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Staphylococcus aureus adapts to the host nutritional environment by coordinating the activity of central metabolic enzymes

  • Reginald A. Woods,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Department of Pharmaceutical Sciences, University of Illinois at Chicago – College of Pharmacy, Chicago, Illinois, United States of America, Department of Microbiology and Immunology, University of Illinois at Chicago – College of Medicine, Chicago, Illinois, United States of America

  • Iván C. Acosta,

    Roles Investigation, Methodology, Writing – review & editing

    Affiliation Department of Microbiology and Immunology, University of Illinois at Chicago – College of Medicine, Chicago, Illinois, United States of America

  • Zachary J. Resko,

    Roles Investigation, Methodology, Writing – review & editing

    Affiliation Department of Microbiology and Immunology, Loyola University Chicago - Stritch School of Medicine, Maywood, Illinois, United States of America

  • Charles Agbavor,

    Roles Formal analysis, Investigation, Methodology, Writing – review & editing

    Affiliation Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America

  • Luka Svet,

    Roles Formal analysis, Methodology, Visualization, Writing – review & editing

    Affiliation Department of Host-Microbe Interactions, St Jude Children’s Research Hospital, Memphis, Tennessee, United States of America

  • Manaar Yousef,

    Roles Formal analysis, Investigation, Methodology

    Affiliation Department of Microbiology and Immunology, University of Illinois at Chicago – College of Medicine, Chicago, Illinois, United States of America

  • Wei Ping Teoh,

    Roles Investigation, Methodology

    Affiliation Department of Microbiology and Immunology, Loyola University Chicago - Stritch School of Medicine, Maywood, Illinois, United States of America

  • Victor J. Torres,

    Roles Funding acquisition, Resources, Supervision, Writing – review & editing

    Affiliation Department of Host-Microbe Interactions, St Jude Children’s Research Hospital, Memphis, Tennessee, United States of America

  • Laty A. Cahoon,

    Roles Funding acquisition, Methodology, Supervision, Writing – review & editing

    Affiliation Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America

  • Francis AlonzoIII

    Roles Conceptualization, Data curation, Funding acquisition, Project administration, Supervision, Writing – original draft, Writing – review & editing

    falonzo@uic.edu

    Affiliations Department of Microbiology and Immunology, University of Illinois at Chicago – College of Medicine, Chicago, Illinois, United States of America, Lead contact

Abstract

The nutritional demands imposed by disparate infection sites represent a significant barrier to bacterial survival. Yet, the proclivity of pathogens such as Staphylococcus aureus to cause disease at nearly all host sites implies significant metabolic flexibility to promote infection. S. aureus catabolizes glucose in several ways, including the phosphotransacetylase (Pta) – acetate kinase (AckA) pathway. The Pta-AckA pathway uses acetyl-CoA derived from the major glycolytic end-product, pyruvate, to rapidly generate ATP, producing acetate as a byproduct. Yet, flux through Pta-AckA necessitates coordinating glycolytic activity with the production of acetyl-CoA and its delivery to Pta-AckA. The generation of acetyl-CoA occurs through the pyruvate dehydrogenase (PDH) complex, an enzyme that requires attachment of the metabolic cofactor, lipoic acid, for its function. Thus, delivery of lipoic acid to enzyme complexes has the potential to serve as a determinant of metabolic adaptation. Here, we provide evidence for a functional link between the lipoic acid transfer enzyme, LipL, and Pta. We demonstrate pta and lipL are transcriptionally coupled and that Pta and LipL directly interact, with potential to direct metabolic flux through Pta-AckA. Both Δpta and ΔlipL mutants are defective for acetate production with evidence for alternative fates for pyruvate that depend on blockade upstream or downstream of the pyruvate node. The functional pairing of Pta and LipL is required for optimal skin infection, whereas Pta and LipL have separable functions in bloodstream infection. Furthermore, we found that a complete block to acetate production leads to significant attenuation in vivo, cementing a direct role for acetogenesis in infection. Together, our results establish a mechanism by which S. aureus regulates metabolite flux by coupling enzymes in linked metabolic pathways to promote energy balance and survival during infection.

Author summary

Staphylococcus aureus causes infections within nearly all host tissues. Several virulence traits contribute to its survival at diverse sites, including the ability to produce myriad toxins, adhesins, and immunomodulatory enzymes. S. aureus also has remarkable metabolic plasticity, allowing it to overcome host-imposed nutrient restriction. In this work, we establish a genetic and functional coupling that links two metabolic pathways involved in S. aureus central carbon metabolism. Our work suggests that the coordinated expression and activity of an enzyme required for the delivery of the metabolic cofactor, lipoic acid, and an enzyme involved in acetogenesis, facilitates optimal metabolite flux and promotes S. aureus survival during infection. Furthermore, our studies support a direct role for acetate production in S. aureus survival during infection. Altogether, this work introduces a new facet of regulatory control over metabolic plasticity in S. aureus with important implications for pathogenesis.

Introduction

The host nutritional landscape can dramatically affect the ability of bacterial pathogens to establish infection [16]. The adaptation of microbes to host nutrient deprivation is crucial for pathogens that cause infection in a wide range of host tissues [7]. Staphylococcus aureus is a Gram-positive pathogen that can infect nearly all host tissues and causes significant morbidity and mortality globally [8,9]. To successfully establish infection, this bacterium not only uses tissue-specific defenses that block immune clearance, but also harnesses the host environment to optimize metabolism and energy expenditures [3,4,6,10,11]. S. aureus adapts to the host nutritional milieu by employing a complex network of transcriptional regulators that fine-tune metabolic gene expression to promote survival and growth [4,12]. The ability of S. aureus to optimize metabolic efficiency during infection extends beyond transcriptional regulation. Several bioinformatic and functional studies indicate that the directionality and efficiency of metabolite production are enhanced by high-affinity or transient protein-protein interactions and post-translational modifications [1316], highlighting critical post-translational checkpoints in metabolic adaptation. As a pathogen that evolved closely with humans, S. aureus also adapts by engaging in piracy of host nutrients during infection [1,2,5,17,18]. Indeed, S. aureus can use host lipids, carbohydrates, metals, and proteins to augment metabolite flux or bypass energetically demanding biological processes [24,1921]. Work from our lab and others suggests that the ability of S. aureus to establish infection in diverse tissues is due in part to adaptations that permit scavenging of key nutrients or redirecting of metabolism to promote survival [1,2,5,17,18,22].

One molecule with low bioavailability in the host is the metabolic cofactor lipoic acid, on account of its synthesis as a protein-bound precursor and its rapid clearance after dietary consumption [2325]. Lipoic acid is an organosulfur derivative of the medium-chain fatty acid, octanoic acid, that is required for the activation of α-ketoacid dehydrogenase complexes. Its redox-sensitive dithiolane ring aids in shuttling substrates through each complex [25]. The lipoic acid-dependent enzymes of S. aureus include pyruvate dehydrogenase (PDH), 2-oxoglutarate dehydrogenase (OGDH), and branched-chain 2-oxoacid dehydrogenase (BCODH) complexes, as well as the glycine cleavage system (GCS) [1,26]. S. aureus synthesizes lipoic acid de novo and scavenges it from host environments to promote survival [1]. The use of both pathways during infection is exemplified by evidence that shows lipoic acid scavenging is required for survival in some host tissues (kidneys), but not others (heart) [1]. Central to lipoic acid acquisition is the amidotransferase, LipL, which harnesses lipoic acid bound to the H subunits of the glycine cleavage system (GcvH) or the GcvH homolog, GcvH-L, for delivery to conserved lysine residues on the E2 subunits of each α-ketoacid dehydrogenase complex (E2-PDH, E2-OGDH, and E2-BCODH) [1,26]. Lipoic acid attachment to these enzyme complexes represents an essential post-translational modification, as LipL-deficient strains of S. aureus have compromised growth in vitro and are highly attenuated during bloodstream infection [5,26]. Altogether, these studies suggest that dynamic delivery of lipoic acid to metabolic enzyme complexes is likely required to facilitate metabolic plasticity and pathway adaptations needed to promote bacterial survival during infection.

