A Global Investigation of the Bacillus subtilis Iron-Sparing ResponseIdentifies Major Changes in Metabolism

Gregory T. Smaldone,a Olga Revelles,b Ahmed Gaballa,a Uwe Sauer,b Haike Antelmann,c and John D. Helmanna

Department of Microbiology, Cornell University, Ithaca, New York, USAa; Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerlandb; and Institute forMicrobiology, Ernst-Moritz-Arndt University of Greifswald, Greifswald, Germanyc

The Bacillus subtilis ferric uptake regulator (Fur) protein is the major sensor of cellular iron status. When iron is limitingfor growth, derepression of the Fur regulon increases the cellular capacity for iron uptake and mobilizes an iron-sparingresponse mediated in large part by a small noncoding RNA named FsrA. FsrA functions, in collaboration with three smallbasic proteins (FbpABC), to repress many “low-priority” iron-containing enzymes. We have used transcriptome analysesto gain insights into the scope of the iron-sparing response and to define subsets of genes dependent for their repression onFsrA, FbpAB, and/or FbpC. Enzymes of the tricarboxylic acid (TCA) cycle, including aconitase and succinate dehydroge-nase (SDH), are major targets of FsrA-mediated repression, and as a consequence, flux through this pathway is signifi-cantly decreased in a fur mutant. FsrA also represses the DctP dicarboxylate permease and the iron-sulfur-containing en-zyme glutamate synthase (GltAB), which serves as a central link between carbon and nitrogen metabolism. Allele-specificsuppression analysis was used to document a direct RNA-RNA interaction between the FsrA small RNA (sRNA) and thegltAB leader region. We further demonstrated that distinct regions of FsrA are required for the translational repression ofthe GltAB and SDH enzyme complexes.

The tricarboxylic acid (TCA) cycle is a central pathway of Bacil-lus subtilis metabolism. The flux of carbon through the TCA

cycle generates ATP through substrate-level phosphorylation andby the generation of reducing equivalents that feed the electrontransport chain. TCA cycle intermediates also serve as biosyn-thetic precursors for numerous amino acids, heme, and other keymetabolites (4, 9, 18, 21, 43). Of particular note, �-ketoglutarate istransaminated by glutamate synthase using glutamine as a donorto generate two glutamate molecules. Thus, glutamate synthaseserves as a direct link between central carbon metabolism andnitrogen metabolism. Citric acid, another key intermediate in theTCA cycle, can also play a role in metal ion homeostasis by facili-tating the uptake of cations, including Fe(III), Mg(II), and Mn(II)(25, 30).

Since the TCA cycle is central to many biosynthetic and meta-bolic processes, several regulators exact tight control over the ex-pression of TCA cycle enzymes, including both global (CcpA,CodY, and TnrA) and pathway-specific (CcpC, RocR, and GltC)regulators (39). To this list, we can now add the ferric uptakeregulator (Fur). Fur has dual roles in iron homeostasis. Underiron-limiting growth conditions, derepression of numerous Fur-regulated operons (2) allows expression of siderophore biosynthe-sis and uptake pathways (30). Many other genes are downregu-lated in the fur mutant (2), including several with roles in centralmetabolism. Many of the genes downregulated in the fur mutantmay be the targets of a Fur-regulated sRNA A (FsrA) and threesmall, Fur-regulated basic proteins (FbpABC) that can act as co-regulators with FsrA. These effectors repress the translation oftarget genes and thereby contribute to an iron-sparing response(15). This response enables the cell to prioritize iron usage byreducing the synthesis of low-priority, iron-containing proteins,which thereby spares iron for more essential functions. The B.subtilis iron-sparing response was defined by proteomics and wasobserved to include at least two enzymes involved in the TCAcycle, aconitase and succinate dehydrogenase (15). Conceptually,

the FsrA-mediated iron-sparing response appears to be function-ally analogous to that mediated by the RyhB small, noncodingRNA (sRNA) of Escherichia coli (28).

Metabolomics studies have also implicated a role for Fur inregulation of the TCA cycle. Fischer and Sauer observed that a nullmutation of fur produced one of the greatest growth defectsamong the 137 strains tested, and this was correlated with a sig-nificantly (23%) reduced flux through the TCA cycle and a 3-foldreduction in citrate synthase activity (14). These dramatic effectscontrasted with the minimal changes noted in the vast majority ofstrains, consistent with the notion that B. subtilis has a very robustmetabolism: there are sufficient opportunities for metabolic re-routing that most mutations tested did not lead to measurablegrowth effects. Although these previous results indicated that thefur mutation had significant effects on TCA cycle activity, the reg-ulatory pathways that led to these effects were not defined.

Here we extend our characterization of the FsrA-mediatediron-sparing response using transcriptomic, fluxomic, and molec-ular genetic analyses. Our results suggest that iron limitation leadsto a physiologically significant repression of the TCA cycle. Inaddition, the FsrA sRNA mediates repression of glutamate syn-thase (which serves as the key link between central carbon andnitrogen metabolism) and a dicarboxylate transporter (DctP) thatis important for growth on TCA cycle intermediates. Our resultssupport a model in which the FsrA small RNA, in conjunction

Received 10 August 2011 Accepted 17 February 2012

Published ahead of print 2 March 2012

Address correspondence to John D. Helmann, jdh9@cornell.edu.

Supplemental material for this article may be found at http://jb.asm.org/.

Copyright © 2012, American Society for Microbiology. All Rights Reserved.

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with the FbpABC coregulators, remodels central metabolism as astrategy to prioritize the usage of iron.

