Mechanisms of iron- and O2-sensing by the [4Fe-4S] cluster of the global iron regulator RirA

Abstract

RirA is a global regulator of iron homeostasis in Rhizobium and related α-proteobacteria. In its [4Fe-4S] cluster-bound form it represses iron uptake by binding to IRO Box sequences upstream of RirA-regulated genes. Under low iron and/or aerobic conditions, [4Fe-4S] RirA undergoes cluster conversion/degradation to apo-RirA, which can no longer bind IRO Box sequences. Here, we apply time-resolved mass spectrometry and electron paramagnetic resonance spectroscopy to determine how the RirA cluster senses iron and O2. The data indicate that the key iron-sensing step is the O2-independent, reversible dissociation of Fe2+ from [4Fe-4S]2+ to form [3Fe-4S]0. The dissociation constant for this process was determined as Kd = ~3 µM, which is consistent with the sensing of ‘free’ iron in the cytoplasm. O2-sensing occurs through enhanced cluster degradation under aerobic conditions, via O2-mediated oxidation of the [3Fe-4S]0 intermediate to form [3Fe-4S]1+. This work provides a detailed mechanistic/functional view of an iron-responsive regulator.

https://doi.org/10.7554/eLife.47804.001

eLife digest

Virtually all life forms require iron to survive, yet too much of the metal can be catastrophic. In healthy cells, many systems regulate this delicate balance. For instance, when a protein called RirA is active in Rhizobium bacteria, it can sense high levels of the metal and helps to shut down the production of proteins that bring in more iron. RirA contains a cluster of four iron and four sulphur atoms, which acts as a sensor for iron availability: however, exactly how this cluster structure detects the levels of the metal in a cell was previously unclear.

Pellicer Martinez, Crack, Stewart et al. used a technique known as time-resolved mass spectrometry to examine the sensory response of the iron-sulphur cluster of RirA when different levels of iron were available. The results revealed a ‘loose’ iron atom in the cluster; when iron levels fall down, this atom is rapidly lost as it is scavenged for use in other essential processes. Without it, the cluster in RirA collapses and the protein becomes inactive. This prompts the cell to produce proteins that enable it to take up iron from its surroundings. Once iron levels are high, RirA can regain its cluster and is active again, stopping the production of proteins that bring in more iron.

Iron-sulphur clusters are common in many proteins, and this work offers new insight into their various roles. It also highlights the potential to use time-resolved mass spectrometry to examine biological processes in depth.

https://doi.org/10.7554/eLife.47804.002

Introduction

Iron–sulphur clusters are ubiquitous protein cofactors that play essential roles across all of life in processes as diverse as respiration, photosynthesis, and DNA replication (Beinert et al., 1997; Johnson et al., 2005), with recent evidence that they may be even more abundant than initially thought (Rouault, 2015). Elucidating the precise nature of their roles is a major challenge, which is often complicated by the extreme reactivity of the cluster to O2 and other gases. However, this very sensitivity has been exploited through the evolution of iron–sulphur cluster-containing transcriptional regulators that enable cells to sense and respond to, for example, oxidative stress and changes in concentrations of metabolically important species such as O2 and iron (Beinert and Kiley, 1999; Crack et al., 2014a).

Iron is an essential micronutrient for nearly all of life, but is also potentially extremely toxic due to its ability to catalyse, via redox cycling, the formation of damaging reactive oxygen species. Consequently, for life to flourish, not only must sufficient iron be obtained from the environment, but its precise form must be carefully controlled (Andrews et al., 2003). A central part of this control is exerted through the regulation of iron uptake into the cell in response to intracellular iron levels. In many bacteria, including such taxonomically diverse model organisms as Escherichia coli and Bacillus subtilis, iron uptake is under the control of the global iron regulator Fur (Ferric uptake regulator). Iron is sensed through the availability and binding of Fe2+ directly to the Fur protein, resulting in a conformation that can bind cis-acting ‘Fur boxes’ close to the promoters of genes encoding proteins that function in the iron-uptake machinery, causing (usually) repression of transcription (Lee and Helmann, 2007; Pohl et al., 2003). The direct binding of Fe2+ as a co-repressor also occurs in DtxR (Diphtheria toxin Repressor) from Corynebacterium diphtheriae and related species. Although DtxR has no significant sequence similarity to Fur, it shares significant structural features, in addition to Fe2+-binding (D'Aquino et al., 2005; Ding et al., 1996).

Rhizobium and other closely related rhizobial genera that induce nitrogen-fixing nodules on legumes, as well as the pathogens Bartonella, Brucella, and Agrobacterium, contain a very different global iron regulator called RirA (Rhizobial iron regulator A) (Todd et al., 2002; Wexler et al., 2003; Yeoman et al., 2004; Todd et al., 2005; Todd et al., 2006; Rudolph et al., 2006; Chao et al., 2005; Ngok-Ngam et al., 2009; Viguier et al., 2005; Bhubhanil et al., 2014; Crespo-Rivas et al., 2019), which has no structural or sequence similarity whatsoever to Fur or DtxR. Rather, RirA belongs to the Rrf2 super-family of transcriptional regulators (Keon et al., 1997) that includes IscR (regulator of iron–sulphur cluster biosynthesis) (Rajagopalan et al., 2013; Schwartz et al., 2001) and NsrR (regulator of nitrosative stress response) (Crack et al., 2012; Crack et al., 2015; Volbeda et al., 2017), both of which are homodimeric and bind an iron–sulphur cluster. In Rhizobium leguminosarum, the symbiont of peas, beans and clovers, RirA regulates many genes involved in iron homeostasis, by binding to cis-acting ‘IRO boxes’ (Yeoman et al., 2004). Recently, it was shown that R. leguminosarum RirA binds a [4Fe-4S] cluster and that this form of the protein binds to the IRO box sequence (Pellicer Martinez et al., 2017). Although the structure of RirA is not yet available, a model based on the structure of dimeric [4Fe-4S] NsrR, the first reported for any cluster-bound Rrf2 regulator (Volbeda et al., 2017), is shown in Figure 1. Exposure of [4Fe-4S] RirA to low iron conditions and/or O2 resulted in cluster conversion to generate a [2Fe-2S] form, which binds to the IRO box with lower affinity than the [4Fe-4S] form. The [2Fe-2S] form was also unstable under low iron conditions, resulting in apo-RirA, which did not bind the IRO box sequence (Pellicer Martinez et al., 2017).

Figure 1 with 1 supplement see all
Model of the homodimer form of [4Fe-4S] RirA.

Cartoon ribbon representation showing one protomer in blue and the other in beige, with iron and sulphide ions in brown and yellow, respectively. The model was generated using Swiss-Model (Bienert et al., 2017; Pettersen et al., 2004) based on the structure of Streptomyces coelicolor [4Fe-4S] NsrR (PDB: 5N07) (Volbeda et al., 2017). An amino acid residue alignment between RirA and NsrR is shown in Figure 1—figure supplement 1.

https://doi.org/10.7554/eLife.47804.003

To understand how RirA functions as an iron sensor and how it enables the cell to integrate iron and O2 signals requires that the mechanisms by which it responds to these two signals are elucidated. Traditional approaches to studies of iron–sulphur cluster proteins cannot readily resolve intermediates of cluster conversion/decay. ESI-MS utilizing solution and ionisation conditions under which proteins remain folded enables accurate mass detection of intact proteins and protein complexes, and has been used extensively to study protein-protein interactions, interactions of proteins with drugs, nucleic acids, sugars and lipids, as well as protein structural changes (Liko et al., 2016; Hopper and Robinson, 2014; Rodenburg et al., 2017). It has also been used to study protein-cofactor interactions where the cofactor remains bound following ionisation, and amongst these, ESI-MS of metalloregulators (Glauninger et al., 2018) and iron–sulphur cluster proteins (Johnson et al., 2000) and their reactivity (Crack and Le Brun, 2019) have also been shown to be valuable. Time-resolved mass spectrometry has been exploited for studying protein metal ion binding (Ngu and Stillman, 2006) and heme transfer (Tiedemann et al., 2012), and for structural studies using H/D exchange (Konermann et al., 2011). Recently, time-resolved ESI-MS provided detailed mechanistic information of the O2-sensing reaction of the [4Fe-4S] cluster binding FNR regulator (Crack et al., 2017).

Here, we employed time-resolved ESI-MS under non-denaturing conditions, along with EPR spectroscopy, to elucidate the exact series of molecular events involved in the conversion of the RirA cluster in response to key environmental signals. The data reveal, in remarkable detail, the nature of intermediates formed and differences in cluster conversion under aerobic and anaerobic conditions. Importantly, we find that the key sensing step, the initiation of cluster conversion/degradation, is dependent on Fe2+ but is independent of O2, and that the Kd for the fourth iron binding to the cluster is in the low micromolar range, supporting a primary role for RirA as an iron sensor in vivo. Nevertheless, O2 influences the overall rate of cluster decay through the oxidation of a key cluster intermediate and of cluster-derived sulphide. Together, the data provide a comprehensive mechanistic and functional view of an important iron-responsive regulator.

