fe-containing proteins (PMID: 28928443; PMID:\n22991063). As a result, Mn²⁺ substitution can selectively impair Fe–S cluster\nfunction.\nIn contrast, other divalent cations such as Zn²⁺, Cu²⁺, or Co²⁺ do not share the\nappropriate coordination chemistry to effectively replace Fe²⁺ in Fe–S cluster-\ncontaining proteins. Consequently, these metals are less likely to disrupt Fe–S\ncluster metabolism in a manner sufficient to trigger the stringent response.\nTo experimentally address this point, we tested whether thiourea could rescue the\ngrowth defects induced by excess Zn²⁺, Cu²⁺, or Co²⁺. Consistent with the specific\nability of Mn²⁺ to interfere with Fe–S cluster function, thiourea failed to rescue the\ngrowth defects caused by these other metals. These new results have been\nincorporated into the revised manuscript and are presented in Figure S3e.\n4. The authors propose that Mn2+ poisons [Fe-S] clusters. This is idea is very\nplausible. Direct measurements of iron-sulfur clusters or enzymatic activity of\nmetalloproteins bearing essential [Fe-S] clusters would strengthen the model put\nforward by the authors.\nWe thank the reviewer for this comment and fully agree that directly monitoring Fe–S\ncluster activity would further strengthen our model. To explore this hypothesis, we\nperformed aconitase assays, as aconitase activity depends on a functional Fe–S\ncluster. Previous work in E. coli has shown that Mn excess reduces the activity of\naconitase, a canonical Fe–S cluster-containing enzyme (PMID: 28928443).\nConsistent with these findings, we observed that aconitase activity in Salmonella is\nalso significantly reduced upon Mn excess, supporting the conclusion that Mn\ninterferes with Fe–S cluster proteins.\nImportantly, when considered together with the observed decrease in branched-chain\namino acid levels, these results provide strong evidence for impaired Fe–S protein\nfunction during Mn intoxication. These new data have been incorporated into Figure\n2b, and the main text has been revised accordingly (lines 127–130).\n5. The model should be directly measured by testing the degree that Mn2+ and\nH2O2 activate ppGpp production in bacteria either are defective in [Fe-S] biogenesis\nor in [Fe-S] repair.\nWe thank the reviewer for this constructive suggestion. To directly test whether\ndefects in Fe–S biogenesis influence Mn²⁺- and H₂O₂-induced (p)ppGpp production,\nwe quantified (p)ppGpp levels in an hscA mutant defective in Fe–S cluster\nmaturation. Consistent with our model, the hscA mutant accumulated (p)ppGpp at\nlower concentrations of Mn²⁺ and H₂O₂ than the WT strain. These results support a\nrole for Fe–S cluster biogenesis in modulating (p)ppGpp production. The new data\nare now included in Fig. S3c (Mn²⁺) and Fig. S5d (H₂O₂).\n6. Selected targets identified in the transcriptomic RNA seq analyses should be\nvalidated by independent methods (e.g., RT-PCR).\nWe thank the reviewers for their comments. To jointly address the concerns raised by\nReviewers 1 and 2 regarding the upregulation of specific target genes during Fe–S\ncluster stress, we focused our validation efforts on targets that are statistically\nsignificant (all significant targets are listed in Tables S4–S7), as not all genes shown\nin the heatmap reach statistical significance. The heatmap is intended to reflect the\noverall expression trend of an entire functional network, such as the SPI-2 apparatus,\nrather than the statistical significance of individual genes.\nAs suggested by Reviewer 2, we performed these validation experiments under mild\noxidative stress, which is more physiologically relevant and induces (p)ppGpp\nproduction in response to Fe–S cluster damage. Consistent with our RNA-seq data,\nqRT–PCR analyses showed that the SPI-2–associated genes sseB, sseC, ssaJ, and\nssaM are significantly overexpressed in the WT strain during oxidative stress, but not\nin the ΔrelA mutant. In contrast, the mntP gene was not overexpressed under these\nconditions, as it is specifically induced in response to Mn excess. These findings are\nconsistent with earlier work demonstrating that (p)ppGpp promotes SPI-2 gene\nexpression (PMID: 16905537; 26039089; 29930310).