MATERIALS AND METHODSBacterial strains, media, and growth conditions. Bacterial strains used inthis study are listed in Table 1. Escherichia coli DH5� was used for routineDNA cloning (35). B. subtilis CU1065 mutant strains were constructed byusing long-flanking homology PCR (6). Erythromycin (1 �g/ml) and lin-comycin (25 �g/ml) (for macrolide-lincosamide-streptomycin B [MLS]resistance), spectinomycin (100 �g/ml), kanamycin (10 �g/ml), andchloramphenicol (5 �g/ml) were used for the selection of various B. sub-tilis strains unless otherwise indicated. Liquid media were inoculated froman overnight preculture and incubated at 37°C with shaking at 225 rpm.Growth media used in this study include LB medium, modified compe-tence medium (MC), minimal growth medium (morpholinepropanesul-fonic acid [MOPS]-based with a glucose carbon source [MM] [8]), fuma-rate minimal growth medium (MOPS based with a 2% fumarate carbonsource [fumarate MM]), succinate minimal growth medium (MOPS-based with 2% succinate as a carbon source [succinate MM]) (5), Belitskyminimal medium (40), and M9 minimal growth medium (19, 24).

Growth curves were done using a Bioscreen C MBR system for 24 h andrecording the optical density at 600 nm (OD600) every 15 min.

For 13C-labeling experiments, cultures were grown in 250-ml baffledshake flasks containing 20 ml citrate-amended M9, supplemented eitherwith 100% (wt/wt) [1-13C]glucose (99%; Cambridge Isotope Laborato-ries) or with a mixture of 20% (wt/wt) [U-13C]glucose (99%; CambridgeIsotope Laboratories) and 80% (wt/wt) natural-abundance glucose. Ci-trate (3.4 mM) is required in these studies to increase iron availability andthereby decrease the expression of the Fur regulon in wild-type cells (datanot shown).

DNA manipulations. Routine molecular biology procedures wereperformed as previously described (35). Isolation of B. subtilis chromo-somal DNA and transformation were carried out as previously described(10). Restriction enzymes, DNA ligase, and DNA polymerases were allused according to the manufacturer’s instructions (New England Bio-Labs). Site-directed mutagenesis was done by PCR and overlap extensionas previously described (20). Primers used in the construction of strainsare included in Table 1 and Table S1 in the supplemental material.

For FsrA complementation, fsrA was PCR amplified to include itsnative promoter and terminator stem-loop and inserted between the

TABLE 1 Strains and primers used in this study

Strain or plasmid Relevant characteristic(s) Source or reference

B. subtilisCU1065 W168 att SP� trpC2 (WT) 42HB2501 CU1065 fur::kan 2HB5733 CU1065 fur::kan fsrA::cat 15HB5735 CU1065 fur::kan fbpAB::tet 15HB5737 CU1065 fur::kan fbpC::MLS 15HB5750 CU1065 fur::kan fsrA::cat fbpC::MLS 15HB5751 CU1065 fur::kan fsrA::cat fbpAB::tet 15HB5752 CU1065 fur::kan fsrA::cat fbpAB::tet fbpC::MLS 15HB8264 CU1065 fur::kan fbpAB::tet fbpC::MLS 15HB12551 CU1065 amyE::dctP-FLAG (pPL82) This studyHB12558 CU1065 fur::kan amyE::dctP-FLAG (pPL82) This studyHB12562 CU1065 dctP::pMUTIN-FLAG This studyHB12563 CU1065 fur::kan dctP::pMUTIN-FLAG This studyHB12564 CU1065 fur::kan fsrA::cat dctP::pMUTIN-FLAG This studyHB12573 CU1065 fur::kan fsrA::cat amyE::fsrA This studyHB11008 CU1065 fur::kan PgltA1::pMUTIN4 This studyHB11009 CU1065 fur::kan PgltA2::pMUTIN4 This studyHB11010 CU1065 fur::kan PgltA3::pMUTIN4 This studyHB11018 HB11008 fsrA::cat thrC::fsrA spc complementation of gltA1 This studyHB11019 HB11009 fsrA::cat thrC::fsrA spc complementation of gltA2 This studyHB11020 HB11010 fsrA::cat thrC::fsrA spc complementation of gltA3 This study

E. coliDH5� �80 �(lacZ)M15 �(argF–lac)U169 endA1 recA1 hsdR17(rK

� mK�) deoR thi-1

supE44 gyrA96 relA135

PlasmidspDG1730 Integration vector for amyE locus BGSCpMUTIN-FLAG Integration vector at locus generating a C-terminal flag tagged ORF BGSCpPL82 IPTG-inducible [Pspac(hy)] integration vector for amyE locus 33

PrimersdctPpPL82FWD GCGCTCTAGAAGGAGGAGGATATGAAACTGTTTAAAAA XbaI site addeddctPpPL82REV GCGCATCGATTTATTATTTATCATCATCATCTTTATAATCGACTGCTG

TTTTCATTTTClaI and FLAG sequence

addeddctP_pMUTIN-FLAG_FWD GCGCGGTACCTTCGCTTCATTAAGGATGAG KpnI site addeddctP_pMUTIN-FLAG_REV GCGCATCGATGACTGCTGTTTTCATTTTTTTC ClaI site addedfsrA_pDG1730_FWD GCGCGAATTCTGATGAAGAAGGCGATCAG EcoRI site addedfsrA_pDG1730_REV GCGCGGATCCGTTCGGCACTCAATGTTTC BamHI site added

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EcoRI and BamHI sites of pDG1730 (17). The construct was then inte-grated ectopically at the amyE locus.

Due to the large size of the gltAB region, the gltAB promoter regioncontaining all regulatory elements, and 175 bp downstream of the startcodon was cloned into pMUTIN4 (41) and integrated into the gltAB locususing Campbell integration. The gltAB promoter region was isolated fromthe genome of the mutants by PCR, and the correct clones were identifiedby DNA sequencing.

The inducible dctP-FLAG construct was generated by PCR amplifica-tion of the dctP gene, including the ribosome binding site (RBS) and startcodon in the forward primer and by addition of the FLAG epitope tagsequence on the reverse primer. This amplified product was cloned be-tween the XbaI and ClaI sites of the pPL82 expression vector and inte-grated into the amyE locus (33). The pMUTIN-FLAG dctP construct wasgenerated by PCR amplification of the dctP open reading frame excludingthe start and stop codons and remaining in frame at the 3= end. Additionof KpnI and ClaI sites to the forward and reverse primers, respectively,allowed for the integration of the amplified product into the multicloningsite of the pMUTIN-FLAG vector. This generated a C-terminal FLAGepitope-tagged dctP gene when integrated into the B. subtilis genome at itsnative locus. The sequences for all mutant constructs were verified byDNA sequencing (Cornell Life Sciences Core Laboratories Center).