Results and discussion

Mass spectrometric analysis of [4Fe-4S] RirA cluster conversion under anaerobic conditions

Regular electrospray ionisation mass spectrometry (ESI-MS) in water/acetonitrile acidified with formic acid results in denatured proteins and the loss of non-covalently attached cofactors. However, the use of a volatile buffer at physiological pH is known to preserve the protein’s folded state and, with it, any bound cofactors (Crack et al., 2017). Therefore, using ESI-MS under such non-denaturing conditions, we set out to observe in real time the decay of the [4Fe-4S] RirA cluster in response to low iron conditions and to determine the identity of any intermediary cluster conversion breakdown products. The feasibility of this approach was indicated by the previously reported ESI-MS of [4Fe-4S] RirA (Pellicer Martinez et al., 2017), in which both dimeric and monomeric forms were observed. Ionisation of RirA in the MS experiment results in partial dissociation of the RirA dimer into monomers. Initially, conditions for the formation of the monomeric form were optimised because this enabled the unambiguous assignment of cluster species. Analysis of the RirA dimer follows in a later section.

The initial spectrum, Figure 2A (black line), in which the protein was held under non-denaturing anaerobic, iron-replete conditions, was very similar to that previously described for cluster-bound RirA (Pellicer Martinez et al., 2017); the major peak at 17,792 Da corresponds to the [4Fe-4S] form (see Supplementary file 1 for predicted and observed masses), but a range of lower intensity cluster breakdown species was also present, which are most likely due to cluster damage sustained during the exchange of the protein into the volatile buffer necessary for ESI-MS studies. Indeed, these were observed to decay away while the [4Fe-4S] form remained stable (Figure 2—figure supplement 1), consistent with previous studies that demonstrated that the [4Fe-4S] form of RirA is entirely stable under anaerobic, iron-replete conditions (Pellicer Martinez et al., 2017).

Figure 2 with 1 supplement see all
ESI-MS analysis of [4Fe-4S] RirA cluster conversion under anaerobic, low iron conditions.

(A) Deconvoluted (to neutral mass) mass spectrum of [4Fe-4S] RirA prior to the addition of 250 µM EDTA (t = 0, black line) and 30 min after the addition at 37°C (t = 30, red line). (B) and (C) Deconvoluted mass spectra measured at intervening times: 0–8 min (from the point of EDTA addition, spectra recorded at 2 min intervals) (B) and 8–30 min (C). Starting and endpoint spectra are in black and red, respectively (corresponding to the data in (A). (D) 3D plot of time dependent changes in the ESI-MS spectrum showing the formation and decay of RirA cluster intermediates and formation of apo-RirA products. [4Fe-4S] RirA (~25 µM) was in anaerobic 250 mM ammonium acetate pH 7.3. Low iron conditions were generated by the addition of 250 µM EDTA and cluster conversion/degradation was followed at 37°C.

https://doi.org/10.7554/eLife.47804.005

We previously showed that various Fe2+ chelators, including EDTA and Chelex 100, can simulate low iron conditions by efficiently competing for Fe2+. The lack of dependence on the concentration or type of chelator used indicated that this competition occurs through two equilibria corresponding to the loss of iron from the cluster and subsequent binding by the chelator. Consistent with this, under low iron conditions generated by the anaerobic addition of 250 µM EDTA, major changes in the ESI-MS spectrum were observed after 30 min, Figure 2A. ESI-MS changes were then measured over this time period (t = 0 is the spectrum prior to the addition of chelator, t = 30 is 30 min post addition). While the [4Fe-4S] peak was observed to decay away, peaks corresponding to protein-bound cluster fragments (17,586–17,762 Da) initially increased in intensity. These included [4Fe-3S], [3Fe-4S], [3Fe-3S], [3Fe-2S], [3Fe-S], [2Fe-2S] and [2Fe-S] forms (see Figure 2B and Supplementary file 1). These species then subsequently decayed away (Figure 2C), with a peak at 17442 Da, due to apo-RirA, becoming the major feature of the spectrum. Peaks at +16, 32 and 64 Da, due to oxygen or sulphur adducts of apo-RirA, were also observed, though at relatively low intensity. The full time course is shown as a 3D plot in Figure 2D.

To assist with unambiguous assignment of cluster-bound forms of RirA, [4Fe-4S] RirA with cluster sulphide specifically labelled with 34S was generated via in vitro cluster synthesis (cluster reconstitution) using 34S-L-cysteine (Crack et al., 2019). The major peak in the deconvoluted ESI-MS spectrum was at 17,800 Da, shifted +8 Da relative to the natural abundance (predominantly 32S) form of [4Fe-4S] RirA, Figure 3A and Supplementary file 1. Exposure of the 34S form to EDTA under anaerobic conditions resulted in a set of peaks, due to intermediate species, observed at masses shifted relative to those of the 32S sample, Figure 3B–G. The peaks initially assigned to [3Fe-4S], [4Fe-3S], [3Fe-3S], [3Fe-2S], [3Fe-S], [2Fe-2S] and [2Fe-S] species were shifted by +2 Da for each sulphide, confirming the identification of these intermediate/product forms. As expected, the apo-protein peak was not shifted (Figure 3H).

Figure 3 with 1 supplement see all
Mass shifts observed for the RirA [4Fe-4S] cluster, conversion intermediates and cluster products upon 34S substitution of cluster sulphides.

(A–G) Deconvoluted mass spectra of natural abundance sulphur [4Fe-4S] RirA and cluster conversion intermediates (black lines) and the equivalent 34S-substituted forms (red lines), as indicated. (H) As in A) except spectra show peaks due to apo-RirA resulting from natural abundance and 34S [4Fe-4S] RirA samples, as indicated. Predicted mass shifts for the assigned species are indicated. Note that the ESI-MS data for natural abundance and 34S-substituted [4Fe-4S] RirA were previously published (Crack et al., 2019); see also Supplementary file 1.

https://doi.org/10.7554/eLife.47804.007

The apo-RirA adduct at +16 and +32 Da were also not shifted, suggesting that these are due, respectively, to one and two O adducts, while the peak at +64 Da was shifted by + 4 Da, consistent with a double sulphur adduct derived from cluster sulphide (Figure 3—figure supplement 1). The latter arises as a result of oxidation of cluster sulphide, generating S0, which can be incorporated into Cys thiol side chains. The origin of oxygen adducts is less clear. Recent ESI-MS studies of the anaerobic nitrosylation of NsrR also revealed O adduct species (Crack and Le Brun, 2019), and we note that under certain conditions aqueous samples may generate oxygen in the ESI source (Banerjee and Mazumdar, 2012).

It is well established that non-denaturing ESI-MS can be used to follow chemical processes in solution (e.g. ligand binding to a protein or isotope exchange over time), yielding quantitative thermodynamic and kinetic information (Hopper and Robinson, 2014; Ngu and Stillman, 2006; Crack et al., 2017; Pacholarz et al., 2012; Schermann et al., 2005). To determine the sequence of events in RirA [4Fe-4S] cluster degradation, abundances of the different cluster fragment species in Figure 3 were analysed as a function of time. Figure 4A shows plots of relative intensities due to [4Fe-4S] and [3Fe-4S] species as a function of time following the addition of EDTA, while Figure 4B–E show equivalent plots for [3Fe-3S], [3Fe-2S], [2Fe-2S] and apo-RirA species.

Kinetic analysis of [4Fe-4S] RirA cluster conversion/degradation.

(A) Plots of relative abundances of [4Fe-4S] cluster (black) and [3Fe-4S] (yellow) species as a function of time following exposure to 250 µM EDTA at 37° C. Inset is a plot of relative abundances of the [4Fe-3S] cluster, illustrating that it is likely formed during ionisation. (B) – (E) As in (A) but showing [3Fe-3S] (B), [3Fe-2S] (C), [2Fe-2S] (D) and apo- (E) forms of RirA. Fits of the data, generated by a global analysis of the experimental data based on the reaction scheme depicted in Figure 5, are shown as solid lines. Broken lines correspond to the kinetic profile of the cluster species associated with that colour and are included to permit easy comparison between intermediates. Error bars show standard error for ESI-MS datasets (n = 4, derived from one biological replicate and three technical replicates). (F) Plot of A382 nm versus time following addition of 250 µM EDTA to [4Fe-4S] RirA (30 µM in cluster in 250 mM ammonium acetate, 500 µM glutathione, pH 7.3) at 37° C. The red line indicates a fit of the data generated using a bi-exponential function. We note that significant A382 nm remains after 30 min, where ESI-MS indicates that the majority of the protein is in an apo-form. The residual absorbance most likely arises from Fe/S species present in the cuvette, either attached to the protein, or in solution/suspension, for example as iron sulphide or iron acetate (Pellicer Martinez et al., 2017).

https://doi.org/10.7554/eLife.47804.009
Proposed reaction scheme for [4Fe-4S] RirA cluster conversion/degradation.