LipL-dependent lipoylation of the E2 subunits of PDH and OGDH is critical for glycolysis and the tricarboxylic acid (TCA) cycle, respectively [26]. PDH generates acetyl-CoA from pyruvate upon exit from glycolysis, and OGDH generates succinyl-CoA from α-ketoglutarate in the TCA cycle [1,26]. The acetyl-CoA generated by PDH has several fates depending on the status of the cell and the nutrients available for use. These include the potential to enter fermentative pathways, fatty acid biosynthesis, TCA cycle, and nucleotide biosynthesis pathways [2729]. During carbon overflow in vitro, S. aureus primarily ferments glucose by shuttling acetyl-CoA into the phosphotransacetylase (Pta) - acetate kinase (AckA) pathway to rapidly synthesize ATP [28]. Pta catalyzes the generation of acetyl-phosphate from acetyl-CoA, which is used in a substrate-level phosphorylation reaction by AckA to generate acetate and ATP [27,28]. The Pta-AckA pathway promotes rapid growth in vitro during overflow metabolism when glucose and oxygen are abundant [27]. Extensive prior work established that the Pta-AckA pathway is vital for energy production and metabolic homeostasis during overflow metabolism in S. aureus [28,30]. Though pta is commonly positioned near, or co-transcribed with, ackA in many bacterial pathogens, we previously determined that in S. aureus, the start codon of lipL is located two nucleotides downstream of the pta stop codon [26]. The potential genetic linkage between pta and lipL and the dependency on efficient LipL-dependent lipoyl transfer for PDH activity highlights the relevance of LipL to central metabolism and suggests a potential functional link to acetate fermentation pathways.

As a facultative anaerobe, S. aureus can replicate in both high and low oxygen environments [3,31]. Past studies indicate that Pta-AckA activity increases during growth in low oxygen to support NAD+ generation and fermentative processes [27,32]. This extends the role of Pta beyond overflow metabolism and implies relevance of the pathway to conditions that occur during host infection (e.g., low oxygen). Inactivation of the Pta-AckA pathway shifts S. aureus metabolism away from acetate fermentation, leading to increased carbon flux through glycolysis and the TCA cycle [28]. Pathway inactivation also leads to early bacterial cell death in some S. aureus strains due to the induction of the cid genes [28]. This is thought to be due to the imposed metabolic block at pyruvate and the cellular requirement to combat intracellular pyruvate accumulation [28]. The cid locus comprises three genes, cidABC, which play a vital role in stationary phase cell death, autolysis, and biofilm formation [3336]. CidA is a functional holin that supports endolysin-induced cell lysis, and CidC is a pyruvate:menaquinone oxidoreductase that converts pyruvate directly to acetate [37,38]. Although its mechanism of action is not fully understood, CidB is thought to act in tandem with CidA to regulate cell lysis and is necessary for full activation of CidC [39]. Work from Thomas et al. found that inactivation of CidC decreased the rate of stationary phase cell death, which disrupts S. aureus biofilm development and biofilm-related disease outcomes [36]. Despite the connection between Pta-AckA and CidC as compensatory pathways to accommodate carbon flow, we do not yet have a complete picture of how Pta, CidC, and LipL interface to promote metabolic adaptability during infection. To date, no studies have assessed the individual versus combined contributions of Pta and CidC during S. aureus infection with planktonic cells.

The prevailing evidence thus far suggests there are contributions from several metabolic pathways, including glycolysis, as well as lipoic acid biosynthesis and salvage, to S. aureus adaptation to host tissues [1,4042]. The unusual positioning of pta and lipL genes in the S. aureus genome may further link lipoic acid transfer and acetogenesis in ways that dictate the fate of major glycolytic metabolites. In this work, we investigated the convergence of lipoic acid relay and Pta-AckA pathways and determined the relative contribution of each to pathogenesis. We show that pta and lipL share a distinct genetic organization in Staphylococci that diverges from pathogenic firmicutes and Gram-negative pathogens. pta and lipL are co-transcribed, and the two encoded proteins (Pta and LipL) directly interact. This genetic and functional linkage promotes infection in the skin, whereas separable functions for Pta and LipL are required for systemic infection. Furthermore, we verified the established block at the pyruvate node in the absence of Pta and determined that a similar block occurs in the absence of LipL, leading to a commensurate increase in cidC transcripts and lactate production during aerobic growth. Finally, we found that bacterial acetate production is required for survival in both skin and systemic infection. Altogether, these studies provide new insight into the factors governing the metabolic plasticity of S. aureus during infection with potential applicability to other pathogens.

Results

pta and lipL are genetically linked in Staphylococci

S. aureus preferentially uses glycolysis to metabolize glucose (Fig 1A) [4,19,43]. The lipoic acid-dependent PDH complex serves as a major exit point from the glycolytic pathway, where the decarboxylation of pyruvate leads to the generation of acetyl-CoA. During periods of carbon overflow in vitro, acetyl-CoA is predominantly shuttled into the Pta-AckA pathway to generate ATP and acetate via substrate-level phosphorylation (Fig 1A), in part because carbon catabolite repression suppresses TCA cycle gene expression [44,45]. Following glucose consumption, acetate is reassimilated via acetyl-CoA synthase (Acs), for use in the TCA cycle (Fig 1A). Central to glycolysis and TCA cycle function is LipL-dependent lipoylation of the E2 subunits of PDH and OGDH (Fig 1A). In a prior study, we determined that the lipL (SAUSA300_0571) open reading frame begins two nucleotides downstream from the stop codon of pta (SAUSA300_0570), implying a gene pairing that links lipoyl transfer activity with the Pta-AckA pathway [26]. Considering pta and ackA are genetically linked in classically studied microorganisms such as Escherichia coli, we wondered if this unusual pta-lipL linkage observed in S. aureus was widespread. We conducted a comparative synteny analysis of the pta gene environment. We surveyed representative Gram-negative or Gram-positive bacterial pathogens and Mycobacterium tuberculosis, as well as commensals Lactococcus lactis subs. cremoris, Bacillus subtilis, and E. coli, and found that most Gram-negative pathogens surveyed were likely to have ackA and pta positioned in an operon, like E. coli (Fig 1B). By contrast, analysis of M. tuberculosis and Gram-positive pathogens showed that pta and lipL were in close genetic proximity for some Gram-positives (Bacillus anthracis and S. aureus), whereas others were positioned at greater than 70kb nucleotide distances (~70kb for Streptococcus pyogenes, ~ 2500kb for Listeria monocytogenes, and ~300kb for Enterococcus faecalis) (Fig 1C). S. aureus was the only species with pta and lipL genetically linked in a putative operon, potentially implying a unique genetic arrangement for Staphylococci (Fig 1C). Indeed, coagulase-positive and negative Staphylococci all have the same pta-lipL organization, indicating it is a conserved feature of the genus (Fig 1D).

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Fig 1. pta and lipL are genetically linked in Staphylococci.

(A) Model of acetate fermentation in S. aureus. Glucose is converted to pyruvate, the primary end-product of glycolysis. Pyruvate has several fates, one of which is its oxidative decarboxylation by pyruvate dehydrogenase (PDH) to generate Acetyl-CoA. Pyruvate can also be directly decarboxylated (CidC) to produce acetate. Acetyl-CoA can enter the tricarboxylic acid (TCA) cycle or is used by the phosphotransacetylase (Pta) to generate Acetyl-phosphate (Ac-P), the substrate for acetate kinase (AckA). The activity of AckA generates Acetate and ATP. PDH activity is regulated by lipoic acid (lipoyl) attachment, which is mediated by delivery of lipoic acid from the H subunit of the glycine cleavage system (GcvH) by the amidotransferase, LipL. (B-D) Synteny analysis of pta and lipL genes. (B) Phylogenetic tree of Gram-negatives, including pta synteny analysis adjacent to the relevant microorganism. (C) Phylogenetic tree of Gram-positives and M. tuberculosis, including pta synteny analysis adjacent to the respective microorganism. (D) Phylogenetic tree of Staphylococci including pta synteny analysis. (E) Normalized and mapped transcript reads across the pta-lipL region in WT and a ΔlipL mutant. (F) qRT-PCR analysis of RNA extracted from WT, Δpta, and ΔlipL strains at 6 hours of growth. ****, p < 0.0001 by one-way ANOVA with Tukey’s post hoc test. qRT-PCR experiments were conducted with two independent biological replicates in technical triplicate. Boxplots indicate the median and quartiles. Whiskers indicate the range.

https://doi.org/10.1371/journal.ppat.1014183.g001

To establish that S. aureus co-transcribes pta and lipL, we conducted RNA sequencing of WT S. aureus and a ΔlipL mutant grown to late exponential phase. The read analysis indicated that pta and lipL transcripts consist of a single mRNA encoding both genes (Fig 1E). The deletion of lipL led to the generation of a truncated transcript but did not negatively impact pta expression (Fig 1E). To validate the RNAseq results, we measured transcript levels of pta, lipL and the junction between the pta and lipL genes via qRT-PCR. Transcript levels were similar between the pta, lipL, and the junction in WT S. aureus (Fig 1F). Junctional amplicons were not detected from the Δpta and ΔlipL mutants (Fig 1F). Altogether, these data indicate that the genetic link between pta and lipL is conserved in Staphylococci and the genes are co-transcribed.