RNA isolation and microarray analysis. Strains CU1065 (wild type[WT]), HB2501 (fur), HB5733 (fur fsrA), HB5735 (fur fbpAB), HB5737(fur fbpC), and HB8264 (fur fbpABC) were inoculated into LB and grownat 37°C with vigorous shaking until an OD600 of �0.4 (Spectronic 21) wasreached, and RNA isolation was performed using the RNeasy minikit(Qiagen). RNA was DNase treated with Turbo DNA-free (Ambion) andprecipitated overnight. The RNA was dissolved in RNase-free water andquantified using a NanoDrop spectrophotometer (Nanodrop Tech. Inc.,Wilmington, DE). RNA was isolated from three biological replicates.

cDNA synthesis was performed using the SuperScript Plus indirectcDNA labeling system (Invitrogen) as per the manufacturer’s instructionswith 20 �g of total RNA and then purified using the Qiagen MiniElute kit(Qiagen, MD) and quantified with NanoDrop. Total cDNA was labeledovernight with Alexa Fluor 555 or Alexa Fluor 647 (Invitrogen), purifiedusing the Qiagen MiniElute kit, and quantified with NanoDrop. Equalamounts (100 to 150 pmol) of labeled cDNA (fur and WT, fur and furfsrA, fur and fur fbpAB, fur and fur fbpC, and fur and fur fbpABC) werecombined to a final volume of 15 �l, and 1 �l salmon sperm DNA (10mg/ml; Invitrogen) plus 16 �l 2 hybridization buffer (50% formamide,10 SSC [1 SSC is 0.15 M NaCl plus 0.015 M sodium citrate], and 0.1%sodium dodecyl sulfate [SDS]) were added. The cDNA mix was denaturedat 95°C and hybridized for 16 to 18 h at 42°C to DNA microarray slideswhich had been prehybridized for at least 30 min at 42°C in 1% bovineserum albumin, 5 SSC, and 0.1% SDS, washed in water, and dried.Following hybridization, the slides were washed sequentially in 2 SSCplus 0.1% SDS for 5 min at 42°C, 2 SSC plus 0.1% SDS for 5 min at roomtemperature, 2 SSC for 5 min at room temperature, and 0.2 SSC for 5min at room temperature and finally dipped in water and spun until dry.Arrays were scanned using a GenePix 4000B array scanner (Axon Instru-ments, Inc.). Our arrays are based on a B. subtilis oligonucleotide librarymanufactured by Sigma-Genosys consisting of 4,128 oligonucleotides(65-mers) representing 4,106 B. subtilis genes, 10 control oligonucleotides(from E. coli and Brome mosaic virus), and 12 random oligonucleotides. Asingle oligonucleotide was designed to represent each of the B. subtilisgenes as annotated in the genome data, release R16.1 (26 April 2001), atthe SubtiList website (http://genolist.pasteur.fr/SubtiList/) (29). The ar-rays were printed onto poly-L-lysine-coated Corning CMT-Gap slides atthe W.M. Keck Foundation Biotechnology Resource Laboratory, YaleUniversity. Each array contains 8,447 features corresponding to dupli-cates of each open reading frame-specific oligonucleotide, additional oli-gonucleotides of control genes, and 50% dimethyl sulfoxide blank con-trols.

Raw data files were produced from the scanned images using the

GenePix Pro 4.0 software package (GPR files), and the red/green fluores-cence intensity values were normalized such that the ratio of medians of allfeatures was equal to 1. The normalized data were exported to Excel foranalysis. The data sets were filtered to remove those genes that were notexpressed at levels significantly above background under either condition(sum of mean fluorescence intensity, 100). Mean signal intensities weredetermined for triplicate microarray experiments with two spots per slide(6 values). We filtered out those genes where the standard deviation of thesignal intensity was greater than the mean value.

Hierarchical clustering analysis. Hierarchical clustering was per-formed using the software program Cluster 3.0 (11) from transcriptomedata sets derived from this work. After hierarchical clustering, the outputwas visualized using the TreeView program (12). Studies were carried outusing those genes that were at least 1.25-fold repressed in the fur mutant(relative to the WT) and also at least 2-fold induced in any one of the fourstrains altered in components of the iron-sparing response. Genes consid-ered in the analysis must have an unfiltered fold change calculation forthree of the four microarray experiments. Genes where expression levelshave been previously observed to be strongly affected by the growth rate(encoding ribosomal proteins, rRNA, and purine and pyrimidine synthe-sis enzymes) were excluded from the analysis.

Bioinformatic analysis of FsrA pairing with putative targets. Pre-dicted targets of the iron-sparing response from reference 15 or from thetranscriptome analysis described in this study were selected for pairinganalysis. Secondary structure models were predicted by joining a regionencompassing the translation initiation region (TIR) (from ��60 to �10nucleotides [nt] from the start of translation) of each mRNA to the FsrAsequence via a short linker (10 CA repeats). Secondary structures pre-dicted using the mFold software program (50) were examined for ex-tended pairing between the TIR and FsrA. If pairing was observed, theinteraction was extended and refined using the program RNAhybrid (34).