Reaction scheme used to fit time-resolved ESI-MS data for [4Fe-4S] RirA. Values of rate constants (k) are given in Table 1. Note that the ESI-MS data cannot distinguish between [3Fe-4S]1+ and [3Fe-4S]0 forms (boxed), so these are treated only as [3Fe-4S] in the kinetic model. They can be distinguished by EPR, however (see below), and the kinetic EPR data support the proposal that [3Fe-4S]0 is susceptible to oxidation to [3Fe-4S]1+ in the presence of O2. Reactions that are enhanced in rate (i.e. have increased associated rate constants) in the presence of O2 are indicated by red arrows. The initial [4Fe-4S] cluster is coordinated by three Cys residues and one unknown ligand, illustrated in the figure as ‘X’. The structure of the [3Fe-3S] species proposed here is based on the recently reported small molecule [3Fe-3S] species in which iron and sulphur form a hexagonal ring (Lee et al., 2016). The faded portion of the figure (involving steps marked k5, k6 and k7) represents a minor pathway that most likely arises from ionisation-induced damage.

https://doi.org/10.7554/eLife.47804.010

The data show that [4Fe-3S] and [3Fe-4S] were the first intermediates to reach their maximum abundance, consistent with their formation early in the conversion process. The [3Fe-3S] species was the next intermediate to maximise, followed by [3Fe-2S] species. The last of the intermediates to maximise in abundance and the last to decay away was [2Fe-2S] RirA. This was previously shown to be a stable intermediate following the [4Fe-4S] to [2Fe-2S] conversion promoted by EDTA (Pellicer Martinez et al., 2017). However, the buffer conditions used in the present study, and which are required for the ESI-MS experiment, appear to reduce the stability of the [2Fe-2S] form leading to observation of apo-protein (Figure 4E), as recently observed following conversion of the O2 sensor [4Fe-4S] FNR to its [2Fe-2S] form (Crack et al., 2017).

The observed sequence of cluster intermediates provided an outline for the mechanism of cluster conversion/degradation, which was used as the basis for global analysis of multiple (n = 4) mass spectrometric kinetic data sets. Iterative optimisation of the mechanism/global fit resulted in the reaction scheme shown in Figure 5, with corresponding fits of the peak intensities due to the formation and/or decay of [4Fe-4S], [4Fe-3S], [3Fe-4S], [3Fe-3S], [3Fe-2S] and [2Fe-2S] RirA species (see the solid lines in the plots of Figure 4). Rate constants obtained from the fit to the reaction scheme are given in Table 1.

Table 1
Rate constants resulting from global fit of experimental ESI-MS data using the model shown in Figure 5.
https://doi.org/10.7554/eLife.47804.011
Reaction stepRate constant (min−1)*,† Reaction step
Anaerobic (-O2)Aerobic (+O2)
k10.300 ± 0.0100.320 ± 0.020[4Fe-4S] → [3Fe-4S] + Fe
k-14.67 ± 0.33 × 1034.67 ± 0.43 × 103[3Fe-4S] + Fe → [4Fe-4S]
k20.090 ± 0.0020.230 ± 0.010[3Fe-4S] → [3Fe-3S]
k30.500 ± 0.0101.200 ± 0.050[3Fe-3S] → [2Fe-2S]
k40.070 ± 0.0010.200 ± 0.005[2Fe-2S] → apo
k50.008 ± 0.0020.007 ± 0.002[4Fe-4S] → [4Fe-3S]
k60.087 ± 0.0030.087 ± 0.008[4Fe-3S] → [3Fe-3S]
k70.083 ± 0.0010.150 ± 0.008[4Fe-3S] → [3Fe-2S]
k80.030 ± 0.0010.026 ± 0.020[3Fe-3S] → [3Fe-2S]
k90.044 ± 0.0040.140 ± 0.002[3Fe-2S] → [2Fe-2S]
k100.160 ± 0.0040.300 ± 0.010[3Fe-2S] → apo
  1. *With the exception of k-1, which is a second order rate constant with units of M−1 min−1.

    Standard errors are indicated.

The mechanistic scheme indicates that loss of a single iron or sulphide ion appears to be an obligatory first step in the cluster conversion process. However, the rate constant describing the loss of a sulphide to generate [4Fe-3S] is extremely low, indicating that this reaction does not occur as a significant part of the (chemical) conversion mechanism and that the observation of a [4Fe-3S] species (which is present at time zero following addition of EDTA) results from damage to the cluster during ionisation. It is important to note that the extent of cluster damage is low and this does not affect the mechanistic picture of the cluster conversion/degradation reaction that emerges. Thus, loss of an initial iron, [4Fe-4S] to [3Fe-4S], is the heavily favoured route for the initiation of cluster conversion. Another important feature of the global fit is that the first step, loss of Fe2+ from [4Fe-4S]2+, is reversible.

The overall rate of cluster conversion observed here is significantly higher than that previously reported from absorbance kinetic experiments (Pellicer Martinez et al., 2017). To confirm that ESI-MS and absorbance spectroscopy report on the same process, cluster degradation was followed by monitoring A382 nm (corresponding to the maximum absorbance of the [4Fe-4S] cluster) as a function of time for a [4Fe-4S] RirA sample in volatile ammonium acetate buffer (necessary for ESI-MS measurements) rather than the HEPES buffer previously used (Pellicer Martinez et al., 2017), see Figure 4F. The decay fitted well to a bi-exponential function, where the initial, more rapid phase must correspond to the loss of the [4Fe-4S] cluster (in which it converts to a species that cannot be identified by its absorbance alone), followed by a slower phase that corresponds to further decay of the cluster. The rate constant for the initial phase, k = 0.34 min−1, is in excellent agreement with the rate constant (k = 0.30 min−1) for the conversion of [4Fe-4S] to [3Fe-4S], derived from the ESI-MS kinetic data (Table 1). Though [4Fe-4S] and [3Fe-4S] clusters often have similar absorbance extinction coefficients, loss of Fe2+ from the RirA [4Fe-4S]2+ cluster would be expected to result in some change in the UV-visible absorbance spectrum, as observed here and for a similar process in aconitase (Emptage et al., 1983). Thus, the enhanced rate of conversion reported here is not a consequence of the ESI-MS method, but rather reflects the different buffer conditions used here compared to those of the previous study (Pellicer Martinez et al., 2017). The RirA cluster is clearly more labile in the ammonium acetate buffer, most likely because acetate is a weak iron chelator.

The ESI-MS data show that the [3Fe-3S] RirA species was formed from [3Fe-4S] and [4Fe-3S] clusters with similar observed rate constants (k = 0.090 and 0.087 min−1, respectively). The temporal behaviour of the [3Fe-3S] intermediate, where it was observed to maximise at ~4 min before decaying away, is consistent with it being an intermediate in the [4Fe-4S] to [2Fe-2S] cluster conversion pathway. A novel [3Fe-3S] intermediate was recently observed by mass spectrometry during the O2-dependent [4Fe-4S] to [2Fe-2S] cluster conversion reaction of FNR (Crack et al., 2017). The observation of a similar intermediate here suggests that it may be a more widespread feature of [4Fe-4S] cluster conversions. While the structure of this particular [3Fe-3S] intermediate was not established, that of a small molecule [3Fe-3S]3+ cluster was recently published, revealing a planar hexagonal arrangement of alternating iron and sulphide ions (Lee et al., 2016). If the [3Fe-3S] intermediate of RirA has a similar planar structure (Figure 5), it would reveal a key feature of the [4Fe-4S] to [2Fe-2S] cluster conversion, in which the geometry of the coordinating ligands changes from tetrahedral (for the [4Fe-4S] cluster) to planar (for the [2Fe-2S] cluster).

[3Fe-3S] RirA degraded predominantly to form [2Fe-2S] (k = 0.5 min−1), before finally generating apo-RirA (k = 0.07 min−1). The mechanistic scheme indicates that [3Fe-3S] may also decay to [3Fe-2S] and then on to apo-RirA (in part via [2Fe-2S]). It is recognised that additional intermediate species are likely to be involved in the degradation of [3Fe-2S]/[2Fe-2S] to apo-RirA. While a [2Fe-S] form was observed in mass spectra, its temporal behaviour could not be sensibly modelled, suggesting that it might, at least in part, arise from spontaneous re-assembly of cluster fragments as iron/sulphide ions are released during cluster conversion/degradation.