Loss of either pta or lipL compromises acetate production

Given the evidence for co-transcription of pta and lipL in S. aureus and the role of Pta in overflow metabolism, we sought to determine how these genes contribute to acetate production via Pta-AckA and metabolic flux in general. We generated in-frame single and double deletions of pta and lipL in the methicillin-resistant Staphylococcus aureus (MRSA) strain LAC [46,47]. We complemented pta and lipL in single copy in the chromosome with constitutive expression [48], and subsequently determined if the loss of pta or lipL resulted in growth defects or shifts in metabolite production. The Δpta mutant had a marginal delay in exit from logarithmic phase growth in tryptic soy broth (TSB) compared to WT (Fig 2A). A ΔlipL mutant, on the other hand, had compromised growth kinetics, including dramatically reduced growth in TSB, consistent with previous work from our group (Fig 2A) [1]. A significant component of the ΔlipL mutant growth defect in TSB is due to loss of LipL-dependent lipoylation of the BCODH complex, which is essential for branched-chain fatty acid synthesis [5]. Indeed, growth of ΔlipL mutant was substantially restored in TSB supplemented with branched-chain carboxylic acids (BCCAs) (isobutyric acid, 2-methylbutyric acid, and isovaleric acid) that bypass the requirement for BCODH or with use of the lipL complement strain [1,26] (Fig 2A). To test for defects in lipoylation of E2 subunits of enzyme complexes, we conducted immunoblots on whole cell lysates of the Δpta and ΔlipL mutants and their complement strains grown in TSB + BCCAs. Consistent with prior results, the ΔlipL mutant had defective lipoylation compared to WT [26] (Fig 2B), whereas the Δpta mutant had evidence for increased lipoylation on E2 subunits (Fig 2B). Thus, while lipoylation itself is not a direct effect of Pta, the degree of lipoylation on E2 subunits is increased in its absence (see below). These data indicate that the effects of pta and lipL on growth kinetics and lipoylation in broth are separable and largely driven by LipL-dependent effects on BCODH activity.

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Fig 2. Loss of either pta or lipL compromises acetate production.

(A) Growth of WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL strains in TSB and TSB + BCCAs [10 mM isobutyric acid (IB), 9 mM 2-methylbutyric acid (2MB), 9 mM isovaleric acid (IV) + 10 mM sodium acetate (NaAc)] containing 14 mM glucose. (B) α-lipoic acid immunoblots of whole cell lysates from the indicated strains after 9-hours of growth in TSB medium. The presented blot and Coomassie-stained gel are representative of at least three independent experiments. (C) Quantification of glucose, acetate, lactate and formate from WT, Δpta, Δpta + pta culture supernatants over time in TSB with 14 mM glucose. (D) Quantification of glucose, acetate, lactate and formate from WT, ΔlipL, ΔlipL + lipL culture supernatants over time in TSB with 14 mM glucose and BCCA supplementation. Each metabolite quantification assay is representative of three independent experiments, with each timepoint measured in technical triplicate. Errors bars indicate standard deviation from the mean. Some lines on growth curve graphs (Δpta + pta, and ΔlipL + lipL) are obscured because they overlap.

https://doi.org/10.1371/journal.ppat.1014183.g002

We next assessed glycolytic flux over time by measuring glucose and acetate levels in media containing 14 mM glucose under aerobic conditions to promote carbon overflow metabolism [28,49]. In addition to acetate, we measured lactate and formate as alternative pyruvate fermentation products in S. aureus [31,32,50]. As previously reported, glucose was rapidly consumed within 6 hours of growth along with a commensurate increase in acetate that peaked at 6 hours and was reassimilated in stationary phase (Fig 2C) [27,28]. The Δpta mutant consumed all the glucose in the media by 6 hours with no differences compared to the WT strain (Fig 2C). Peak acetate levels from the Δpta mutant were ~13 mM, a ~ 57% reduction compared to WT (Fig 2C). There were no differences in lactate or formate levels produced by the Δpta mutant compared to WT (Fig 2C). Conversely, the ΔlipL mutant had a delay in the glucose consumption rate relative to WT (Fig 2D). Peak acetate production from the ΔlipL mutant was around 8 mM, a ~ 70% reduction compared to WT (Fig 2D). There was also a commensurate increase in lactate production by the ΔlipL mutant, which peaked at ~8 mM at 6 hours (Fig 2D). Growth and metabolite quantification assays using glucose-free media or low glucose supplementation (3.5 mM) established that acetate production requires LipL and that levels depend on the amount of glucose added. Compensatory increases in lactate production by a ΔlipL mutant are only observed when glucose is provided as a carbon source (14 mM and 3.5 mM) (S1 Fig and Fig 2D). Together, these data suggest that both Pta and LipL are required for optimal acetate fermentation during overflow metabolism and under conditions where glucose is limiting. While deletion of either pta or lipL leads to compensatory acetate production, presumably by other acetogenic pathways, lactate fermentation is only induced upon deletion of lipL in the presence of glucose, potentially to offset a pyruvate bottleneck during overflow that is associated with inactivation of PDH.

LipL and Pta coordinate PDH activity and acetate production

pta and lipL are co-transcribed (Fig 1). The deletion of either gene alone shifts acetate production and metabolic flux either downstream (Δpta) or upstream (ΔlipL) of PDH (Figs 1A and 2). We hypothesized that the tandem expression of pta-lipL might promote coordination of pyruvate decarboxylation with the delivery of acetyl-CoA to Pta-AckA to improve metabolic efficiency. To test this, we assessed the effect of loss of the entire pta-lipL locus on growth and metabolite production. The Δpta ΔlipL mutant had severely compromised growth in TSB, which was largely complemented when TSB was supplemented with BCCAs or when using a Δpta ΔlipL + lipL complement strain (Fig 3A). The Δpta ΔlipL + pta strain did not restore growth in TSB without BCCAs (Fig 3A). Immunoblots on whole cell lysates of the Δpta ΔlipL double mutant and complement strains revealed that only those strains lacking lipL had defective lipoylation profiles compared to WT (Fig 2B).

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Fig 3. Pta and LipL coordinate PDH activity and acetate production.

(A) Growth of WT, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL strains in TSB and TSB + BCCAs [10 mM isobutyric acid (IB), 9 mM 2-methylbutyric acid (2MB), 9 mM isovaleric acid (IV) + 10 mM sodium acetate (NaAc)] containing 14 mM glucose. (B) Quantification of glucose, acetate, lactate, and formate from WT, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL culture supernatants over time in TSB with 14 mM glucose and BCCA supplementation. Each metabolite quantification assay is representative of three independent experiments, with each timepoint measured in technical triplicate. Error bars indicate standard deviation from the mean.

https://doi.org/10.1371/journal.ppat.1014183.g003

The WT and Δpta ΔlipL + lipL strains consumed all glucose by 6 hours, whereas the Δpta ΔlipL double mutant and Δpta ΔlipL + pta had delays in glucose consumption (Fig 3B). Notably, the Δpta ΔlipL double mutant did not produce additional acetate (Fig 3B). The Δpta ΔlipL + pta strain mirrored this phenotype and acetate levels did not accumulate beyond ~5 mM, a ~ 83% reduction compared to peak acetate production in the WT and Δpta ΔlipL + lipL strains (Fig 3B). Intriguingly, the Δpta ΔlipL + lipL strain had delayed acetate reassimilation. Furthermore, compensatory lactate production by the Δpta ΔlipL double mutant and Δpta ΔlipL + pta strains was consistent with a redirection of pyruvate toward lactate fermentation (Fig 3B). Taken together, these data confirm that defects in growth associated with the Δpta ΔlipL mutant are due to activities of LipL that are independent of Pta-AckA and flux through PDH. Furthermore, loss of both pta and lipL halts acetate production entirely, redirecting pyruvate towards alternative fates, such as lactate fermentation. Constitutive expression of lipL favors alternative modes of acetate production that do not depend on Pta-AckA.