Northern blot experiments. B. subtilis wild-type strain CU1065 andfur, fur fsrA, and fur fbpABC cells were grown in Belitsky minimal medium(40), and samples were harvested for RNA isolation at OD500s of 0.4, 1.0,and 2.0, corresponding to the exponential growth phase, transition phase,and stationary phase, respectively. RNA isolation and Northern blot anal-yses were performed as described previously (44). Hybridizations specificfor sdhA, citB, and lutB were performed with the digoxigenin-labeled RNAprobes synthesized in vitro using T7 RNA polymerase from the T7promoter containing internal PCR products of the respective genes usingthe following primer pairs: CATCAAACCCATACGTGCTG (citB-for),CTAATACGACTCACTATAGGGAGATACGTCGTAAATCCGCCTTC(citB-T7-rev), CGGGAATCATCTTTGGAAAA (sdhA-for), CTAATACGACTCACTATAGGGAGAAGCGCTCCATTAACTCCTGA (sdhA-T7-rev),GAAGGAAGGCTGTGAAGTCG (lutB-for), and CTAATACGACTCACTATAGGGAGACCAAGTCCGAATGCTTTCAT (lutB-T7-rev).

Analytical techniques and sample preparation. Maximum specificgrowth rate, biomass yield on glucose, specific glucose consumption, andby-product formation rates were determined by regression analysis dur-ing the exponential growth phase in batch cultures. Glucose and acetateconcentrations were determined from culture supernatants along thegrowth curve on an HPLC HP1100 system (Agilent Technologies, SantaClara, CA). Detection was performed using a refractive index for glucoseand a UV detector at 240 nm for acetate. Cellular dry weights were calcu-lated from the OD600 values multiplied by a conversion factor that waspreviously determined.

Metabolic flux analysis. To assess 13C patterns in proteinogenicamino acids, cell pellets from 5 ml of culture aliquots were harvestedduring growth at an OD600 of 1, hydrolyzed in 6 M HCl, and derivatizedwith N-(ter-butyldimethylsilyl)-methyltrifluoroacetamide as describedelsewhere (48). Derivatized amino acids were analyzed for 13C-labelingpatterns with a series 8000 gas-chromatograph (GC) combined with anMD800 mass spectrometer (MS) (Fisons Instruments). The GC-MS-de-rived mass isotope distributions of proteinogenic amino acids were thencorrected for naturally occurring isotopes. Flux ratio analysis and subse-

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quent 13C-constrained net flux analysis were conducted by using the soft-ware package FiatFlux (48, 49). Ratios of converging fluxes were directlycalculated from 13C patterns and then used together with measured phys-iological rates as constraints to estimate the flux distribution from thestoichiometric matrix. Fluxes into biomass were calculated from theknown metabolite requirements for macromolecular compounds andthe growth rate-dependent RNA and protein contents (13). Using theFiatFlux software program (49), the sum of the weighted square residualsof the constraints from both metabolite balances and flux ratios was min-imized using the MATLAB function, and the residuals were weighted bydividing through the experimental error (48). The computation was re-peated at least five times with randomly chosen initial flux distributions toensure identification of the global minimum. Two independent experi-ments have been analyzed.

Growth curve generation and comparison. Fresh single colonies werepicked from selective LB plates and cultivated statically at 30°C overnightin 5 ml MM. They were then shifted to 37°C with shaking and grown tomid-exponential phase (OD600 of �0.4; Spectronic 21). Cells were recov-ered from 1 ml of each culture, washed in 0.75 ml 0.88% NaCl, and thenresuspended and diluted to a standard OD600 of 0.1 (Perkin Elmer) in0.88% NaCl. Thirty microliters of cells were inoculated into 170 �l ofeither fumarate MM or succinate MM in a 100-well microtiter plate, andgrowth was monitored with shaking at 37°C using a BioScreen C platereader.

Western blot analysis. Strains for Western blot analysis were grownovernight in 1 ml LB broth plus MLS (when appropriate) at 37°C shaking.A 0.5-ml overnight culture was inoculated into 50 ml LB broth, grown toan OD600 of �0.4, and spun down at 5,000 rpm for 5 min in an Eppendorf5804R swinging bucket rotor centrifuge. The pellet was resuspended in 1ml of MM supplemented with 0.2 mM KPO4 (pH 7.0), 40 mM MnCl2,and 1 mM FeSO4 (MMa) and centrifuged for 2 min at 5,900 g. Thepellet was then resuspended in 1 ml of MMb (1 Bacillus salts [5], 40 mMMOPS [pH 7.4], and 2% [wt/vol] glucose) and centrifuged for 2 min at5,900 g. The pellet was then resuspended in 1 ml of MMa with theaddition of 20% sucrose and 1 mg/ml lysozyme and incubated with shak-ing at 37°C for 40 min. Formation of protoplasts was verified by micros-copy, and the protoplasts were centrifuged for 4 min at 4,600 g at 4°C.The protoplasts were resuspended in 200 �l TBS (50 mM Tris-HCl [pH7.4], 150 mM NaCl, 1 mM EDTA, 1 mM dithiothreitol [DTT], and 0.1mM phenylmethylsulfonyl fluoride [PMSF]), briefly sonicated, and thenultracentrifuged at 45,000 rpm for 30 min (TLA 100.3 fixed-angle rotorfor a Beckman TL-100 ultracentrifuge) to separate the membrane andcytoplasmic fractions. The membrane fraction was resuspended in 200 �lTBS. A Bradford assay was carried out with the membrane fraction todetermine total recovered protein, and 10 �g of total protein was used forSDS-PAGE. Protein levels were determined after membrane transfer andWestern blot analysis using commercially obtained anti-FLAG primaryantibodies (Sigma).

Microarray data accession number. All original raw data files weredeposited into the GEO database as series GSE27416.

RESULTS AND DISCUSSIONScope of FsrA-dependent iron-sparing response as monitoredat the transcriptome level. Under conditions of iron sufficiency,the fsrA, fbpAB, and fbpC operons are repressed and their productsare inactive. We therefore used a fur mutant strain, in which thesegenes are constitutively expressed (2), as the starting point for ouranalysis. This strain is said to express an iron-sparing response inwhich multiple iron-dependent proteins are repressed (15). Inmost cases tested previously, this translational repression was ac-companied by a decrease in steady-state mRNA levels (15). Wetherefore focused out attention on those genes with reducedmRNA levels in the fur mutant as visualized by transcriptomics(Fig. 1, fur/wt). Since the level of decrease in steady-state mRNA

levels is often quite small, we selected all genes with mRNA levelsreduced by at least 1.25-fold in a fur mutant (corresponding to lessthan 3% of coding regions). The resulting set of genes includedmost of those previously identified as targets of the iron-sparingresponse (15).