\nTogether, these additional validation experiments support our conclusion that\nconditions destabilizing Fe–S clusters promote SPI-2 gene expression through\n(p)ppGpp signaling. The new data have been added as Fig. S7g, and the manuscript\nhas been revised accordingly to emphasize earlier work on the regulation of SPI-2 by\n(p)ppGpp (lines 283–284).\nReviewer #2 (Remarks to the Author):\nThe Stringent Response is a universal bacterial stress mechanism triggered by\nvarious nutritional and environmental stresses enabling bacteria to adapt and survive\nunpredictable fluctuating conditions. This global reprogramming of bacterial cell\nphysiology is driven by the accumulation of the alarmones (p)ppGpp, which are\nsynthesized by RelA/SpoT homologue proteins in salmonella. Importantly, (p)ppGpp\nhas emerged as a key regulator not only of the bacterial stress response but also of\nmany other aspects of bacterial physiology, including virulence, immune evasion, and\nantibiotic tolerance. In the present study the authors show that Iron-sulfur (Fe-S)\ncluster damage serves as a conserved trigger of the stringent response in pathogenic\nbacteria. Indeed disruption of Fe-S clusters by oxidative stress or metal imbalance\nrestricts the availability of branch chain and sulfur containing amino acid therefore\nactivating RelA-dependent (p)ppGpp synthesis. In turn, this activation can\nreprograms global gene expression to promote bacterial fitness adaptation and\nvirulence. The manuscript is clearly written and supported by well-organized figures.\nOverall the research is relevant and addresses an important topic. However, the\nfollowing points outline clarifications and additional experiments necessary to\nstrengthen the manuscript.\nSpecific comments\n1) the authors claim that Iron starvation (with DIP chelator) does not induce (p)ppGpp\naccumulation in Salmonella on the contrary to what observed in E. coli. However, the\nmethod used in the present study is completely different. (p)ppGpp accumulation\nafter DIP addition is a slow process that take hours in E. coli. The authors only\npresent screenshot of (p)ppGpp production 30 min after chelators addition.\n-The authors should show that this time is indeed enough to induce starvation. The\nfinal drop in the OD observed after 6H of treatment (Fig S1B) is not sufficient, a\nproper growth curve should be added to see what happens during the first 30 min.\nWe thank the reviewer for this comment. Under our experimental conditions,\nSalmonella rapidly loses its ability to grow in the presence of 1 mM DIP, which is the\ncondition used for TLC analyses. To directly address the reviewer’s concern and to\ndemonstrate that this treatment is sufficient to induce starvation, we have now\nincluded a complete growth curve with additional early time points, including the first\n30 minutes following DIP addition. These data show an immediate growth arrest\nupon DIP treatment and are provided in the revised supplementary information (new\nFig. S1b).\nTo note, we have replaced the abbreviation “DPI” with “DIP” throughout the\nmanuscript and figures to align with current literature and ensure consistency.\n- The authors should perform time points experiments over an extended period. Note\nthat the method used in Fig1A can only reflect rapid accumulation of (p)ppGpp since\nradiolabeled GTP is completely consumed during 30 min in absence of stress\n(Fig1A).\nWe thank the reviewer for this insightful suggestion. We chose to use a pulse-chase\nprotocol to assess (p)ppGpp accumulation under different stress conditions using the\nsame pool of radiolabeled bacteria, in order to minimize potential interference in\nnucleotide labeling that could arise from stress-induced effects on P³² transport, for\ninstance.\nAs suggested by the reviewer, we have now performed a kinetic analysis over an\nextended period (every 30 min for 2.5 h) to determine whether DIP alone induces the\naccumulation of (p)ppGpp over time. We did not detect any (p)ppGpp accumulation\nduring the first 30 min of DIP treatment (as previously shown on Fig. 1a). However, a\nsmall and transient increase in ppGpp (but not pppGpp) was observed starting at 60\nmin, which rapidly declined and returned to near-baseline levels by 2.5 h (consistent\nwith Fig. 3e).