Pta and LipL proteins directly interact

Prior functional and computational studies suggest that metabolic flux can be enhanced by protein-protein interactions and protein complex formation [1315]. Considering our demonstration of the coordinated expression of pta and lipL and the necessity of both for optimal acetate production, we hypothesized there might be a direct interaction between Pta and LipL that could facilitate acetate fermentation. We first used AlphaFold3 to predict the likelihood of a direct interaction between Pta and LipL. The AlphaFold3 model predicted a potential interaction between Pta and LipL, with a template modeling of 0.76 and an interface predicted template modeling (ipTM) score of 0.61 (Fig 4A). Considering the ipTM score of the predicted interaction falls at the likelihood threshold for a potential interaction, we opted to validate this prediction by expressing and purifying Pta (Pta-6xHis) and LipL (LipL-6xHis) and conducting a biophysical assessment of a direct interaction using microscale thermophoresis (MST). Recombinant Pta was labeled with the amine-reactive dye, N-hydroxysuccinimide (NHS) and titrated against unlabeled LipL (Fig 4B). MST determined that Pta interacts with LipL in solution with moderate affinity (Kd of 490 + /- 105 nM) (Fig 4B). To determine if the proteins interact in vivo, we cloned the coding sequences of both pta and lipL into the adenylate cyclase-based Bacterial two-hybrid (BACTH) system [51,52]. Pta and LipL interacted strongly when expressed in E. coli, achieving similar levels of β-galactosidase activity as the leucine zipper positive control (Fig 4C). In considering the possibility that an interaction between Pta and LipL might improve efficiency of metabolic flux through PDH to Pta-AckA, we reasoned that loss of Pta would enhance the demand for LipL-mediated delivery of lipoic acid to E2 proteins of PDH and OGDH as a compensatory measure to drive carbon flux. Indeed, a Δpta mutant had increased lipoylation on E2-PDH and E2-OGDH at 3 and 6 hours compared with WT and the Δpta + pta strain (Fig 4D and 4E). This increase in lipoylation was not associated with an increase in pdhC (E2-PDH) or sucB (E2-OGDH) transcripts at 3 or 6 hours (S2A Fig), suggesting increased delivery of lipoic acid to E2-PDH and E2-OGDH by LipL. Collectively, these results indicate Pta and LipL directly interact in vitro and in vivo. Furthermore, the loss of Pta results in increased delivery of lipoic acid to E2-PDH and E2-OGDH as a compensatory measure.

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Fig 4. Pta and LipL proteins directly interact.

(A) AlphaFold3 prediction of the interaction between Pta (blue) and LipL (pink). pTM (0.76) and an ipTM (0.61) are displayed graphically below the model. (B) Microscale thermogram of Pta-NHS titrated against the recombinant LipL. The top panel shows the thermophoretic time-traces of four independent experiments, and the blue and pink areas represent time spans used to obtain the fluorescence cold (Fc) and hot (Fh) regions, respectively. The middle panel shows the binding curve with the line of best fit using the 1:1 binding model with an error surface projection confidence of 95%. The residuals between the data and fit are shown in the bottom panel. Kd is presented as the mean ± standard deviation of four independent replicates. (C) Bacterial adenylate cyclase two-hybrid (BACTH) assay was used to assay an interaction between Pta and LipL. Graph displays β-galactosidase activity (Miller Units) from E. coli BTH101 co-transformed with pUT18C-pta and pKT25-lipL, pUT18C-zip and pKT25-zip (positive control – PC) or pUT18C and pKT25 vectors (negative control – NC). ***, p < 0.001 by one-way ANOVA with Tukey’s post hoc test. Cultures of E. coli BTH101strains co-transformed with the aforementioned plasmid combinations were also spotted on LB agar plates with X-Gal as an indicator. Data are representative of at least three independent experiments. (D-E) α-lipoic acid immunoblots of whole cell lysates from WT, Δpta, and Δpta + pta strains after 3 and 6-hours of growth in TSB medium. Densitometric quantification of E2-PDH and E2-OGDH bands in Δpta and Δpta + pta strains relative to WT bands. *, p < 0.05; **, p < 0.01 by Kruskal-Wallis test with Dunn’s post hoc analysis. The presented blots and Coomassie-stained gels are representative of four independent experiments. The mean and standard error of the mean are shown.

https://doi.org/10.1371/journal.ppat.1014183.g004

The coordinated activity of Pta and LipL is important during infection of the skin, whereas additional functions of LipL promote systemic infection

Previous work from our group found that LipL is required for optimal S. aureus infection in both a murine sepsis model and a murine skin and soft tissue infection model [26]. Follow up studies determined that S. aureus is mostly refractory to lipoic acid deficiency in murine skin but not kidneys on account of its ability to bypass LipL-dependent branched-chain fatty acid synthesis by incorporating host unsaturated fatty acids [5]. These results do not preclude the possibility that the coordinated activity of Pta and LipL that drives acetate fermentation might contribute to infection in one or both infection models. To test this, we infected mice intravenously or intradermally with WT, Δpta, Δpta + pta, ΔlipL, ΔlipL + lipL, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL strains. At 96 hours post intravenous infection, kidneys from Δpta mutant-infected animals had ∼100-fold fewer CFUs compared to WT (Fig 5A). By contrast, the kidneys from ΔlipL mutant-infected mice had ~ 10000-fold fewer CFUs (Fig 5A). The kidneys from Δpta ΔlipL, and Δpta ΔlipL + pta infected mice phenocopied ΔlipL mutant-infected mice with ~10000-fold fewer CFUs (Fig 5A). Systemic infection with Δpta + pta, ΔlipL + lipL, and Δpta ΔlipL + lipL complement strains restored CFUs in the kidney to nearly WT levels (Fig 5A). At 72 hours post intradermal infection, abscesses from mice infected either with Δpta, ΔlipL, and Δpta ΔlipL mutants phenocopied one another with ∼10-fold fewer CFUs compared to WT (Fig 5B). Infection with the Δpta + pta and ΔlipL + lipL complement strains restored abscess CFUs to nearly WT levels (Fig 5B). Infection with either Δpta ΔlipL + pta or Δpta ΔlipL + lipL strains did not restore CFU to WT levels (Fig 5B). Considering the identical attenuation for Δpta, ΔlipL, and Δpta ΔlipL, Δpta ΔlipL + pta or Δpta ΔlipL + lipL strains during infection of the skin, we conclude that the coordinated activity between Pta and LipL is required for S. aureus survival at this site. In contrast, during systemic infection, the contributions of Pta and LipL to virulence are separable and dominated by independent roles for LipL in promoting branched fatty acid synthesis, as we have previously published [5].

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Fig 5. The coordinated activity of Pta and LipL is important during infection of the skin, whereas additional functions of LipL promote systemic infection.

(A) Bacterial burden in the kidneys of mice 96 hours after bloodstream infection with 1.0 x 107 CFU of WT, Δpta, Δpta + pta, ΔlipL, ΔlipL + lipL, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL strains. Animal numbers displayed are as follows: WT, N = 36; Δpta, N = 29; Δpta + pta, N = 28; ΔlipL, N = 20; ΔlipL + lipL, N = 19; Δpta ΔlipL, N = 20; Δpta ΔlipL + pta, N = 8; and Δpta ΔlipL + lipL, N = 8. ns, not significant; *, p < 0.05; ***, p < 0.001; ****, p < 0.0001 by Kruskal-Wallis test with Dunn’s post hoc analysis. (B) Bacterial burden in the skin of mice 72 hours after intradermal infection with 1.0 x 107 CFU of WT, Δpta, Δpta + pta, ΔlipL, ΔlipL + lipL, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL. Animal numbers displayed are as follows: WT, N = 16; Δpta, N = 16; Δpta + pta, N = 16; ΔlipL, N = 16; ΔlipL + lipL, N = 16; Δpta ΔlipL, N = 16; Δpta ΔlipL + pta, N = 16; and Δpta ΔlipL + lipL, N = 16. ns, not significant; **, p < 0.01; ****, p < 0.0001 by Kruskal-Wallis test with Dunn’s post hoc analysis. log10 CFU per organ or abscess is displayed for each infected mouse along with the median as a measure of central tendency. Graphs represent combined data from at least two independent experiments.