To determine whether this observed downregulation involvedany of the fsrA, fbpAB, or fbpC operons, we compared the tran-scriptome of a fur mutant with strains additionally inactivated forone or more components of the iron-sparing response. Of the 116genes with at least a 1.25-fold reduction in mRNA levels, 78 dis-played an increase in mRNA in a strain additionally lacking one ormore of the effectors of the iron-sparing response. Cluster analysisof those genes that were at least 2.0-fold upregulated (relative tolevels for the fur mutant) in any one of four genetic backgroundstested allowed us to define clusters of coordinately regulatedgenes. These gene sets define mRNA targets whose levels are af-fected primarily by the Fur-regulated FsrA small RNA (cluster R),FbpAB (cluster AB), or FbpC (cluster C). For other genes, thegreatest increases in mRNA levels were observed in response tomutations in either FsrA or one or more of the presumed coregu-lators. These clusters include FsrA/FbpAB-coregulated genes(cluster RAB) and FsrA/FbpC-coregulated genes (cluster RC)(Fig. 1).

In general, FsrA is postulated to function as an antisense RNAto preclude translation of those target genes where it has signifi-cant complementarity in the translation initiation region (TIR).The roles of the FbpA, -B, and -C proteins are less clear. Some orall may work as RNA chaperones to increase the efficacy of FsrAaction, they may work in conjunction with other yet-to-be-iden-tified sRNAs, or they may work as part of protein-based transla-tional repression or RNA destabilization pathways.

Consistent with our previous findings for the sdh operon (15),mutation of fsrA leads to significant upregulation, and the effectsof FsrA on expression are largely independent of FbpABC (clusterR). The leuC gene and pdh operon also belong to cluster R.SdhCBA and PdhABCD both play a role in carbon metabolism,and their activities are expected to be correlated with the activity ofthe TCA cycle. We note that leuC is the penultimate gene of theilv-leu operon, and the LeuC protein was previously found to bestrongly repressed in an FsrA-dependent manner by proteomicsstudies (15). This operon is also subject to complex RNA process-ing of the primary transcript (27). Some genes of the ilv-leuoperon had low RNA levels under the growth conditions used forthe transcriptome analysis and were removed during data filtering.

Most of the other genes upregulated in the fur fsrA mutant(compared to fur alone) appeared to also be (variably) upregu-lated in the fur fbpAB and/or fur fbpC mutants (including clustersRAB and RC, as well as some genes in clusters AB and C). This maymean that the effect of FsrA on these targets is stimulated by orrequires one or more of these basic proteins as coregulators. Formost operons that appear to be repressed in the fur mutant strainin a process involving FsrA and/or FbpABC, neither the mecha-nism nor the physiological relevance of the noted regulation is yetestablished. We have shown previously that the FsrA sRNA iscomplementary to, and anneals with, the leader region of the sdhoperon (15). We further show, in the accompanying article, thattranslational repression of the lutABC operon by FsrA requiresFbpB in cells with wild-type levels of FsrA but not when FsrA isoverexpressed by 2- to 3-fold (38). These results are consistent

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FIG 1 Hierarchical cluster analysis of transcriptional changes in iron-sparing response mutant strains. A hierarchical cluster analysis (generated using Treeview)represents genes that are at least 1.25-fold repressed in the fur-versus-WT microarray experiment and induced at least 2.0-fold under at least one of the followingconditions: fur versus fur fsrA, fur versus fur fbpAB, fur versus fur fbpC, or fur versus fur fbpABC. Clusters with similar regulatory patterns are indicated by bracketsand represent genes mostly affected by FsrA (R), FbpC (C), FsrA and FbpAB (RAB), and FsrA and FbpABC (RABC). Red intensity indicates increasing expression,while green intensity indicates decreased expression. Black indicates no change or no data for the gene/array indicated. Genes are listed to the right of the cluster,and the corresponding regulators (where known) are indicated to the right of each gene.

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with a role for FbpB in augmenting the action of FsrA, at least forthis one target.

The transcriptome analysis reveals a significant number of ad-ditional genes where the mRNA level is affected primarily byFbpAB (cluster AB), FbpC (cluster C), or all three coregulators ina manner largely independent of FsrA. For example, cluster Cincludes the eps operon, encoding functions for extracellular poly-saccharide biosynthesis, and the qcrABC operon, responsible forthe production of the Fe-S-containing quinone-cytochrome c re-ductase. For cluster C genes, the effects of FbpC are greater thanthose of FsrA, which is inconsistent with FbpC acting throughFsrA and suggests that FbpC (either as a transcript or as the pep-tide product) has additional, FsrA-independent regulatory activ-ity. Similarly, the lutABC operon is in the AB cluster, which re-flects the fact that the levels of the corresponding RNA are affectedmost strongly by FbpB, as described in the accompanying article(38). In general, there is an imperfect correlation between changesnoted at the RNA level (e.g., Fig. 1) and at the protein level (15).This may indicate that translational repression by annealing ofFsrA to its mRNA targets has variable effects on mRNA stability.Presumably, the subset of mRNAs where FsrA (or other effectorsof the iron-sparing response) leads to destabilization are mosteasily detected at the transcriptome level. The mechanisms of cou-pling between sRNA and subsequent effects on RNA degradationare not yet well defined for B. subtilis (1). For E. coli, however,annealing of the sRNAs to target transcripts leads to an Hfq-de-pendent recruitment of an RNA degradosome that cleaves themRNA at sites distal to the RNA pairing interaction (22, 32).