The effect of O2 on [4Fe-4S] RirA cluster conversion revealed by mass spectrometry

Previous studies of [4Fe-4S] RirA showed that the cluster is sensitive to O2, undergoing conversion in an apparently similar manner to that observed under low iron conditions (Pellicer Martinez et al., 2017). To gain a much more detailed view of this aspect of the conversion process, [4Fe-4S] RirA was investigated using non-denaturing ESI-MS under low iron conditions in the presence of O2 (228 µM). Cluster conversion/breakdown species were observed to form and decay as a function of time, Figure 6 and Table 1. Plots of the individual cluster intermediate species as a function of time, Figure 7, revealed marked differences to those in the absence of O2. We note that the presence of O adducts in experiments carried out under anaerobic conditions suggested that some O2 might be generated during the ESI-MS experiment; however, the differences observed between the anaerobic and aerobic experiments suggest that this is relatively minor. Indeed, the formation of several intermediates, including the [3Fe-3S] and [2Fe-2S] forms, occurred significantly more rapidly under aerobic conditions, consistent with previous observations that a combination of low iron and O2 enhanced the rate of cluster conversion/degradation (Pellicer Martinez et al., 2017). Interestingly, the formation of sulphur adducts of apo-RirA, which were confirmed to be derived from cluster sulphide by 34S-dependent mass shifts (Figure 6—figure supplement 1), occurred to a much greater extent in the presence of O2, consistent with O2 acting as oxidant for S2- ions released from the cluster (Figure 6). Low abundance peaks due to oxygen adducts (the first at apo-RirA +16 Da) were also observed (Figure 6—figure supplement 1). The temporal behaviour of the double sulphur adduct of apo-RirA is shown in Figure 7E.

Figure 6 with 1 supplement see all
ESI-MS analysis of [4Fe-4S] RirA cluster conversion under aerobic, low iron conditions.

(A) Deconvoluted mass spectrum of [4Fe-4S] RirA prior to the addition of 250 µM EDTA (black line) and 30 min after the addition at 37°C (red line). (B) and (C) Deconvoluted mass spectra measured at intervening times: 0–6 min (relative to the addition of EDTA/O2, spectra recorded at 2 min intervals) (B) and 6–30 min (C). Starting and endpoint spectra are in black and red, respectively (corresponding to the data in (A). (D) 3D plot of time-dependent changes in the ESI-MS spectrum showing the formation and decay of RirA cluster intermediates and formation of apo-RirA products. [4Fe-4S] RirA (~25 µM) was in aerobic (~228 µM O2) 250 mM ammonium acetate pH 7.3. Low iron conditions were generated by the addition of 250 µM EDTA and cluster conversion/degradation was followed at 37°C.

https://doi.org/10.7554/eLife.47804.012
Kinetic analysis of [4Fe-4S] RirA cluster conversion/degradation in the presence of O2.

(A) Plots of relative ESI-MS abundances of [4Fe-4S] cluster (black) and [3Fe-4S] (yellow) species as a function of time following exposure to 250 µM EDTA and 228 µM O2 at 37° C, as shown in Figure 6. Normalised A382 nm data (see panel F) are plotted in purple, revealing the close correspondence between the absorbance and [4Fe-4S] decay. Inset is a plot of ESI-MS data for the [4Fe-3S] species. (B) – (D) As in (A) but showing plots of relative abundances of [3Fe-3S] (B), [3Fe-2S] (C), and [2Fe-2S] (D) cluster intermediates. (E) Plot of relative abundance of the double sulphur adduct of apo-RirA. Fits of the data generated by a global analysis of the ESI-MS data, based on the reaction scheme depicted in Figure 5, are shown as solid lines. Broken lines correspond to the kinetic profile of the cluster species associated with that colour and are included to permit easy comparison between intermediates. Error bars show standard error for ESI-MS datasets (n = 2 derived from two technical replicates). (F) Plot of A382 nm versus time following addition of 250 µM EDTA and 228 µM O2 to [4Fe-4S] RirA (30 µM in cluster) at 37° C. The red line indicates a fit of the data generated using a single exponential function. The origin of the residual A382 nm at 30 min, discussed in the legend of Figure 4, may be somewhat different in the presence of O2, where significantly more sulphide undergoes oxidation.

https://doi.org/10.7554/eLife.47804.014

A global analysis of the aerobic kinetic ESI-MS data was achieved on the basis of the same mechanistic scheme employed for the analysis of anaerobic data (Figure 5) - see the solid lines in the kinetic plots of Figure 7. The rate constants obtained from the fit are consistent with the enhanced rates of several steps in the conversion mechanism in the presence of O2 (Table 1). As a control, absorbance spectroscopy was again used to monitor the decay of A382 nm as a function of time for an aerobic [4Fe-4S] RirA sample in ammonium acetate buffer (Figure 7F). In contrast to the equivalent anaerobic experiment (Figure 4F), the data were fitted well by a single exponential function with a rate constant, k = 0.34 min−1, again in excellent agreement with that obtained for the initial, [4Fe-4S] to [3Fe-4S] step of the cluster conversion reaction (Table 1).

The effect of O2 on [4Fe-4S] RirA cluster conversion revealed by EPR spectroscopy

Previous studies of RirA revealed that a paramagnetic species was formed in RirA samples under oxidative conditions (Pellicer Martinez et al., 2017). Thus, EPR spectroscopy was employed here to monitor the formation of paramagnetic intermediates as a function of time following exposure to low iron conditions in the presence of O2. To facilitate direct comparison of kinetic data, samples were prepared at the same concentration, in the same buffer and at the same temperature as used for the mass spectrometric studies. An S = ½ signal at g = 2.01, similar to that previously reported for RirA (Pellicer Martinez et al., 2017), was observed, which was assigned to the [3Fe-4S]1+ cluster intermediate (Figure 8A). However, the detection of a [3Fe-3S] intermediate also raised the possibility that this species might be responsible for the EPR signal, as recently proposed for cluster conversion in [4Fe-4S] FNR (Crack et al., 2017).

Figure 8 with 2 supplements see all
EPR analysis of [4Fe-4S] RirA cluster conversion under aerobic and anaerobic low iron conditions.

(A) EPR spectra of [4Fe-4S] RirA at specified time points following the addition of 250 µM EDTA under aerobic conditions at 37°C. (B) Plot of g = 2.01 EPR signal intensity dependence on temperature at a range of microwave powers. The dashed red line represents a hyperbolic 1/T function plotted in arbitrary units to represent the Curie law (when no saturation effects take place). All experimental dependences are individually scaled so that each meets the hyperbola via at least one data point, with remaining data points lying below the hyperbola (indicating that the signal saturates). (C) Plot of ESI-MS relative abundances of RirA [3Fe-4S] cluster as a function of time following exposure of RirA [4Fe-4S] to 250 µM EDTA at 37° C and aerobic conditions (yellow triangles) and RirA [3Fe-4S]1+ cluster determined under identical condition by EPR under aerobic (+O2, white-filled circles) and anaerobic (-O2, blue-filled circles) conditions. The solid yellow line represents the global fit to the ESI-MS data (as shown in Figure 7). (D) As in (A) but under anaerobic conditions. [4Fe-4S] RirA (~25 µM) was in aerobic (~228 µM O2) 250 mM ammonium acetate pH 7.3.

https://doi.org/10.7554/eLife.47804.015

So, to investigate the EPR-active species in more detail, the saturation properties of the g = 2.01 EPR signal were studied as a function of microwave power and temperature (Figure 8—figure supplement 1). Signal intensities as a function of temperature at six microwave power values were plotted (Figure 8B and Figure 8—figure supplement 2). The inclusion of a 1/T hyperbola (Figure 8B) reveals the narrow temperature interval in which the EPR signal follows the Curie law (based on non-saturated and non-broadened lines originating from an undisturbed Boltzmann distribution of energy levels populations) for each microwave power. At a very low microwave power, such as 3.2 µW, the EPR signal perfectly obeyed the Curie law in the explored temperature range of 4–15 K. As the power was increased, the temperature dependence in the 4–9 K region became lower, indicating power saturation at these temperatures for all powers ≥ 100 µW. At temperatures above ~20 K, all dependences deviated from the Curie hyperbola, which is an effect of line broadening. No microwave power was able to produce any detectable EPR absorbance at temperatures above 50 K. This is a particular characteristic of [3Fe-4S]1+ clusters; they exhibit the most sensitive dependence on increasing temperature, with signal disappearing at a lower temperature than for any other cluster type (Svistunenko et al., 2006). Such microwave power saturation behaviour, as well as the g-value and EPR line shape are highly characteristic of well-characterised [3Fe-4S]1+ clusters (Beinert and Thomson, 1983; Cammack, 1992) and so we conclude that, in the case of RirA, the EPR active species is the [3Fe-4S]1+ cluster. It is perhaps surprising that none of the other intermediates identified by ESI-MS are detected by EPR; it appears that such species are diamagnetic.

To determine the kinetic properties of the RirA [3Fe-4S]1+ intermediate, EPR measurements were performed for samples prepared at a range of time points following exposure to aerobic low iron conditions, Figure 8A. Quantification of the g = 2.01 signal revealed that ~ 1 µM (~4%) of the cluster was present in the [3Fe-4S]1+ form at time zero, prior to the introduction of chelator and O2. The signal intensity increased with time up to ~4.5 µM (~18% of the original cluster concentration) by 3 min before decaying away over the next 15 min (Figure 8A and C). The [3Fe-4S]1+ cluster contains three Fe3+ ions, meaning that it is formed from a [4Fe-4S]2+ cluster through loss of a Fe2+ ion and oxidation of the remaining Fe2+ to Fe3+. EPR measurements were also carried out for [4Fe-4S] RirA samples under identical conditions except that O2 was omitted (Figure 8D). A signal similar to that observed in the aerobic experiment was detected, but at a significantly lower concentration. Beginning at ~4% of original cluster concentration, the signal increased only to ~6.5% after 5 min, then remained at that level up to ~15 min before returning to its pre-EDTA exposure concentration (Figure 8C and D). We note that the [3Fe-4S]1+ signal does not entirely decay away under either aerobic or anaerobic conditions. One possibility is that this low intensity residual signal represents an ‘off pathway’ form of the cluster that is less reactive.