https://doi.org/10.1371/journal.ppat.1014183.g005

Loss of lipL induces significant transcriptional changes in S. aureus

Our data suggest that a block to exit from glycolytic metabolism at PDH redirects metabolic flux on account of pyruvate accumulation in the cell. To test this, we quantified intracellular pyruvate levels from WT, Δpta, Δpta + pta, ΔlipL, ΔlipL + lipL, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL strains at 3 hours. We found that all strains harboring a ΔlipL mutation had approximately twice the amount of intracellular pyruvate compared to WT (~745 pmol for a ΔlipL mutant versus ~363 pmol for WT) (Fig 6A). The redirection of pyruvate metabolism is further substantiated by increases in lactate and Pta-AckA - independent generation of acetate (Figs 2D and 3B). Given the importance of LipL in activating the PDH, OGDH, and BCODH complexes [1,26], we hypothesized that, in addition to the shifts in glucose metabolism at the PDH node, LipL might also drive a metabolic landscape that is shifted in a ΔlipL mutant on account of disruptions to TCA cycle activity and branched fatty acid synthesis. To test this possibility, we grew WT and ΔlipL mutant strains to late-exponential phase and performed bulk RNA-sequencing. Our results confirmed several major changes in gene expression patterns between the WT and ΔlipL mutant (Fig 6B and 6C). The ΔlipL mutant significantly upregulated genes involved in virulence, histidine catabolism and oxidative metabolism and significantly downregulated genes involved in purine nucleotide biosynthesis and branched-chain amino acid biosynthesis (Fig 6D). Specifically, the loss of lipL increased expression of several cytoxin genes (lukS-PV, hla, psmβ1, and psmβ2), gudB (glutamate dehydrogenase), the hut operon (histidine uptake) and the qox operon (electron transport chain), while decreasing expression of the pur operon (purine biosynthesis), as well as the leu and the ilv operons (branched-chain amino acid biosynthesis) (Fig 6E). Furthermore, we saw substantially increased levels of the pyruvate oxidase cidC (SAUSA300_2477) (Fig 6C, 6E and 6F). CidC generates acetate directly from pyruvate and does not require PDH activity [37]. We also saw increased levels of alsD transcripts (Fig 6E). AlsSD diverts carbon flow towards neutral byproducts to prevent CidC-mediated acidification of the cell [36]. To validate our RNAseq results, we assessed cidC transcript levels in WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL strains via qRT-PCR. Indeed, we found a ~ 8-fold increase of cidC transcripts in both the Δpta and ΔlipL mutants (Fig 6F). Overall, RNAseq analysis confirmed that the loss of lipL significantly alters the S. aureus transcriptome, including changes to pathways involved in virulence, oxidative metabolism, amino acid metabolism, and nucleotide biosynthesis. Furthermore, the RNAseq dataset revealed increased levels of cidC transcripts, which were confirmed by qRT-PCR in both the Δpta and ΔlipL mutants.

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Fig 6. Loss of lipL induces significant transcriptional changes in S. aureus.

(A) Quantification of intracellular pyruvate from WT, Δpta, ΔlipL, Δpta + pta, ΔlipL + lipL, Δpta ΔlipL, Δpta ΔlipL + pta, and Δpta ΔlipL + lipL strains after 3 hours of growth in TSB. ns, not significant; **, p < 0.01 by Kruskal-Wallis test with Dunn’s post hoc analysis. Graphs represent combined data from three independent experiments. (B) Principal component analysis (PCA) of RNA sequencing datasets for the WT and ΔlipL mutant triplicate samples. (C) Volcano plot of transcriptional changes observed in a ΔlipL mutant compared to WT S. aureus during late-exponential phase growth. Each dot represents one gene. Vertical dotted lines represent log2 fold change = -2 and 2 cut-offs. Horizontal dotted line represents adj. p value = 0.05. (D) Analysis of upregulated and downregulated pathways in a ΔlipL mutant compared to WT. Black bars represent log(p-value); vertical dotted line is p-value < 0.05 threshold of significance as determined by NIH DAVID Bioinformatics pipeline. Blue bars represent the number of downregulated genes associated with the respective pathway, and pink bars represent the number of upregulated genes associated with the respective pathway. (E) Fold change of specific genes in the ΔlipL mutant compared to WT. (F) qRT-PCR analysis of RNA extracted from WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL strains after 3 hours of growth in TSB. ****, p < 0.0001 by one-way ANOVA with Tukey’s post hoc test. qRT-PCR experiments were conducted with two independent biological replicates in technical triplicate. Boxplots indicate the median and quartiles. Whiskers indicate the range.

https://doi.org/10.1371/journal.ppat.1014183.g006

The deletion of both pta and cidC significantly reduces acetate production by S. aureus

Prior studies showed that inactivation of the Pta-AckA pathway led to redirection of carbon into the TCA cycle [28,53]. Furthermore, loss of LipL or Pta leads to transcriptional changes that are suggestive of premature entry into the TCA cycle, increased oxidative metabolism, and increased acetate production by CidC (Fig 6F) [28]. Increased cidC levels in both Δpta and ΔlipL strains signify demand for acetate production in S. aureus regardless of whether the block occurs before or after PDH. To confirm prior studies and test if Pta and CidC are the primary sources of acetate, we generated an in-frame deletion of cidC in both WT and a Δpta mutant of S. aureus. The ΔcidC mutant had no effect on growth in TSB, whereas a Δpta ΔcidC double mutant had a marginal delay in transition to stationary phase growth (Fig 7A), like the Δpta single mutant (Fig 2A). The Δpta ΔcidC and Δpta ΔcidC + cidC strains, but not the ΔcidC or the Δpta ΔcidC + pta strains had evidence of increased lipoylation on E2 subunits consistent with more lipoylation occurring in the absence of Pta, but not CidC (Fig 7B).

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Fig 7. The deletion of both pta and cidC significantly reduces acetate production by S. aureus.

(A) Growth of WT, ΔcidC, Δpta ΔcidC, ΔcidC + cidC, Δpta ΔcidC + pta, and Δpta ΔcidC + cidC strains in TSB and TSB + BCCAs [10 mM isobutyric acid (IB), 9 mM 2-methylbutyric acid (2MB), 9 mM isovaleric acid (IV) + 10 mM sodium acetate (NaAc)] containing 14 mM glucose. (B) α-lipoic acid immunoblots of whole cell lysates from the indicated strains after 9-hour subculture growth in TSB medium. The presented blot and Coomassie-stained gel are representative of three independent experiments. (C) Quantification of glucose, acetate, lactate, and formate from WT, ΔcidC, and ΔcidC + cidC culture supernatants over time in TSB with 14 mM glucose. (D) Quantification of glucose, acetate, lactate, and formate from WT, Δpta ΔcidC, Δpta ΔcidC + pta, and Δpta ΔcidC + cidC culture supernatants over time in TSB with 14 mM glucose. Each metabolite quantification assay is representative of three independent experiments, with each timepoint measured in technical triplicate. Error bars indicate standard deviation from the mean.

https://doi.org/10.1371/journal.ppat.1014183.g007

When measuring glucose, acetate, lactate, and formate levels, we noted the ΔcidC mutant consumed all glucose in the media by 6 hours with no difference compared to the WT (Fig 7C). Peak acetate production was ~ 30 mM for all strains (Fig 7C). Furthermore, there was negligible production of lactate and formate (Fig 7C). The Δpta ΔcidC double mutant also consumed all glucose by 6 hours and had no delay in the glucose consumption compared to the WT (Fig 7D). Consistent with previous reports, there was negligible production of acetate from the Δpta ΔcidC double mutant (~5 mM, a ~ 83% reduction compared to WT). (Fig 7D) [28]. Peak acetate production from the Δpta ΔcidC + cidC was ~ 13 mM (Fig 7D), whereas acetate production from Δpta ΔcidC + pta was the same as WT (Fig 7D). There was no lactate or formate produced, consistent with our earlier observations that compensatory lactate fermentation only occurs when PDH is inactivated (Fig 7D). These data corroborate prior work and indicate that cidC is dispensable for S. aureus growth in broth yet is activated to compensate for the loss of Pta to promote acetate production (compare Figs 2C and 7D) [28,36].

Acetate production is required for S. aureus infection

In prior studies, CidC was implicated in the pathogenesis of biofilm-associated infection in the heart, suggesting CidC has a role in virulence [36]. Furthermore, the increase of cidC transcripts in the Δpta and ΔlipL mutants (Fig 6F) led us to hypothesize that acetate generation via CidC could be an important compensatory strategy to promote S. aureus survival in vivo, especially if acetate generation in and of itself were important for infection. To begin to test this possibility, we determined if cidC was required for S. aureus bloodstream and skin infection using planktonic cultures. We infected mice intravenously or intradermally with WT, ΔcidC, and ΔcidC + cidC strains. At 96 hours post intravenous infection, we isolated and homogenized kidneys from ΔcidC mutant-infected animals and found no difference in CFUs compared to WT (Fig 8A). At 72 hours post intradermal infection, there was also no difference in CFUs between strains (Fig 8A). We then infected mice intravenously or intradermally with WT, Δpta ΔcidC, Δpta ΔcidC + pta, and Δpta ΔcidC + cidC strains. After systemic infection, the kidneys from Δpta ΔcidC double mutant-infected animals had ∼10000-fold fewer CFUs compared to WT (Fig 8B). This result was in stark contrast to a Δpta mutant, which had a ~ 100-fold reduction in CFUs (Fig 5A). Complementation of the double mutant with pta restored kidney CFUs to nearly WT levels (Fig 8B), whereas complementation of the double mutant with cidC partially restored virulence to levels previously observed for a Δpta mutant (~100-fold fewer CFUs compared to WT) (Fig 8B). At 72 hours post intradermal infection, we found ∼100-fold fewer CFUs were recovered from the abscesses of Δpta ΔcidC double mutant compared to WT (Fig 8B). Like the kidneys, complementation with pta restored CFU levels to WT levels (Fig 8B), whereas complementation with cidC in the skin was not evident (Fig 8B).