\nTo determine whether this delayed ppGpp accumulation resulted from RelA\nactivation due to amino-acid limitation caused by Fe-S cluster damage, we measured\nintracellular levels of branched-chain amino acids (BCAA) during iron starvation (DIP)\nor Mn intoxication. While Mn-treated cells exhibited a rapid decrease in BCAA levels,\niron-starved cells maintained high BCAA levels, despite the known dependence of\nBCAA biosynthesis on functional Fe-S clusters (new Fig. 3a). These data indicate\nthat, under our experimental conditions, iron starvation does not induce RelA-\ndependent (p)ppGpp accumulation through amino-acid auxotrophy.\nAn alternative and intriguing possibility is that iron availability directly modulates the\nactivity of SpoT, the second (p)ppGpp synthetase, as previously suggested in E. coli\n(Vinella et al., PMID: 15853883) and highlighted by the reviewer. Although the\nprecise molecular mechanisms remain to be elucidated, our data are consistent with\na model in which SpoT activity—and possibly inhibition of its hydrolase function—is\nsensitive to iron availability.\nThese results further support the coordination model proposed in the original\nmanuscript, in which RelA and SpoT respond to distinct but interconnected signals:\nRelA to Fe-S cluster damage–associated amino-acid limitation, and SpoT to iron\navailability. Regulation of SpoT hydrolase activity may prevent a futile cycle of\n(p)ppGpp synthesis and degradation under Fe-S cluster–damaging conditions, which\ncould explain both the selective accumulation of ppGpp and the delayed onset of the\nstringent response during iron starvation compared with Mn intoxication.\nIn light of these new data, we have revised the section discussing the impact of iron\nlimitation on (p)ppGpp accumulation to clarify the lack of RelA activation under these\nconditions (lines 191–198), and we have expanded the Discussion to emphasize the\npotential role of iron availability in modulating SpoT activity (lines 331–338).\n2) The claim that excess of Mn leads to Fe-S cluster damage is supported by growth\nrescue experiments with amino acid supplementation and reducing agents. It would\nbe important to confirm this assumption by measuring the activity of an Fe-S cluster-\ndependent enzyme (such as the aconitase) under the conditions where (p)ppGpp\naccumulate (30 min after 1mM Mn addition)\nWe thank the reviewer for this important comment. We agree that directly monitoring\nthe activity of a Fe-S cluster–dependent enzyme provides a critical and independent\nvalidation of Fe-S cluster damage and would substantially strengthen our model.\nPrevious work in E. coli has shown that excess manganese impairs the activity of\naconitase, a canonical Fe-S cluster–containing enzyme commonly used as a proxy\nfor Fe-S cluster integrity (PMID: 28928443). In agreement with these findings, we\ndirectly measured aconitase activity in Salmonella under the conditions where\n(p)ppGpp accumulation is observed (30 min after addition of 1 mM Mn). We found\nthat aconitase activity is significantly reduced upon Mn excess, supporting the\nconclusion that manganese interferes with the function of Fe-S cluster–dependent\nproteins under these conditions. These data have now been added to the revised\nmanuscript (new Fig. 2b), and the corresponding Results section has been updated\naccordingly (lines 127–131).\nIn addition, as requested by reviewer 1, we quantified intracellular levels of branched-\nchain amino acids, whose biosynthesis depends directly on the Fe-S cluster–\ncontaining enzymes IlvD and LeuC. We observed a rapid decrease in branched-\nchain amino acid levels upon Mn intoxication, further supporting the notion that Mn\nexcess causes functional impairment of Fe-S cluster proteins. These results are now\nincluded in the revised manuscript (Fig. 2c) and discussed in the main text (lines 137-\n138).\nTogether, these complementary approaches provide direct biochemical evidence that\nMn excess induces Fe-S cluster damage under the conditions that trigger (p)ppGpp\naccumulation, thereby reinforcing the causal link between Mn intoxication, Fe-S\ncluster dysfunction, and activation of the stringent response.