The first step of 4Fe-4S] RirA cluster conversion is the O2-independent reversible loss of Fe2+ to form [3Fe-4S]

While the presence of O2 enhances several of the steps of cluster conversion/degradation, importantly, this is not the case for the initial reversible step in which the cluster loses a Fe2+ ion to form the [3Fe-4S] intermediate: rate constants for the initial step (principally loss of iron) are similar under aerobic and anaerobic conditions. However, the oxidation state of the [3Fe-4S] cluster is affected by the presence of O2. A comparison of the ESI-MS data for [3Fe-4S] from Figure 7B and the EPR intensity data for [3Fe-4S]1+ is shown in Figure 8C. The data are generally in good agreement for the aerobic experiment. There is a slight lag in the appearance of the EPR signal relative to the ESI-MS [3Fe-4S] peak, which could arise from the initial formation of the EPR silent [3Fe-4S]0 intermediate, followed by its oxidation to the [3Fe-4S]1+ form in the presence of O2. In the anaerobic experiment, the observed intensity of the [3Fe-4S]1+ cluster is much lower, consistent with the major form being the EPR silent [3Fe-4S]0 form. In combination, the ESI-MS and EPR data show that a [3Fe-4S] cluster intermediate is formed in both the absence and presence of O2 (at similar abundance as judged by ESI-MS), but it is predominantly present in different oxidation states, being largely in the reduced [3Fe-4S]0 form under anaerobic conditions and in the oxidised [3Fe-4S]1+ form under aerobic conditions.

The insensitivity of the initial step to O2 revealed here by time-resolved ESI-MS is consistent with the previous observation that the rate of the [4Fe-4S] to [2Fe-2S] cluster conversion reaction is O2-independent, leading to the conclusion that the rate-limiting step of the reaction does not involve O2 (Pellicer Martinez et al., 2017). While the overall rates of reaction in the ammonium acetate buffer used here for ESI-MS and EPR experiments are greater than those previously reported, the global analyses indicate that, when O2 is present, the initial reaction (corresponding to the loss of a single iron (as Fe2+) from the [4Fe-4S]2+ cluster) is, or is close to, the rate-limiting step (Table 1). This accounts for why the absorbance decay at 382 nm follows a single exponential in the presence of O2 but a bi-exponential in the absence of O2: in the former condition, the initial and subsequent reaction ([3Fe-4S] to [3Fe-3S]) occur at similar rates, while under anaerobic conditions, the second step is significantly slower. The independence from O2 of the initial step is consistent with RirA functioning principally as an iron sensor.

In considering the question of why O2 should significantly affect the [3Fe-4S] to [3Fe-3S] conversion, it is likely that the [3Fe-4S]1+ species resulting from O2-mediated oxidation of the initially formed [3Fe-4S]0 cluster is more labile, and differences in oxidation state of intermediate cluster irons could be an important stability factor throughout. Another factor that is likely to be of at least equal importance is the enhanced oxidation of cluster sulphide in the presence of O2, which would be expected to accelerate the degradation of the [3Fe-4S], [3Fe-3S] and [2Fe-2S] forms towards apo-RirA. A comparison of the rate constants in Table 1 suggests that both sulphide and iron oxidation processes are important for the overall enhanced rate of degradation towards apo-RirA in the presence of O2.

Determination of the Kd for binding of the fourth iron of the RirA [4Fe-4S] cluster

The data presented above point to the equilibrium [4Fe-4S]2+ ↔ [3Fe-4S]0 + Fe2+, as being key for iron sensing. If this is the case, then the binding affinity of the fourth iron should reflect the likely ‘free’ iron concentration of the cell, to which it would need to respond. Levels of ‘free’ or chelatable iron have not been reported for R. leguminosarum, but have been measured for Escherichia coli, in which it was found to be ~10 µM (Keyer and Imlay, 1996), and there are no a priori reasons why those in other proteobacteria should be very different.

Mag-fura-2, which binds Fe2+ to form a 1:1 complex with a Kd of 2.05 µM, has been used previously to probe Fe2+-binding to proteins (Rodrigues et al., 2015). A titration of [4Fe-4S] RirA with an increasing concentration of mag-fura-2 was carried out. Importantly, the concentration of Fe2+-mag-fura-2 formed at the end of the titration corresponded to ~1 iron per [4Fe-4S] cluster (Figure 9), confirming that the process being measured corresponded to the [4Fe-4S]2+ ↔ [3Fe-4S]0 + Fe2+ equilibrium, and that no further cluster (conversion/degradation) reaction occurred on the timescale of the measurement. Resulting spectra were corrected for contributions from the underlying FeS cluster absorbance and normalised, as described in Materials and methods, see Figure 9. The data describe the increasing proportion of Fe2+ that is bound by the ligand and are fitted by a simple binding isotherm, yielding an apparent Kd that reflects the competition between mag-fura-2 and [3Fe-4S] RirA for Fe2+, from which the dissociation constant for RirA was readily determined as Kd = 3 ± 0.2 µM. This value is entirely consistent with the [4Fe-4S]2+ ↔ [3Fe-4S]0 + Fe2+ equilibrium functioning as the iron-sensing reaction.

Determination of the binding affinity of the fourth iron of the RirA [4Fe-4S] cluster.

(A) Normalised UV-visible absorbance spectra showing the ratio of apo- and Fe2+-bound mag-fura-2 upon addition of increasing concentrations of mag-fura-2 to [4Fe-4S] RirA (7 µM) was in 25 mM HEPES, 50 mM NaCl, 750 mM KCl, pH 7.5. In addition to the titration spectra (solid grey lines), spectra of fully apo- (dashed line) and Fe2+-bound (dotted line) forms of mag-fura-2 are shown. Arrows denote the direction of absorbance change upon increasing concentration of mag-fura-2. (B) Plot of extent of Fe2+-mag-fura-2 complex formation (determined from data at 366 nm and expressed as fractional saturation, where one equals one Fe2+ per initial [4Fe-4S] cluster) as a function of concentration of free mag-fura-2. The data were fitted using a simple binding isotherm, giving an apparent Kd, which reflects the competition between mag-fura-2 and RirA for iron. From this, the Kd for binding of the fourth iron to the RirA cluster was determined as ~3 µM as described in Materials and methods.

https://doi.org/10.7554/eLife.47804.018

Iron-responsive cluster conversion in dimeric [4Fe-4S] RirA revealed by mass spectrometry

Conditions for the detection of the RirA dimer by ESI-MS were optimised (Pellicer Martinez et al., 2017) and time-resolved ESI-MS was used to follow cluster degradation in the RirA dimer under anaerobic conditions, see Figure 10A. The major species prior to addition of iron chelator were the [4Fe-4S]/[4Fe-4S] and [3Fe-4S]/[4Fe-4S] forms. In the dimer, the presence of two clusters in many cases precludes unambiguous identification of the intermediates because the distribution of iron and sulphur across the two clusters is unknown. Furthermore, there are many more possible intermediates of the dimer as each of the two clusters undergoes conversion/degradation. Nevertheless, the temporal behaviour of tentatively assigned species could be fitted to a basic model of cluster conversion in dimeric RirA, see Figure 10—figure supplement 1. Plots of relative abundance of [4Fe-4S]/[4Fe-4S], [3Fe-4S]/[3Fe-4S], and [2Fe-2S]/[2Fe-2S] forms and fits to the global model are shown in Figure 10B, with rate constants in Supplementary file 2. Additional plots of [3Fe-4S]/[4Fe-4S], [2Fe-2S]/[3Fe-4S], [apo]/[2Fe-2S] and [apo]/[apo] are shown in Figure 10—figure supplement 2. A plot comparing the time dependence of the EPR signal intensity due to [3Fe-4S]1+ forms under aerobic and anaerobic conditions with the ESI-MS abundance of the [3Fe-4S]/[3Fe-4S] species is shown in Figure 10—figure supplement 3. As in the case of the monomer, the aerobic ESI-MS and EPR data are in good agreement, consistent with the susceptibility of the [3Fe-4S]0 cluster to oxidation.

Figure 10 with 3 supplements see all
Time-resolved ESI-MS analysis of dimeric RirA cluster conversion under anaerobic, low iron conditions.