As expected, many of the mRNAs that are present at a lowerlevel in response to FsrA, FbpAB, and/or FbpC encode known orlikely metalloproteins. Examples include the metalloprotein Map(methionine aminopeptidase) and the iron-containing enzymeCydAB (a 3-heme-containing cytochrome bd) (23). It has beenhypothesized that Map and its paralog, YflG, both function asmethionine aminopeptidases, each requiring a different metal co-factor (46). The regulation of map as part of the iron-sparingresponse, as well as studies demonstrating activity for Fe(II)-met-allated Map orthologs (45, 47), suggests that the Map cofactormay be iron. In general, many of the proteins targeted by the

iron-sparing response encode relatively abundant, iron-contain-ing enzymes, as also noted based on our previous proteome anal-yses (15).

To confirm the results observed in the transcriptome studies,we performed Northern blot analysis of three operons (Fig. 2). Weincluded the sdhCAB operon, since the corresponding leader re-gion was shown previously to anneal with FsrA (15). We alsomonitored the aconitase (citB) mRNA, since previous results sug-gested that this gene was a target for the iron-sparing response(15), but this was not apparent in the DNA microarray-basedanalysis (this gene signal was not reliably detected with these mi-croarrays). Third, we included the lutABC transcript, which is alsoa target of FsrA-mediated regulation, as shown by monitoring, atthe RNA and protein level, a lutA-FLAG fusion allele (38). In eachcase tested, the level of mRNA was reduced significantly in the furmutant strain, and this reduction was in each case dependent onFsrA: mRNA levels returned to near-wild-type levels in the fur fsrAdouble mutant. The lutABC operon also returned to near-wild-type levels in a strain containing FsrA but lacking the FbpA, -B,and -C proteins. A lesser dependence on the Fbp proteins was alsonoted for the sdhCAB transcript. These results again highlight thecombinatorial complexity originally noted in our proteome data(15).

Bioinfomatic analysis supports a direct role for FsrA at manytargets. We anticipated that some of the effects noted at the tran-scriptional level were likely due to the direct action of FsrA as anantisense RNA, with other effects being secondary in nature. Inmost bacterial systems, small trans-acting RNAs function by an-nealing at or near the TIR (26). Subsequent to hybrid formation,the duplex RNA can be targeted for degradation, which can ac-count for the observed reduction in steady-state mRNA levels(26). Moreover, mRNAs that are not actively translated often havea shorter half-life than those that are being translated (7).

In an initial attempt to understand the mechanism behind theregulation by fsrA, we sought to determine if FsrA was comple-mentary to the TIR of various mRNA targets. Using both mFoldand RNAhybrid, pairings were predicted that could account forthe translational repression of several targets (Fig. 3). It is inter-esting to note that all of the pairings presented here involve a

FIG 2 Northern analysis of selected FsrA regulon members. Equal amounts of total RNA isolated from wild-type and fur, fur fsrA, and fur fbpABC mutant strainswere hybridized with antisense RNA probes specific for sdhA, citB, and lutC, as indicated. Cells were grown in Belitsky minimal medium and harvested at OD500sof 0.4, 1.0, and 2.0, corresponding to the log phase (lane 1), transition phase (lane 2), and stationary phase (lane 3). The arrows point to the expected sizes of thespecific transcripts.

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FIG 3 Predicted RNA pairings for FsrA and selected FsrA regulon members. (A) Secondary structure of FsrA, including the terminator hairpin (T). A regionincluding the second of two tetracytidine repeats is underlined. (B) Predicted RNA-RNA hybrids between FsrA (3= to 5=; with the CCCCUCU sequence in boldand underlined for indexing) and the TIR of the indicated target mRNA (5= to 3=).

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C-rich unstructured loop region of FsrA (15) and regions overlap-ping the RBS of the target operon. This suggests that FsrA maynucleate interaction with its targets via this open loop structure.Similar C-rich motifs have been found in S. aureus sRNAs and arepredicted to act in a similar manner (16).

FsrA regulates the expression of glutamate synthase by RNA-RNA hybrid formation. To test the pairing predictions, we fo-cused on the gltAB operon leader region. The levels of the gltABmRNA were found previously to be reduced �2- to 3-fold in a furmutant or in response to iron deprivation (2).

To determine if glutamate synthase (GltAB) is regulated as partof the iron-sparing response, we first monitored the abilities of thewild type and the fur, fur fsrA, fur fbpAB, fur fbpC, and fur fbpABfbpC mutants to grow in the presence of different nitrogensources. Consistent with a deficiency of GltAB activity, the furmutant was unable to grow in glucose minimal medium with am-monium as the sole nitrogen source (Fig. 4A). Growth was re-stored by addition of glutamate, glutamine, or Casamino Acidsbut not by �-ketoglutarate (data not shown), as shown previouslyfor a gltAB mutant (3). The growth defect of the fur mutant withammonium as a nitrogen source was suppressed by an fsrA muta-tion (Fig. 4A) but not by the mutation of fbpAB, fbpC, or fbpABC(data not shown).

RNA pairing analysis identified several regions of complemen-tarity between FsrA and the gltAB leader region. We targeted threeof these regions for analysis (Fig. 3B), while avoiding the regionscomprising the gltAB ribosome-binding site and its complementin FsrA. For two of the leader region mutations (gltA2 and gltA3),the mutations appeared to reduce or prevent FsrA-mediated re-pression and the cells grew on ammonium as a nitrogen source. Aspredicted by the RNA-RNA pairing model, introduction of com-pensatory mutations into FsrA restored the repression of gltAB, asevidenced by a failure to grow on ammonium (Fig. 4B and C). Incontrast, mutation gltA1 in the gltAB leader appeared to reduceGltAB function (as reflected in the decreased growth rate on am-monium), but this growth defect was independent of FsrA, andrestoring the complementarity by mutation of FsrA did not have adramatic effect on growth, at least in the early stages. Downregu-lation of glutamate synthase in response to iron deprivation hasbeen previously found in the yeast Saccharomyces cerevisiae (37),likely as part of the iron-sparing response orchestrated by the RNAbinding Cth1 and Cth2 proteins (31).