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Fig 8. Acetate production is required for S. aureus infection.

(A) Upper panel - Bacterial burden in the skin of mice 72 hours after intradermal infection with 1.0 x 107 CFU of WT and ΔcidC strains. Animal numbers displayed are as follows: WT, N = 18; ΔcidC, N = 18. Lower panel - Bacterial burden in the kidneys of mice 96 hours after bloodstream infection with 1.0 x 107 CFU of WT, ΔcidC strains. Animal numbers displayed are as follows: WT, N = 34; ΔcidC, N = 33. NS, not significant. Statistics were calculated by Mann-Whitney test. (B) Upper panel - Bacterial burden in the skin of mice 72 hours after intradermal infection with 1.0 x 107 CFU of WT, Δpta ΔcidC, Δpta ΔcidC + pta, and Δpta ΔcidC + cidC strains. Animal numbers displayed are as follows: WT, N = 29; Δpta ΔcidC, N = 29; Δpta ΔcidC + pta, N = 28; Δpta ΔcidC + cidC, N = 28. Lower panel - Bacterial burden in the kidneys of mice 96 hours after bloodstream infection with 1.0 x 107 CFU of WT, Δpta ΔcidC, Δpta ΔcidC + pta, and Δpta ΔcidC + cidC strains. Animal numbers displayed are as follows: WT, N = 16; Δpta ΔcidC, N = 16; Δpta ΔcidC + pta, N = 16; Δpta ΔcidC + cidC, N = 16. ***, p < 0.001; ****, p < 0.0001 by Kruskal-Wallis test with Dunn’s post hoc analysis. (C) Upper panel - Bacterial burden in the skin of mice 72 hours after intradermal infection with 1.0 x 107 CFU of WT, Δagr::tet, Δpta ΔcidC, and Δpta ΔcidC Δagr::tet strains. Animal numbers displayed are as follows: WT, N = 16; Δagr::tet, N = 16; Δpta ΔcidC, N = 16; Δpta ΔcidC Δagr::tet, N = 16. Lower panel - Bacterial burden in the kidneys of mice 96 hours after bloodstream infection with 1.0 x 107 CFU of WT, Δagr::tet, Δpta ΔcidC, and Δpta ΔcidC Δagr::tet strains. Animal numbers displayed are as follows: WT, N = 12; Δagr::tet, N = 12; Δpta ΔcidC, N = 12; Δpta ΔcidC Δagr::tet, N = 12. *, p < 0.05; **, p < 0.01; ****, p < 0.0001 by Kruskal-Wallis test with Dunn’s post hoc analysis. log10CFU per organ or abscess is displayed for each infected mouse along with the median as a measure of central tendency. All graphs represent combined data from at least two independent experiments.

https://doi.org/10.1371/journal.ppat.1014183.g008

Among the pathways significantly upregulated in RNAseq analysis of a ΔlipL mutant (Fig 6E) were genes involved in virulence. Toxin genes, including hla, psmβ1, psmβ2, and lukS-PV, were amongst the most significantly upregulated (Fig 6F). These toxin genes are all regulated by the Accessory Gene Regulatory (Agr) two-component quorum sensing system [54,55]. Despite the increase in Agr-dependent virulence gene expression, a ΔlipL mutant remained attenuated in vivo (Fig 5) arguing that virulence factor expression is not contributing to in vivo phenotypes in this strain. Nevertheless, this outcome prompted us test if in vivo phenotypes linked to acetate production were potentially due to changes in Agr activity. To test this possibility, we infected mice intravenously or intradermally with WT, Δagr::tet, Δpta ΔcidC, and Δpta ΔcidC Δagr::tet strains. At 96 hours post-intravenous infection, kidneys from Δagr::tet mutant-infected animals had similar CFUs to WT (Fig 8C), consistent with previous reports [56,57]. Conversely, kidneys from Δpta ΔcidC and Δpta ΔcidC Δagr::tet mutant-infected animals had identical reduction in CFUs compared to WT (∼10000-fold) (Fig 8C). At 72 hours post intradermal infection, abscesses from mice infected with Δagr::tet mutant had ∼10-fold fewer CFUs compared to WT, which is consistent with previous literature [58] (Fig 8C). Abscesses from mice infected with Δpta ΔcidC double mutant had ∼100-fold fewer CFUs compared to WT (Fig 8C). Mice infected with Δpta ΔcidC Δagr::tet triple mutant had ∼1000-fold fewer CFUs, demonstrating an additive effect (Fig 8C). Taken together, these data suggest that acetate production mediated by Pta and CidC is required for infection and is Agr independent.

Discussion

In this study, we investigated the genetic and functional link between lipoic acid transfer and acetate production by S. aureus. We found that the genes encoding phosphotransacetylase, Pta, and the lipoic acid amidotransferase, LipL, are co-transcribed and that this regulatory arrangement is conserved amongst Staphylococci. At the protein level, Pta and LipL directly interact and their activities promote acetate fermentation (Pta-AckA) over oxidative metabolism. Deletion of either Pta or LipL significantly hindered acetate production, leading to an intracellular buildup of pyruvate and compensatory shifts in metabolism. This includes a substantial increase in cidC transcript, encoding the pyruvate oxidase, CidC, which generates acetate from direct decarboxylation of pyruvate. The coordinated function of Pta and LipL is required for infection of the skin, whereas the roles of Pta and LipL in systemic infection are separable (Fig 9). Moreover, we found that acetate production by Pta and CidC was required for S. aureus infection in both systemic and skin infections. Altogether, our data highlight a previously unidentified mechanism to regulate carbon flow by integrating the dynamic delivery of lipoic acid with metabolite shuttling. This work provides a compelling example of how metabolic adaptations that coordinate nutrient flux are beneficial for S. aureus survival in the host by allowing the bacterium to optimize its nutritional resources.

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Fig 9. Proposed model of tissue-specific LipL-mediated requirement for virulence.

(A) During skin and soft tissue infection, Pta and LipL activities coordinate metabolic flux through the Pta-AckA pathway. (B) During systemic infection, there is a dominant role for LipL-dependent lipoylation of BCODH that is vital for BCFA synthesis and S. aureus survival, which is distinct from roles for Pta in virulence. Figure Created in BioRender. Woods, R. (2026) https://BioRender.com/vbnk4gt.

https://doi.org/10.1371/journal.ppat.1014183.g009

In prior work, we found that the lipL open reading frame is positioned two nucleotides downstream of the pta gene in S. aureus, suggesting the two genes are co-regulated at the transcriptional and likely translational levels (Fig 1E) [26]. RNAseq and qRT-PCR data validated the presence of a single pta-lipL transcript (Fig 1E and 1F). This finding raised the question of the frequency with which lipL and pta genes coincide. In silico synteny analyses herein revealed that, within the Gram-positive pathogens assessed, some had lipL in close genetic proximity to pta (Fig 1B-1D). This phenomenon was not observed in representative Gram-negative pathogens, where, in most instances, ackA and pta are co-transcribed (Fig 1B). The evolutionary differences between the lipoic acid biosynthesis and salvage pathways of Gram-positive and Gram-negative bacteria offer some insight into these in silico results. The lipoic acid biosynthesis pathway in E. coli and other Gram-negatives consists of two enzymes, LipA and LipB [25,59,60]. The octanoyltranferase, LipB, attaches octanoic acid directly to E2 and H protein subunits, followed by sulfur insertion by LipA. Thus, lipoic acid is synthesized directly on each metabolic enzyme complex [25,59,60]. Notably, Gram-negatives do not encode amidotransferases such as LipL and thus do not perform lipoyl relay between E2 and H proteins [25]. On the other hand, Gram-positives harbor a more complex lipoic acid biosynthesis pathway that includes LipM, a transferase that delivers octanoic acid to the H protein of GcvH, the sole site of sulfur insertion by LipA [25,61,62]. The transfer of lipoic acid from GcvH to other enzyme complexes is mediated by LipL. Without LipL, complete transfer to E2 subunits does not occur [1,26,62]. Furthermore, the presence of LipL confers a dynamic flexibility that potentially allows for dynamic redistribution of lipoic acid based on the metabolic state of the cell [1,25,26,62]. The absence of LipL in Gram-negatives and direct synthesis on each enzyme complex precludes the regulatory advantages offered by a lipoyl relay pathway. These fundamental differences may explain why lipoic acid synthesis and carbon overflow pathways are only linked in Gram-positives. Indeed, the transcriptional coupling of pta and lipL in Staphylococci hinted at a direct coupling of lipoic acid transfer and acetate fermentation that was validated in this work.