\n3) Both Mn excess and H2O2 stress cause Fe-S cluster damage that triggers the\nstringent response. However, the final model linking Fe-S cluster damage to the\nactivation of specific virulence programs relies solely on transcriptomic data obtained\nfrom Mn excess. Consequently, this model may not be fully applicable to other more\nphysiologically relevant Fe-S damaging conditions such as oxidative stress. The\nauthors should at least follow expression of virulence genes in WT and ΔrelA strains\nexposed to mild oxidative stress (0.5 mM H₂O₂). This will directly test whether SPI-2\nT3SS upregulation, are conserved across different Fe-S cluster-damaging conditions.\nAlternatively, targeting an essential FeS biogenesis (ie CRISPRi) would also be an\ninteresting approach to reveal the transcriptional response to Fe-S cluster damage\nitself.\nWe thank the reviewer for this important and thoughtful comment. We agree that\nextending the analysis beyond Mn excess to other physiologically relevant Fe-S\ncluster–damaging conditions is essential to strengthen the generality of our model.\nTo directly address this concern, we examined the expression of SPI-2–associated\ngenes in WT and ΔrelA strains exposed to mild oxidative stress (0.5 mM H₂O₂), a\nwell-established condition that destabilizes Fe-S clusters. Using qRT–PCR, we found\nthat SPI-2 genes are significantly upregulated in the wild-type strain upon oxidative\nstress, whereas this response is strongly impaired in the ΔrelA mutant. These results\ndemonstrate that SPI-2 activation in response to oxidative stress requires RelA-\ndependent (p)ppGpp synthesis.\nImportantly, these findings are consistent with our RNA-seq data obtained under Mn\nexcess and align with previous studies showing that (p)ppGpp positively regulates\nSPI-2 gene expression. Together, these results indicate that the transcriptional\nactivation of SPI-2 is not specific to Mn intoxication but represents a broader\nresponse mediated by the stringent response.\nCollectively, these additional validation experiments support our conclusion that Fe-S\ncluster destabilization—whether caused by metal imbalance or oxidative stress—\npromotes SPI-2 gene expression through (p)ppGpp signaling. The new data have\nbeen added to the supplementary information (new Fig. S7g), and the manuscript\nhas been revised accordingly to better integrate earlier work on the regulation of SPI-\n2 by (p)ppGpp (lines 283–284).\n4) The results shown in Fig 3 argue that iron starvation promotes the stringent\nresponse under conditions inducing Fe-S damage. An intriguing observation which is\nnot discuss is the differential pattern of (p)ppGpp accumulation observed during\nMn excess and H2O2+DIP treatment. The kinetic is similar but H202 only induce ppGpp\nbut not pppGpp. It is reminiscent of the old phenotype associated with the spoT1\nallele. Do the authors have an explanation? This should be at least discussed.\nWe thank the reviewer for this insightful comment. A key distinction between Mn\nintoxication (as well as SHX treatment) and oxidative stress is that Mn excess\ninduces the accumulation of both ppGpp and pppGpp, whereas H₂O₂ exposure leads\npredominantly to ppGpp accumulation, independently of the presence of DIP.\nSeveral non-mutually exclusive mechanisms may contribute to this differential profile.\nFirst, we considered the role of GppA, the enzyme responsible for the conversion of\npppGpp to ppGpp. To directly test whether enhanced GppA activity could account for\nthe absence of detectable pppGpp during oxidative stress, we constructed a ΔgppA\nstrain and monitored (p)ppGpp accumulation under the same conditions. As\nexpected, pppGpp levels were increased under Mn excess and SHX treatment in the\nΔgppA mutant compared with the WT. Notably, pppGpp accumulation was also\nobserved in the ΔgppA mutant during oxidative stress, but not in the WT. However,\nsubstantial levels of ppGpp were still detected in the ΔgppA mutant under H O\n2 2\nstress, indicating that enhanced GppA-mediated conversion alone does not fully\naccount for the observed ppGpp/pppGpp profile.\nA second contributing factor likely involves stress-induced changes in the intracellular\nbalance of GDP and GTP, which serve as substrates for ppGpp and pppGpp\nsynthesis, respectively. Oxidative stress has been shown to perturb nucleotide pools\nand, similar to what has been described during nitrosative stress—another Fe-S\ncluster–destabilizing condition—may preferentially limit GTP availability, thereby\nfavoring ppGpp over pppGpp synthesis (PMID: 29487237). Such an imbalance would\nbias alarmone production toward ppGpp, even in the absence of enhanced pppGpp\nhydrolysis.