Different regions of FsrA regulate the sdhCAB and gltABoperons. Expression of both sdhCAB and gltAB is repressed byFsrA (15; this work). RNA hybrid predictions (Fig. 3) suggest thatlargely distinct regions of FsrA interact with the sdhC (15) andgltAB leader sequences. The RNA hybrid analysis predicts that theFsrA mutations that suppress gltA2 should not affect the ability ofFsrA to repress the sdhCAB operon. We therefore monitored theabilities of wild-type and mutant FsrA alleles to prevent growth onsuccinate as a carbon source. As expected, the wild type grew nor-mally on succinate (OD600 � 2.6 � 0.16), whereas the fur mutantwas unable to grow (OD600 � 0.2 � 0.1). The fur fsrA mutant grewas well as the wild type. An inability to grow on succinate wasrestored by provision of either wild-type fsrA or a mutated copy(complementary to gltA2). We conclude that distinct regions ofFsrA interact with the sdhCAB and gltAB leader regions.

FsrA decreases flux through the TCA cycle. The repression ofthe Sdh complex by FsrA, together with the downregulation notedfor aconitase (CitB) (Fig. 2) and pyruvate dehydrogenase (Pdh),

suggests that the iron-sparing response may significantly perturbcarbon metabolism and specifically the TCA cycle. This is consis-tent with prior results demonstrating that a fur mutant strain hasreduced flux through the TCA cycle (14).

We performed a 13C-based flux analysis (36) to determine ifthe reduced TCA cycle activity is due to FsrA and/or FbpABC. Forthis purpose, 13C-labeling experiments with exponentially grow-ing cultures were carried out in medium containing 80% naturalabundance glucose and 20% [U-13C]glucose and, in another se-ries, with 100% [1-13C]glucose. From each culture, proteins were

FIG 4 FsrA interacts directly with the gltAB leader region. Growth of theindicated strains was monitored in MM with ammonia as a sole nitrogensource. Cells were inoculated from overnight cultures into MM without glu-tamate, and the OD600s were recorded using the Bioscreen C MBR system for24 h. The wild type and the fur and fur fsrA mutants are shown in all panels. Thefur fsrA mutant was complemented with a WT copy at the thrC locus as shownin panel A. Mutants in the gltAB leader region (designated 1, 2, and 3, as in Fig.3) and the corresponding compensatory changes in FsrA (to restore the pre-dicted pairing) are shown in panels A, B, and C, respectively.

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isolated and the 13C distribution in proteinogenic amino acids wasdetermined by mass spectrometry as described previously (48).Fluxes from two independent experiments were obtained by 13C-constrained flux analysis using the software program FiatFlux(49). This analysis relies on the fact that the precise pattern oflabeling in amino acids reports on the relative activities of variousmetabolic pathways, which, in turn, can be fit to a flux modelbased on the known metabolic pathways for a given organism. Thecomplete net flux distribution for the wild-type strain and its iso-genic mutants is given in Fig. S1 in the supplemental material, andselected fluxes are shown in Fig. 5.

The most apparent perturbations in the flux analysis are due tothe fur mutation (relative to the WT) and are best observed inglycolysis and the TCA cycle (Fig. 5; see also Fig. S1 in the supple-mental material). The fur fsrA mutant but not the fur fbpAB or furfbpC mutant generally reverts the fur flux phenotype to wild-typelevels, and this is most notable for the TCA cycle-related fluxes(Fig. 5). Even the fbpABC triple mutation was less effective thanthe fsrA single mutation in restoring the fluxes of the fur mutant totheir wild-type pattern. In contrast, fluxes through the pentosephosphate pathway remained at a relatively constant level (see Fig.

S1 in the supplemental material). These results suggest that FsrA isthe major regulator of flux through the TCA cycle during condi-tions of iron deprivation.

Consistent with previous data (14) and with the altered fluxesthrough the TCA cycle, the fur mutation roughly halves thegrowth rate on glucose as the sole carbon source (Table 2). Mu-tating fsrA in the fur mutant background partially restores thegrowth phenotype, but a full restoration of rapid growth isachieved only for those fur fsrA mutants that are additionally lack-ing either FbpAB, FbpC, or all three (Table 2). These results pro-vide evidence that FbpAB and FbpC have physiological functionsindependent of FsrA. This further indicates that optimal growthrequires the restoration of expression of both TCA cycle enzymes(repressed by FsrA) and other pathways (repressed by FbpABC-mediated pathways).

Role of DctP in C4-dicarboxylate uptake and utilization.Downregulation of Sdh can explain our previous observation thata fur mutant strain grows very poorly on minimal medium withsuccinate as the carbon source. However, we have also observedthat a fur mutant is severely impaired in growth on fumarate (15),which is the product of the Sdh reaction. A hint of a possiblemechanism is provided from earlier transcriptome studies whichindicated that a C4-dicarboxylate permease (DctP) is stronglydownregulated in a fur mutant (2). We therefore hypothesizedthat the inability to grow on succinate or fumarate might be due torepression of DctP rather than (or in addition to) Sdh.

To monitor the effects of fur and the iron-sparing response onDctP levels, Western blot analysis was used with strains expressinga DctP-FLAG protein. A marked reduction in the level of DctP-FLAG was observed in the membrane fractions of the fur mutantcompared to that for the WT (Fig. 6). Protein levels increased withthe additional mutation of fsrA (Fig. 6) but not in fbpAB or fbpCmutant strains (data not shown). This indicates that dctP (whichwas removed during filtering of our microarray data) is likely amember of Cluster R (as is the sdh operon) and is regulated pri-marily by FsrA. Consistent with this hypothesis, the inability of afur mutant to grow on succinate or fumarate can be rescued in afur fsrA double mutant strain but not by a fur fbpAB or fur fbpCdouble mutant strain (Fig. 7 and data not shown).