(A) Deconvoluted mass spectrum of [4Fe-4S] RirA prior to the addition of 250 µM EDTA (black line) and 30 min after the addition at 37°C (red line) and at intervening time points (grey lines). [4Fe-4S] RirA (~25 µM) was in aerobic 250 mM ammonium acetate pH 7.3. Low iron conditions were generated by the addition of 250 µM EDTA and cluster conversion/degradation was followed at 37°C. The peak at +294 Da could represent an EDTA adduct of the apo-RirA dimer. (B) Plots of relative ESI-MS abundances of [4Fe-4S]/[4Fe-4S] (black), [3Fe-4S]/[3Fe-4S] (yellow), and [2Fe-2S]/[2Fe-2S] (red) forms of RirA as a function of time following exposure to 250 µM EDTA at 37° C. Fits of the data generated by a global analysis of the ESI-MS data based on the reaction scheme depicted in Figure 10—figure supplement 1 are shown as solid lines. Error bars show standard error for ESI-MS dataset (n = 2 derived from two biological replicates).

https://doi.org/10.7554/eLife.47804.019

We note that [3Fe-3S]/[3Fe-4S] and [3Fe-3S]/[3Fe-3S] cluster intermediates were not clearly observed; signals at the predicted masses for these species were observed, but only at very low intensities, indicating that these forms are reactive intermediates during the dimer cluster conversion process and therefore do not accumulate. Importantly, the rate constant derived from the global fit for the initial reversible loss of Fe2+ is very similar to that obtained from analysis of the monomer state (0.31 compared to 0.30 min−1, Table 1 and Supplementary file 2). Finally, the extent of sulphur adduct formation was greater than observed in the monomer region under equivalent conditions. Thus, within the limits of what we are able to observe, the RirA dimer behaved similarly to the monomer, consistent with monomer species forming from dimers during the measurement.

Conclusions

The global iron regulator RirA differs in many respects from the well characterised bacterial iron regulator Fur, and so a distinct model is needed to account for how it senses and responds to the intracellular iron status. Data from ESI-MS under non-denaturing conditions, including 34S isotope exchange, along with EPR spectroscopy, have provided a highly detailed view of the [4Fe-4S] RirA cluster degradation reactions in response to low iron and O2, another key environmental signal. In particular, the work further illustrates the remarkable potential of ESI-MS to provide time-resolved information on metallo-cofactor reactivity (that involves a change in mass), which is not available from other techniques. As shown in Figure 5, the mechanism involves a complex series of events initiated by the loss of iron, resulting in a [3Fe-4S] intermediate that decays further to [3Fe-3S], [3Fe-2S] and [2Fe-2S] species along the pathway to apo-RirA. Importantly, ESI-MS and absorbance data showed that the iron (Fe2+) dissociation step occurs at a similar rate under both aerobic and anaerobic conditions, consistent with RirA functioning principally as an iron sensor.

Thus, the data presented here enabled us to elucidate at a molecular level the changes that occur in the transition from Fe-replete to Fe-depleted conditions. We propose a model in which the RirA [4Fe-4S]2+ cluster continually undergoes Fe2+ dissociation, to form a [3Fe-4S]0 form, and, under iron replete conditions, re-association to re-form [4Fe-4S]2+. When cellular iron becomes scarce, competition for the dissociated Fe2+ increases, and re-association is disfavoured. In order to effectively sense cytoplasmic iron levels, the affinity (dissociation constant) of the fourth cluster iron must be in the range of normal free (chelatable) iron levels. Although unknown for R. leguminosarum, cytoplasmic free iron has been measured for E. coli and found to be ~10 µM (Keyer and Imlay, 1996). Assuming that free iron levels are not very different in R. leguminosarum, the Kd of ~3 µM determined here for the [3Fe-4S]0 + Fe2+ ↔ [4Fe-4S]2+ equilibrium is entirely consistent with an iron-sensing function. Indeed, we note that Fur, the iron-sensing regulator of E. coli, binds Fe2+ with a Kd of ~1–10 µM (Bagg and Neilands, 1987; Mills and Marletta, 2005).

Although done in vitro, the parameters that emerged are in keeping with its role as a Fe-responsive regulator in vivo. Here, as previously (Pellicer Martinez et al., 2017), we have used the iron chelator EDTA to simulate low iron, via its ability to coordinate Fe2+ that has dissociated from the RirA [4Fe-4S] cluster. While EDTA is clearly not a physiological ligand, it nevertheless induces low iron conditions by providing a sink for iron that simulates conditions under which cluster degradation occurs. Conditions such as this must exist in the cytosol of cells growing under iron-limiting conditions, where a myriad of iron-requiring systems are in competition for available iron, and where a drop in ‘free’ iron levels results in loss of RirA-mediated transcriptional repression leading to up-regulation of iron uptake systems.

Competitive loss of Fe2+ from [4Fe-4S]2+ RirA results in a [3Fe-4S]0 form that is unstable, undergoing degradation to an apo-form. This lability under low iron conditions is not a general property of [4Fe-4S] clusters, as previously demonstrated for the closely related [4Fe-4S] NsrR (Pellicer Martinez et al., 2017). This raises the question of why the RirA cluster is so fragile. One possibility is that the cluster is bound to the protein only by the three conserved Cys residues, with the tetrahedral coordination of the non-Cys bound iron completed by a weakly interacting ligand such as water or hydroxide. Such an arrangement, which would enhance the lability of the site-differentiated iron of the [4Fe-4S] cluster, would be similar to that found in the mammalian iron sensor protein IRE-BP (iron regulatory element-binding protein) (Dupuy et al., 2006), and it is tempting to speculate that this may be a general feature of iron-sensing iron–sulphur clusters. We also note that the key step of iron-sensing in RirA, the simple equilibrium [4Fe-4S]2+ ↔ [3Fe-4S]0 + Fe2+, mirrors the iron-sensing step of the better known bacterial global iron regulators Fur and DtxR in which Fe2+ binds the apo-form of these proteins (Lee and Helmann, 2007; Pohl et al., 2003; D'Aquino et al., 2005; Ding et al., 1996). However, the relative complexity of the RirA cofactor (co-repressor) enables it to also directly sense O2.

A key step for O2-sensing is the oxidation of [3Fe-4S]0 to [3Fe-4S]1+. The [3Fe-4S]1+ intermediate was more reactive than the [3Fe-4S]0 form, and several other subsequently formed intermediates also showed higher reactivity, leading to an overall enhanced rate of degradation (Figure 5 and Table 1). The susceptibility of cluster iron and sulphide to oxidation in the presence of O2 clearly drives the increased rate of cluster degradation. Thus, the [3Fe-4S]0 cluster formed via the reversible dissociation of Fe2+ from [4Fe-4S]2+ RirA is susceptible to oxidation in the presence of O2. We propose that, even under iron-replete conditions, in the presence of O2 some oxidation of the RirA [3Fe-4S]0 form occurs before it can re-associate with Fe2+, resulting in cluster degradation.

Understanding how iron and O2 signals are sensed and integrated is important for all organisms that depend on both iron and O2. In the case of R. leguminosarum, RirA regulates not only iron uptake, but also iron–sulphur cluster biogenesis (Todd et al., 2006). The RirA O2-sensing mechanism enables the cell to meet the requirement for iron–sulphur cluster biosynthesis under aerobic conditions (Imlay, 2006). Under low iron and in the presence of O2, cluster degradation occurs more readily as a result of the combined effects of competition for iron and the enhanced rate of cluster degradation under oxidising conditions. The rate at which cluster conversion/degradation occurs is relatively slow, particularly compared to the rate at which the [4Fe-4S] ↔ [3Fe-4S] equilibrium is established. In some cases at least, sensing processes are relatively slow reactions. For example, the master regulator of the aerobic/anaerobic switch in many bacteria, [4Fe-4S] FNR, undergoes a similar [4Fe-4S] to [2Fe-2S] cluster conversion reaction over minutes (Crack et al., 2008; Crack et al., 2007), with in vivo transcriptional responses occurring over a similar timescale (Partridge et al., 2007). Responses to changes in iron levels mediated by Fur also occur over several minutes (Pi and Helmann, 2017). Thus, the cellular response to change does not necessarily need to occur instantly, perhaps reflecting that environmental changes themselves may occur over a period of time. The similarities between the FNR cluster conversion mechanism (Crack et al., 2017) and that described here for RirA are remarkable in that the two proteins have no sequence or structural similarity beyond the cluster, and FNR does not sense iron levels; its cluster is stable in the presence of iron chelators (Crack et al., 2008).