Assays of acetate levels in Δpta and ΔlipL mutants revealed different degrees of impairment in acetate production, where a Δpta mutant produced more acetate over time compared to a ΔlipL mutant (Fig 2C and 2D). This is likely accounted for by the fact that a ΔlipL mutant also produces substantial lactate, suggesting that blockade upstream of PDH necessitates redirection of pyruvate through both lactate fermentation and CidC (Fig 2D). In support of this point, the ΔlipL mutant also had considerably higher pyruvate levels (Fig 6A). In addition to these observations that center on pyruvate accumulation, our RNA sequencing data also showed that loss of lipL led to a global change to the transcriptome including upregulation of genes involved in histidine catabolism (hut operon) and oxidative metabolism (qox operon) and downregulation of genes involved in branched-chain amino acid biosynthesis (leu and ilv operons) and purine biosynthesis (pur operon) (Fig 6D and 6E). The downregulation of genes involved in branched-chain amino acid biosynthesis was accompanied by the downregulation of bmfBB (encoding E2-BCODH), accA (a subunit of acetyl-CoA carboxylase), and bioY (biotin transporter) (6E). These results suggest that a ΔlipL mutation leads to reduced branched-chain fatty acid biosynthesis since bmfBB encodes the E2 subunit of the enzyme complex that generates the coA derivatives required for branched chain fatty acid synthesis, while acetyl-CoA carboxylase is required for fatty acid synthesis itself with the biotin transporter aiding in acquisition of biotin, an essential cofactor for this process [6365]. Conversely, upregulation of the hut operon suggests there is increased TCA cycle activity in a ΔlipL mutant because it is directly involved in the catabolism of histidine to glutamate, which is directly fed into the TCA cycle via gudB [45]. Indeed, gudB transcript levels were also elevated in a ΔlipL mutant relative to WT (Fig 6E). The shift toward a transcriptional profile that favors TCA cycle activity in a ΔlipL mutant is further supported by the fact that, of the lipoylated E2 subunits, only E2-OGDH maintains its lipoylation status in the absence of LipL (Fig 2B) [1,5,26]. The residual lipoylation of E2-OGDH is mediated by the S. aureus encoded lipoic acid ligases, LplA1 and LplA2 [1,66]. Furthermore, our RNAseq data showed increased sucA (encodes E1-OGDH) transcripts (Fig 6E), supporting the idea that TCA cycle activity is increased in a ΔlipL mutant (Fig 2B). A ΔlipL mutant also had increased expression of genes with roles in oxidative metabolism (Fig 6D) such as the qox operon, sdhC and ctaB (Fig 6E). The qox operon is involved in aerobic respiration, sdhC is a gene involved in both the TCA cycle and the electron transport chain, and ctaB produces the heme O cofactor required for QoxABCD terminal oxidase function [6771]. All together these data support the idea that LipL has a key role in precisely modulating S. aureus metabolic flux, favoring acetate fermentation while limiting the TCA cycle and oxidative metabolism.

Our RNAseq analysis also uncovered several other genes that were upregulated in a ΔlipL mutant. We observed a significant increase in cidC transcripts, which was corroborated by qRT-PCR (Fig 6E and 6F). These results validate work from others, which suggests that induction of cidC represents a compensatory strategy to overcome intracellular pyruvate accumulation [28,36]. CidC is encoded in an operon alongside genes encoding the holin, CidA, and a potential support protein, CidB [34,72]. Transcription of the cid operon is under the control of multiple promoters and transcriptional regulators [33,72,73]. During exponential phase growth, sigma factor B (σB) induces the expression of cidBC [72]. During stationary phase, the LysR-type transcriptional regulator CidR induces expression of cidABC [39,33]. CidR induction of cidABC is known to promote maintenance of biofilm structure, where the holin activity of CidA aids in promoting bacterial cell death [39]. To determine if σB or CidR-dependent transcriptional upregulation was occurring in a ΔlipL mutant, we assessed our RNAseq dataset for cidA or cidB transcripts. Intriguingly, we found that the baseMean values for cidC were 3231.85, compared to 611.48 for cidB and 161.65 for cidA, suggesting the cidC transcript was upregulated independent of cidA and cidB in this scenario. Furthermore, a read analysis of cidA, cidB, and cidC showed a markedly higher read density across cidC compared to cidA and cidB (S2B Fig). The elevated cidC signal, coupled with its higher baseMean value, suggests the possibility of an alternative transcriptional start site for cidC that is independent of cidAB. Future work will address this possibility.

Work from Sadykov et al. highlights the importance of Pta and AckA for S. aureus fitness and metabolism. They found that the metabolome of both a Δpta and a ΔackA mutant is marked by a redirection of carbon flux into glycolysis, TCA cycle, pentose phosphate pathway, and amino acid biosynthetic pathways [28]. Our lipoylation profile data support this redirection of metabolic flux toward glycolysis and TCA cycle, wherein we noted increased lipoylation of E2-PDH and E2-OGDH in the Δpta mutant (Fig 4D and 4E). Furthermore, we found that a Δpta mutant does not have a commensurate increase in pdhC, or sucB transcripts (S2A Fig), suggesting the increase in lipoylation on E2-PDH and E2-OGDH is due to a redirection of lipoic acid transfer by LipL. Sadykov et al. also found that the loss of pta causes a fitness defect in which there is a delay in exponential phase growth, which we reproduced herein (Fig 2A) [28]. Interestingly, an ackA mutant in S. aureus has a faster growth rate during exponential phase compared to a pta mutant [28]. These results suggest the coordinated activity of Pta and LipL in S. aureus, which occurs upstream of AckA activity, is more critical to overall fitness. Intriguingly, the reduced exponential phase growth rate of a Δpta mutant compared to a ΔackA mutant appears to be specific to S. aureus. Studies in other pathogens suggest a ΔackA mutant has a more severe effect on growth rate compared to a Δpta mutant, citing accumulation of acetyl-phosphate as the potential culprit [28,29,74,75]. This was the case for strains where ackA-pta were in an operon (E. coli), pta and lipL were in close genetic proximity but not linked (B. subtilis), and strains where pta and lipL were divergently transcribed (B. anthracis) [29,53,76]; thus, it is difficult to draw conclusions on the basis of these observations from gene positioning alone. Nevertheless, these prior studies coupled with our in-silico analysis (Fig 1B1D) suggest that Staphylococci have adapted in ways that allow coordination of Pta and LipL activity to maintain fine-tuned control over metabolic flux through pathways that are critical for fitness.

Functional and computational studies suggest that metabolic flux is enhanced through improved channeling of substrates from one enzyme to another via protein complex formation and protein-protein interactions [1315,77]. We used AlphaFold to predict the likelihood of a direct interaction between Pta and LipL and confirmed this model with in vitro and in vivo evidence (Fig 4). These studies suggest, at minimum, Pta and LipL may interact to drive metabolism in the direction of Pta-AckA. In these experiments, Pta and LipL had components of adenylate cyclase or 6x-his epitope tags appended to the C-terminus of each protein. Efforts to append CyaA fragments or epitope tags to the N-terminus prevented detection of an interaction between Pta and LipL (S2C Fig). Prior structural analysis of Pta in Gram-negative and positive organisms revealed that the protein contains two functional domains separated by an interdomain cleft, which is vital for the binding of acetyl-phosphate [7880]. Crystal structures of Pta in Gram-positive organisms such as B. subtilis and S. pyogenes revealed that the N-terminus of Pta is a component of this interdomain cleft and may provide a potential reason why the N-terminus of Pta is not a productive site for epitope tags, as it is required for binding of substrates and presence in the interdomain cleft may preclude attachment of even small tags [78,80,81]. Future studies in our lab aim to identify specific residues critical for the Pta–LipL interaction and to test their impact on metabolite flux.