\nTogether, these data indicate that the lack of pppGpp accumulation during oxidative\nstress likely arises from a combination of increased pppGpp turnover and stress-\ndependent alterations in nucleotide pool availability. As suggested by the reviewer,\nwe have now included a dedicated paragraph discussing this point in the revised\nDiscussion (lines 320–330).\nMinor comments\n-A growth curve with all amino acid should be add in Fig2B to show that ILV+CM are\nnot sufficient to fully restore bacterial growth.\nAs suggested, we updated Fig. 2B to include growth with all amino acids for\ncomparison with ILV+CM.\n-Representative TLC should be provide for the Fig 2G and H\nBoth TLCs are provided as raw data in Figure S3g and h. We selected the\nquantification for the main paper, as we observed the same pattern as in Salmonella.\n-When possible, the authors should provide proper growth curve experiments rather\nthan simply providing the final optical density value.\nWe thank the reviewer for this comment. Whenever possible, we have replaced final\noptical density measurements with full growth curve analyses to better capture\ngrowth dynamics over time. Specifically, Fig. S3f now shows the complete growth\ncurve for ascorbic acid treatment, and original Figures S1B and S1C have been\nupdated to display full growth curves for each independent stress condition (now\nS1a-f).\nFor growth/no-growth assays (e.g., Fig. 2e), we have retained the original\npresentation in the main manuscript. This format allows direct visual comparison of\nmultiple conditions within a single figure, ensuring clarity and readability while still\nconveying the key qualitative differences in growth behavior.\n- The RNASeq data (Fig 4 EH and S7) are convincing, however, the scaling is not\nclear. Are they normalized globally or locally.\nWe thank the reviewer for this comment. The RNA-seq data shown in Figures 4E–H\nand S7 are presented as TPM (transcripts per million) values, which represent\nglobally normalized expression levels across the transcriptome. No additional local or\ncondition-specific normalization was applied beyond TPM calculation.\nThe scaling and color schemes used in these figures are intended solely as visual\naids to facilitate comparison of expression patterns and trends across conditions,\nrather than to convey further quantitative normalization. All statistically significant\ndifferentially expressed genes are ranked and reported in the corresponding\nsupplementary tables (Tables S4–S7), which contain the full quantitative and\nstatistical information.\n-It would be also interesting to provide analysis and to present volcano plot\ncomparing WT to RelA before and after stress in the supplementary data\nWe thank the reviewer for the suggestion. We have added volcano plots comparing\nWT to ΔrelA before and after stress (new Figures S6d and S6e) and provided two\nfully annotated tables (Tables S6 and S7) to allow readers to directly compare the\ntranscriptomes under these conditions.\n-The authors state that 1mM of Mn is bacteriostatic for the WT strain. Does it become\nbactericidal in the ∆relA strain?\nWe thank the reviewer for this comment. To determine whether Mn excess becomes\nbactericidal in the absence of RelA, we directly assessed bacterial survival of the WT\nand ΔrelA strains following 4 h of exposure to excess manganese (1 mM). Under\nthese conditions, Mn treatment resulted in bacteriostasis rather than loss of viability\nin both strains, indicating that Mn excess is not bactericidal even in the absence of\nRelA. These data have now been included in the revised manuscript (new Fig. S7a),\nand the corresponding section of the text has been amended accordingly (lines 244–\n245)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have responded very nicely to all my queries. I have no further questions.", "reviewer_2": "In the revised manuscript, the authors have done an excellent job thoroughly addressing ALL reviewers comments. They\nprovide important controls that further strengthen their general model of (p)ppGpp regulation in response to iron–sulfur\ncluster damage, and have added depth to the discussion.\nAs it stands, the manuscript is concise and well written, and the results are clear and significant."}, "author_response": ""}]

Decision letter