The advances reported here are relevant to all species that utilise RirA as a regulator, including several important pathogens of plants and animals. This work also contributes important new information about the widespread Rrf2 family of iron–sulphur cluster-binding regulators, and the variable ways in which they employ a cluster to sense environment change. Finally, it opens up new questions about RirA function, including: the nature of the cluster coordination; whether the Kd for the [4Fe-4S]2+ ↔ [3Fe-4S]0 + Fe2+ equilibrium and the mechanism of cluster disassembly are affected by [4Fe-4S] RirA complex formation with DNA; which steps of the degradation pathway are key for loss of DNA-binding; and, whether disruption of one cluster is sufficient to modulate DNA-binding of the RirA dimer. Efforts to address these are currently underway.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or referenceIdentifiersAdditional information
Gene (Rhizobium leguminosarum strain 8401)rirANACAC35510
Peptide, recombinant proteinR. leguminosarum RirAPellicer Martinez et al., 2017
Peptide, recombinant proteinAzotobacter vinelandii NifSCrack et al., 2014bThe nifS plasmid was a kind gift from Prof. Dennis Dean (Virginia Tech)
Chemical compound, drug34S L-cysteineCrack et al., 2019
Software, algorithmOriginOrigin LabVersion 8
Software, algorithmDynaFitBioKin Ltd; Kuzmic, 1996RRID:SCR_008444Version 4

Purification and reconstitution of [4Fe-4S] RirA

Request a detailed protocol

R. leguminosarum RirA was over-expressed in E. coli and purified as previously described (Pellicer Martinez et al., 2017). In vitro cluster reconstitution to generate [4Fe-4S] RirA was carried out in the presence of NifS, as described previously (Crack et al., 2014b). Protein concentrations were determined using the method of Bradford (Bio-Rad), with bovine serum albumin as the standard. Cluster concentrations were determined by iron and sulphide assays (Crack et al., 2006; Beinert, 1983) or by using an absorbance extinction coefficient at 383 nm for the RirA [4Fe-4S] cluster of 13,460 ± 250 M−1 cm−1 (Pellicer Martinez et al., 2017 ). 34S labelled [4Fe-4S] RirA was generated by reconstitution using 34S-L-cysteine as previously described (Crack et al., 2019).

Preparation of samples under low iron and low iron/aerobic conditions

Request a detailed protocol

[4Fe-4S] RirA was exchanged into anaerobic 250 mM ammonium acetate, pH 7.3, using a desalting column (PD-10, GE Healthcare) in an anaerobic glove box (O2 < 2 ppm) and diluted to ~30 µM cluster using the same buffer. To simulate low iron conditions, the soluble high affinity iron chelator EDTA (Fe2+-EDTA, logK = 14.3, Fe3+-EDTA, logK = 25.1) (Martell and Smith, 1974) was added at 250 µM (final concentration) and the cluster response was followed via spectroscopy or mass spectrometry. To investigate the sensitivity of [4Fe-4S] RirA to low iron conditions in the presence of O2, anaerobic protein samples in 250 mM ammonium acetate, pH 7.3, were rapidly diluted with an air-saturated buffer containing EDTA to give the desired final O2 and EDTA concentrations and the sample was infused directly into the mass spectrometer via a syringe pump thermostatted at 37°C, or incubated at 37°C prior to rapid freezing in liquid nitrogen for EPR measurements. For absorbance experiments, 500 µM glutathione (GSH) was added to the sample to help solubilise oxidised sulphur species that otherwise caused significant scattering of light.

Determination of Fe2+-binding affinity via competition assay

Request a detailed protocol

The dissociation constant (Kd) for Fe2+ binding to [3Fe-4S]0 RirA was determined using an Fe2+-binding competition assay employing the well-known divalent metal ligand mag-fura-2 (Rodrigues et al., 2015). Mag-fura-2 forms a 1:1 complex with Fe2+, resulting in a shift of absorbance maximum from 366 nm (for metal-free mag-fura-2) to 325 nm (Rodrigues et al., 2015). Mag-fura-2 was dissolved in ultra-pure water to give a 2 mM stock solution and stored at −80°C until needed. Titrations of ~7 µM [4Fe-4S] RirA in 25 mM HEPES, 50 mM NaCl, 750 mM KCl, pH 7.5 with mag-fura-2 were carried out under anaerobic conditions at room temperature. Optimisation experiments showed that absorbance changes due to Fe2+-binding to the Mag-fura-2 occurred quickly and so UV-visible spectra were recorded using a Jasco V500 spectrometer immediately following each addition of the chelator, such that the titration was complete within ~60 min. Overnight incubation of RirA with Mag-fura-2 led to cluster conversion/breakdown, and increased coordination of Fe2+ to the chelator. Thus, the dissociation of a single Fe2+ from the [4Fe-4S]2+ cluster occurred on a very different timescale to cluster conversion, permitting investigation of the [4Fe-4S] to [3Fe-4S] equilibrium.

A potential difficulty of using this or any ligand that gives rise to absorbance in the UV-visible region is that its absorbance spectrum overlaps that of the RirA cluster. Furthermore, the absorbance due to the cluster changes upon loss of a single Fe2+, and so a robust method to correct for these changes was required. Fortunately, the absorbance profiles of apo- and divalent metal-bound mag-fura-2 overlap, with an isosbestic point at 346 nm, providing a means to correct for underlying absorbance changes due to the cluster (Rodrigues et al., 2015; Simons, 1993). Firstly, the spectrum due to initial [4Fe-4S] cluster was subtracted from each subsequent spectrum. Then the data were normalised so that the resulting nest of spectra reported on the changing proportions of Fe2+-bound and apo-mag-fura-2. Finally, spectra were corrected for any changes in the subtracted cluster spectrum using a scaling factor that preserved the isosbestic point. Spectra of mag-fura-2 in apo and Fe2+ forms (in the absence of RirA) were used to assist with this. Changes due to the scaling factor were <0.07 absorbance units, within the range expected for the absorbance change during cluster conversion. From this, the percentage of maximum Fe2+-mag-fura-2 complex present (where 100% equated to the concentration of [4Fe-4S] RirA, that is one Fe2+ per cluster) was plotted as a function of free mag-fura-2. This resulted in a plot with a hyperbolic form, which was fitted with an equation describing a simple binding isotherm using Origin8 (OriginLabs). This yielded an apparent competition dissociation constant from which the Kd for RirA was determined using the expression:

KdMF2 app=KdMF2(1+RirAKdRirA)

Where Kd(MF2 app) is the determined apparent Kd from the competition binding assay, Kd(MF2) is the Kd for mag-fura-2 binding to Fe2+, (previously determined as Kd = 2.05 µM; Rodrigues et al., 2015) and Kd(RirA) is the Kd for [3Fe-4S] binding to Fe2+ (Hulme and Trevethick, 2010). The resulting Kd and standard error was determined from three equivalent titration experiments.

ESI-MS measurements

Request a detailed protocol

[4Fe-4S] RirA samples were infused directly (0.3 mL/h) into the ESI source of a Bruker micrOTOF-QIII mass spectrometer (Bruker Daltonics, Coventry, UK) operating in the positive ion mode, and calibrated using ESI-L Low Concentration Tuning Mix (Agilent Technologies, San Diego, CA). Mass spectra (m/z 500–1750 for RirA monomer; m/z 1,800–3,500 for RirA dimer) were acquired for 5 min using Bruker oTOF Control software, with parameters as follows: dry gas flow 4 L/min, nebuliser gas pressure 0.8 Bar, dry gas 180°C, capillary voltage 2750 V, offset 500 V, ion energy 5 eV, collision RF 180 Vpp, collision cell energy 10 eV. Optimisation of experimental conditions for the transmission of dimeric species was achieved by increasing the capillary voltage to 4000 V and the collision RF to 600 Vpp (Laganowsky et al., 2013).

Processing and analysis of MS experimental data were carried out using Compass DataAnalysis version 4.1 (Bruker Daltonik, Bremen, Germany). Neutral mass spectra were generated using the ESI Compass version 1.3 Maximum Entropy deconvolution algorithm over a mass range of 17,300–18,000 Da for the monomer and 34,850–35,810 Da for the dimer. For kinetic modelling, in order to clearly resolve overlapping peaks, multiple Gaussian functions were fitted to the experimental data using a least-squares regression function in Origin 8 (Origin Lab) (Laganowsky et al., 2013). Exact masses are reported from peak centroids representing the isotope average neutral mass. For apo-proteins, these are derived from m/z spectra, for which peaks correspond to [M + nH]n+/n. For cluster-containing proteins, where the cluster contributes charge, peaks correspond to [M + (Fe-S)x+ + (n-x)H]n+/n, where M is the molecular mass of the protein, Fe-S is the mass of the particular iron–sulphur cluster of x+ charge, H is the mass of the proton and n is the total charge. In the expression, the x+ charge of the iron–sulphur cluster offsets the number of protons required to achieve the observed charge state (n+) (Johnson et al., 2000). Predicted masses are given as the isotope average of the neutral protein or protein complex, in which iron–sulphur cluster-binding is expected to be charge-compensated (Crack et al., 2017; Kay et al., 2016).

Mass spectra are plotted as percentage relative abundances, where the most abundant species is arbitrarily set to 100% and all other species are reported relative to it. Time-resolved MS intensity data for global analysis was processed to generate relative abundance plots of ion counts for the relevant species as a fraction of the total ion count for all species. This permitted changes in relative abundance to be followed without distortions due to variations in ionisation efficiency that normally occur across a data collection run. Some variation in the starting spectrum was observed due to the presence of cluster breakdown products, which affected concentrations of intermediates during the cluster conversion/breakdown process; these variations are represented by error bars in the relative abundance plots of Figures 4 and 7. Such plots were analysed globally using the program Dynafit 4 (BioKin Ltd) (Kuzmic, 1996), which employs nonlinear least-squares regression of kinetic data, based on multi-step mechanisms, from which fits of the experimental data were generated and rate constants estimated, as previously reported (Crack et al., 2017). The presence of breakdown products in the starting spectrum was accounted for by allowing starting abundance to be offset from zero. Briefly, the kinetic model consisted of a series of sequential or branched reactions beginning with the dissociation of Fe2+ from [4Fe-4S]2+ to form [3Fe-4S]0 and the reverse reaction, the binding of Fe2+ to [3Fe-4S]0 to reform the [4Fe-4S]2+ cluster. With the exception of the latter, which is a second order process, all steps in the proposed mechanism are first order. All steps of the mechanism are shown in Figure 5.