To directly test if regulation of DctP was responsible for thesegrowth effects, we generated an isopropyl-�-D-thiogalactopyra-noside (IPTG)-inducible dctP-FLAG construct and integrated it

TABLE 2 Physiological parameters of B. subtilis growth oncitrate-supplemented M9 mediuma

GenotypeGrowth rate(�)

Biomass yield, g(g glucose)�1

Glucoseuptake(mmolg�1 h�1)

Acetatesecretion

WT 0.64 � 0.01 0.42 � 0.09 9.7 � 2 3.8 � 0.65fur 0.36 � 0.02 0.35 � 0.05 7.0 � 1.3 3.0 � 0.5fur fsrA 0.50 � 0.007 0.36 � 0.02 7.8 � 0.5 2.0 � 0.2fur fbpC 0.44 � 0.002 0.32 � 0.02 6.1 � 0.3 3.8 � 0.8fur fbpAB 0.42 � 0.04 0.40 � 0.05 6.4 � 1.2 2.7 � 1fur fbpABC 0.41 � 0.01 0.36 � 0.01 8.4 � 2 4.3 � 1.5fur fsrA fbpC 0.61 � 0.03 0.51 � 0.04 7.4 � 1.8 3.2 � 0.8fur fsrA fbpAB 0.65 � 0.04 0.50 � 0.04 7.8 � 0.9 2.9 � 0.09fur fsrA fbpABC 0.64 � 0.03 0.43 � 0.07 8.3 � 1.6 2.5 � 0.6a Values are means � SD.

FIG 5 Absolute metabolic fluxes in B. subtilis mutants during exponentialgrowth in glucose batch culture. Selected fluxes are given for the enzymes thatcatalyze the indicated reactions: MDH, flux measured from malate to oxalo-acetate; AKG:MAL, flux measured from �-ketoglutarate to malate; and TCA,flux through the TCA cycle. Strains tested for flux analysis are described belowthe graph. One of two replicate experiments is shown. Generally, the 95%confidence intervals were between 10 and 15% of the values shown for themajor fluxes. Larger confidence intervals were estimated for reactions with lowfluxes. The complete solution for the flux analyses in two replicate experimentsis shown in the supplemental material.

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ectopically in WT and fur mutant strains. Growth of both strainswas measured after 24 h in both succinate MM and fumarate MMwith and without the addition of 1.0 mM IPTG. Induction ofdctP-FLAG led to significant restoration of growth in fumarateMM but not in succinate MM (Fig. 7C). This suggests that repres-sion of DctP is at least in part limiting for growth on fumarate.Conversely, induction of DctP is not sufficient to overcome the

growth restriction on succinate, presumably because FsrA addi-tionally represses SdhCBA translation.

Concluding remarks. Transcriptome analysis of the fur mu-tant strain compared to the wild type reveals derepression of thosegenes repressed by Fur (including many operons encoding ironuptake functions) and downregulation of numerous other oper-ons, consistent with findings of prior studies (2). The discovery ofthe iron-sparing response, mediated by FsrA and/or FbpABC,provides a mechanistic explanation for much of this downregula-tion: mRNAs that are targeted by the FsrA sRNA for translationalrepression are presumably degraded more rapidly, which therebyreduces the steady-state mRNA level.

The genes targeted by the iron-sparing response include thoseencoding aconitase (citB), glutamate synthase (gltAB), succinatedehydrogenase (sdhCAB), and C4-dicarboxylate permease (dctP),which all may affect fluxes through the TCA cycle (Fig. 8). Theresults presented here confirm that these effects, as observed intranscriptomics and noted previously in proteomics studies (15),are indeed responsible for a substantially reduced flux through theTCA cycle. The repression of TCA cycle enzymes is physiologicallysignificant: the fur mutant has a reduced growth rate and yield onglucose and is unable to grow on either succinate or fumarate as acarbon source. The inability to grow on fumarate may result atleast in part from downregulation of the DctP dicarboxylate per-mease. Our results further highlight the complex nature of the B.

FIG 6 Western analysis of DctP-FLAG. Western blot analysis was used tomonitor the expression of DctP-FLAG in various mutant backgrounds. Tenmicrograms total protein from membrane fractions was loaded per lane. Eachlane is labeled with the strain background, and a wild-type strain carrying noFLAG construct was included as a negative control. The first lane is the molec-ular mass marker (in kDa). Development was carried out with anti-FLAGprimary antibody and alkaline phosphatase-linked secondary anti-rabbit an-tibody.

FIG 7 Growth phenotypes of selected mutant strains. (A) Growth curves of mutant strains affected in the iron-sparing response in succinate MM. The strainsused in this experiment are as follows: WT (open diamond), fur mutant (cross), fur fsrA mutant (open triangle), and fur fsrA �fsrA strain (HB12573, filledtriangle). (B) Growth curves of mutant strains affected in the iron-sparing response in fumarate MM. Strain designations are as in panel A. (C and D) Comparisonof growth in succinate MM (C) or fumarate MM (D). Column labels indicate amounts of IPTG added. Columns represent final OD600s after 24 h of growth at37°C. The strains used in this experiment are as follows: WT �Pspac-dctP-FLAG (HB12551, white) and fur �Pspac-dctP-FLAG (HB12558, gray). All growth datapresented here are the averages and standard deviations for three biological replicates.

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subtilis iron-sparing response, which, though largely dependenton the FsrA sRNA, additionally involves the poorly characterizedFbpABC proteins. These coregulators may function at some tar-gets as part of a common pathway with FsrA, possibly by acting asRNA chaperones or in recruitment of the RNA degradation ma-chinery. In other cases, FbpABC have effects independent of FsrAand may act directly as RNA-binding proteins or in conjunctionwith yet-to-be-identified sRNA partners.

ACKNOWLEDGMENTS

This work was supported by a grant from the National Institutes of Health(GM059323 to J.D.H.) and by a grant from the Deutsche Forschungsge-meinschaft (AN746/2-1 to H.A.). G.T.S. was partially supported by theNIH Predoctoral Training in Cellular and Molecular Biology grantGM007273.

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