Spectroscopy

Request a detailed protocol

Absorbance kinetic data at A386 nm were recorded via a fibre optic link, as previously described (Crack et al., 2007). EPR measurements were made with an X-band Bruker EMX EPR spectrometer equipped with a helium flow cryostat (Oxford Instruments). Unless stated otherwise, EPR spectra were measured at 10 K at the following instrumental settings: microwave frequency, 9.471 GHz; microwave power, 3.18 mW; modulation frequency, 100 kHz; modulation amplitude, 5 G; time constant, 82 ms; scan rate, 22.6 G/s; single scan per spectrum. Relative concentrations of the paramagnetic species were measured using the procedure of spectral subtraction with a variable coefficient (Svistunenko et al., 2006) and converted to absolute concentrations by comparing an EPR spectrum second integral to that of a 1 mM Cu(II) in 10 mM EDTA standard, at non-saturating values of the microwave power. The RirA EPR signal saturation was studied by taking EPR measurements at 13 values of microwave power, ranging from 0.2 µW to 200 mW, at eight temperature values, ranging from 4 K to 50 K. The EPR sample was equilibrated at every new temperature for at least 8 min before the power set of spectra measurements commenced.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. ESI-MS datasets have been deposited at Open Science Framework (http://doi.org/10.17605/OSF.IO/JMF6H). Source data files are available on the Open Science Framework (http://doi.org/10.17605/OSF.IO/H2M4P).

The following data sets were generated
    1. Ma Teresa Pellicer Martinez
    2. Jason C Crack
    3. Melissa YY Stewart
    4. Nick E Le Brun
    (2019) OSF
    ESI-MSanalysis of RirA under anaerobic low iron conditions: monomer region.
    https://doi.org/10.17605/OSF.IO/JMF6H

References

    1. Emptage MH
    2. Dreyers JL
    3. Kennedy MC
    4. Beinert H
    (1983)
    Optical and EPR characterization of different species of active and inactive aconitase
    The Journal of Biological Chemistry 258:11106–11111.
  1. Book
    1. Martell AE
    2. Smith RM
    (1974)
    Critical Stability Constants
    New York: Plenum Press.

Article and author information

Author details

  1. Ma Teresa Pellicer Martinez

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Formal analysis, Investigation, Writing—original draft
    Contributed equally with
    Jason C Crack and Melissa YY Stewart
    Competing interests
    No competing interests declared
  2. Jason C Crack

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Methodology, Writing—original draft
    Contributed equally with
    Ma Teresa Pellicer Martinez and Melissa YY Stewart
    Competing interests
    No competing interests declared
  3. Melissa YY Stewart

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Data curation, Formal analysis, Investigation, Writing—original draft
    Contributed equally with
    Ma Teresa Pellicer Martinez and Jason C Crack
    Competing interests
    No competing interests declared
  4. Justin M Bradley

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Supervision, Methodology, Writing—original draft
    Competing interests
    No competing interests declared
  5. Dimitri A Svistunenko

    School of Biological Sciences, University of Essex, Colchester, United Kingdom
    Contribution
    Data curation, Formal analysis, Supervision, Investigation, Writing—original draft
    Competing interests
    No competing interests declared
  6. Andrew WB Johnston

    School of Biological Sciences, University of East Anglia, Norwich, United Kingdom
    Contribution
    Conceptualization, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
  7. Myles R Cheesman

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Conceptualization, Supervision, Writing—original draft
    Competing interests
    No competing interests declared
  8. Jonathan D Todd

    School of Biological Sciences, University of East Anglia, Norwich, United Kingdom
    Contribution
    Conceptualization, Writing—review and editing
    Competing interests
    No competing interests declared
  9. Nick E Le Brun

    Centre for Molecular and Structural Biochemistry, School of Chemistry, University of East Anglia, Norwich, United Kingdom
    Contribution
    Conceptualization, Supervision, Funding acquisition, Investigation, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    n.le-brun@uea.ac.uk
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9780-4061

Funding

Biotechnology and Biological Sciences Research Council (BB/E003400/1)

  • Andrew WB Johnston
  • Nick E Le Brun

Biotechnology and Biological Sciences Research Council (BB/J003247/1)

  • Nick E Le Brun

Biotechnology and Biological Sciences Research Council (BB/L006140/1)

  • Jason C Crack
  • Nick E Le Brun

Horizon 2020 Framework Programme (CA15133)

  • Nick E Le Brun

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

Acknowledgements

This work was supported by Biotechnology and Biological Sciences Research Council through grants BB/E003400/1, BB/J003247/1 and BB/L006140/1, by UEA through the award of a PhD studentship to MTPM and purchase of the ESI-MS instrument, and by the FeSBioNet COST Action CA15133.

Version history

  1. Received: April 19, 2019
  2. Accepted: July 29, 2019
  3. Version of Record published: September 17, 2019 (version 1)

Copyright

© 2019, Pellicer Martinez et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,093
    Page views
  • 260
    Downloads
  • 24
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Ma Teresa Pellicer Martinez
  2. Jason C Crack
  3. Melissa YY Stewart
  4. Justin M Bradley
  5. Dimitri A Svistunenko
  6. Andrew WB Johnston
  7. Myles R Cheesman
  8. Jonathan D Todd
  9. Nick E Le Brun
(2019)
Mechanisms of iron- and O2-sensing by the [4Fe-4S] cluster of the global iron regulator RirA
eLife 8:e47804.
https://doi.org/10.7554/eLife.47804

Share this article

https://doi.org/10.7554/eLife.47804

Further reading

    1. Biochemistry and Chemical Biology
    2. Developmental Biology
    Zhi Li, Yuedi Wang ... Zeyang Zhou
    Research Article

    Imidacloprid is a global health threat that severely poisons the economically and ecologically important honeybee pollinator, Apis mellifera. However, its effects on developing bee larvae remain largely unexplored. Our pilot study showed that imidacloprid causes developmental delay in bee larvae, but the underlying toxicological mechanisms remain incompletely understood. In this study, we exposed bee larvae to imidacloprid at environmentally relevant concentrations of 0.7, 1.2, 3.1, and 377 ppb. There was a marked dose-dependent delay in larval development, characterized by reductions in body mass, width, and growth index. However, imidacloprid did not affect on larval survival and food consumption. The primary toxicological effects induced by elevated concentrations of imidacloprid (377 ppb) included inhibition of neural transmission gene expression, induction of oxidative stress, gut structural damage, and apoptosis, inhibition of developmental regulatory hormones and genes, suppression of gene expression levels involved in proteolysis, amino acid transport, protein synthesis, carbohydrate catabolism, oxidative phosphorylation, and glycolysis energy production. In addition, we found that the larvae may use antioxidant defenses and P450 detoxification mechanisms to mitigate the effects of imidacloprid. Ultimately, this study provides the first evidence that environmentally exposed imidacloprid can affect the growth and development of bee larvae by disrupting molting regulation and limiting the metabolism and utilization of dietary nutrients and energy. These findings have broader implications for studies assessing pesticide hazards in other juvenile animals.

    1. Biochemistry and Chemical Biology
    2. Cancer Biology
    Pengfei Guo, Rebecca C Lim ... Hui Zhang
    Research Article Updated

    The Polycomb Repressive Complex 2 (PRC2) methylates H3K27 to regulate development and cell fate by transcriptional silencing. Alteration of PRC2 is associated with various cancers. Here, we show that mouse Kdm1a deletion causes a dramatic reduction of PRC2 proteins, whereas mouse null mutation of L3mbtl3 or Dcaf5 results in PRC2 accumulation and increased H3K27 trimethylation. The catalytic subunit of PRC2, EZH2, is methylated at lysine 20 (K20), promoting EZH2 proteolysis by L3MBTL3 and the CLR4DCAF5 ubiquitin ligase. KDM1A (LSD1) demethylates the methylated K20 to stabilize EZH2. K20 methylation is inhibited by AKT-mediated phosphorylation of serine 21 in EZH2. Mouse Ezh2K20R/K20R mutants develop hepatosplenomegaly associated with high GFI1B expression, and Ezh2K20R/K20R mutant bone marrows expand hematopoietic stem cells and downstream hematopoietic populations. Our studies reveal that EZH2 is regulated by methylation-dependent proteolysis, which is negatively controlled by AKT-mediated S21 phosphorylation to establish a methylation-phosphorylation switch to regulate the PRC2 activity and hematopoiesis.