Additionally, previous biochemical assessments of Pta in Gram-negatives such as E. coli and Salmonella enterica Typhimurium found that the N-terminus of Pta serves a regulatory role through the allosteric binding of cofactors and substrates, such as NADH and pyruvate [82,83], whereas biochemical studies in Gram-positives reveal Pta activity is not altered by allosteric effectors [81]. Our inability to generate epitope tags of Pta or LipL that maintain protein-protein interaction characteristics suggests that the N-terminus of S. aureus Pta is, at minimum, important for interactions (S2C Fig). The increase in LipL-dependent lipoylation of E2-PDH and E2-OGDH in the absence of Pta could imply that LipL increases delivery of lipoic acid to E2 subunits due to increased metabolic demand or that Pta negatively impacts LipL function (Figs 2B, 4E4D, and 7B). It is also possible that LipL improves Pta function. Future biochemical experiments will directly examine these possibilities [8486]. Furthermore, our bacterial two-hybrid assays also detected evidence for an interaction between Pta and E2-PDH (S2C Fig); however, Alphafold modeling of the interaction had low predictive values (PTM of 0.47 and iPTM of 0.2) (S1D Fig). Nevertheless, the bacterial two-hybrid results may support the possibility of a larger complex between Pta, LipL, and PDH that improves substrate delivery. Additional evidence in support of this idea includes a protein interaction network analysis in S. aureus that identified an interaction between Pta and E2-PDH [87]. Further assessment of a potential Pta-LipL-PDH complex is warranted. We are currently pursuing these areas of investigation.

In a systemic infection model, the roles of Pta and LipL in virulence are separable (Fig 5A). While Pta contributes to infection in the kidney, the attenuation of ΔlipL and Δpta ΔlipL mutants is far more dramatic, with the ΔlipL mutant and Δpta ΔlipL mutants phenocopying each other (Fig 5A). LipL is known to transfer lipoic acid to enzyme complexes that extend beyond overflow metabolism pathways and include enzymes that facilitate branched-chain fatty acid synthesis (BCODH) and TCA cycle activity (OGDH). In prior work, we noted a strong dependency on branched-chain fatty acid synthesis during systemic infection that is bypassed in the skin via uptake of host unsaturated fatty acids [5]. Thus, the contribution of LipL to infection in the kidney is largely driven by deficiencies in branched-chain fatty acid synthesis, whereas Pta contributes to a lesser degree (Fig 5A). This conclusion is further supported by the finding that constitutive expression of lipL, but not pta, in a Δpta ΔlipL mutant background nearly restores full virulence in the kidneys (Fig 5A). In contrast, Δpta, ΔlipL, and Δpta ΔlipL strains phenocopy one another (Fig 5B) for infection defects in the skin, implying a direct role for flux through PDH and toward Pta-AckA in skin infection. In agreement with this idea, complementation with either pta or lipL alone fails to restore full virulence in the skin (Fig 5B). These results further cement the importance of regulating acetate production during S. aureus skin infection (Fig 9).

Several studies have considered the roles of S. aureus acetate production genes during infection. One study found that infection with a ΔackA mutant had reduced lesion area during skin infection of hyperglycemic mice [40]. Another study assessed a ΔcidC mutant in a rabbit model of infective endocarditis and found no difference between the ΔcidC mutant and WT at the primary site of the vegetation [36]. Instead, the authors found that a ΔcidC mutant had significantly fewer CFUs in secondary sites of infection, leading them to suggest CidC may play a role in dispersal from biofilms in the host [36]. Here, we find that a requirement of acetate production is not contingent on a high glycemic status (mice are on standard chow). Furthermore, our ΔcidC mutant infection data suggest that during planktonic growth, CidC alone is not required for infection. However, infection with a Δpta ΔcidC strain leads to dramatic attenuation compared to either single deletion, implying compensatory demand for acetate production in vivo (Fig 8B). Altogether, this infection data highlights the critical importance of acetate-producing genes in several models of infection.

Recent work from Thurlow et al. determined that glycolytic flux enhances activity of the accessory gene regulatory (Agr) system [40]. Agr is a two-component system (TCS) that responds to changes in bacterial cell density and is a master regulator of virulence factors, controlling the expression of leukotoxins, hemolysins, lipases, and proteases [8890]. Agr-dependent toxin production by S. aureus requires ATP production from processes such as overflow metabolism through Pta-AckA [40]. The requirement of glycolysis to enhance Agr-dependent gene expression is accounted for by a reduced affinity of AgrC, the sensor histidine kinase of the Agr system, for ATP [40,91,92]. Thus, ATP must be high for maximal production of Agr-dependent virulence factors in S. aureus. We found that a ΔlipL mutant increases oxidative metabolism to maintain energy production when flux through the PDH node is blocked (Fig 6E6F). RNAseq analysis further revealed increased expression of Agr-regulated virulence genes in the ΔlipL mutant (Fig 6E6F). Although not yet directly tested, these findings raise the possibility that ATP generated through oxidative metabolism might also promote Agr-dependent virulence factor production. Regardless, these studies further support the idea that the metabolic status of S. aureus, as defined by the nutritional environment, can have direct impacts on pathogenic potential.

The innate immune system serves as the body’s first line of defense against bacterial infections, with macrophages and neutrophils acting as key early responders that initiate the host immune response. Our data demonstrates that the loss of acetate production is detrimental for S. aureus survival in the host (Fig 8), suggesting that acetate might play a role in modulating the host response to infection. Given this, we suspect that S. aureus-derived acetate might alter the function of innate immune cells. Indeed, acetate is a ligand for the G-protein-coupled receptors FFAR2 and FFAR3, which are present on the surface of macrophages and neutrophils [9396]. FFAR2 primes innate immune cells, facilitating productive immune responses during bloodstream, gastrointestinal, and pulmonary infections caused by both Gram-negative and Gram-positive pathogens [97100]. More recent work from Xu et al showed that acetate and formate produced by S. pyogenes inhibited innate immune cell accumulation and cytokine production, which delayed host wound healing and bacterial clearance during soft tissue infections [101]. Thus, a paradox emerges in which acetate can either enhance or suppress the innate immune response. Given the importance of Pta and CidC for S. aureus infection (Fig 8), our data may imply a role for acetate in dampening the innate immune response. Ongoing work aims to study the potential impact of acetate on innate immune cells during S. aureus infections.

Collectively, this work supports the idea that S. aureus coordinates metabolic flux through transcriptional and post-transcriptional mechanisms to promote adaptation and survival during infection. These findings have implications for our understanding of coordinated enzyme complex assembly that drives the delivery of key metabolites to their targets and argue for a potential direct role for acetate production in bacterial virulence. Further, it highlights the importance of tissue-specific dependencies on major metabolic processes for virulence, which supports a critical examination of pathogenesis using several infection models.

Methods

Ethics statement

All animal experiments were conducted in ABSL2 facilities under Institutional Animal Care and Use Committee (IACUC)-approved protocols from the University of Illinois Chicago (Protocol #25–042) and Loyola University Chicago Health Sciences Division (Protocol #2020025), in accordance with United States Department of Agriculture (USDA), Public Health Service (PHS), and Office of Laboratory Animal Welfare (OLAW) guidelines. The University of Illinois Chicago holds a current PHS Animal Assurance (#A3460-01, through 04/30/2027), is Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) accredited (#000186, 04/01/2024), and USDA licensed (#33-R-0018). Loyola University Chicago holds a current PHS Animal Assurance (#A3460-01, through 02/28/2026), is AAALAC-accredited (#000180, 11/18/2022), and USDA-licensed (#33-R-0024). All procedures complied with institutional ethical standards.

Phylogenetic tree construction and synteny analysis

The pta coding sequence was used in independent searches of the Seed analysis viewer (https://pubseed.theseed.org/FIG/seedviewer.cgi?page=Minimal) [102,103]. The pta gene in Staphylococcus aureus subsp. aureus USA300 used for search was taxon ID 367830; feature ID fig|367830.3.peg.650) and is annotated as phosphate acetyltransferase (EC 2.3.1.8). All genomes were compared by a standard search of the Seed database. The genomes of M. tuberculosis and selected Gram-positive and Gram-negative bacteria representing the most frequent genetic organizations of pta, lipL, and ackA were then chosen for subsequent analysis. Taxonomic assignments for these genomes were confirmed in NCBI (TaxIDs: 242231, 604162, 99287, 575584, 1051003, 272620, 83333, 196600, 187410, 451515, 224308, 1027396, 160490, 1773, 226185, 416870, 373153, 191218, 1385523, 1242971, 1155131, 904338, 1189311, 435837, 1134914, 342451). Phylogenetic trees were constructed using the selected genomes in PhyloTv2 (https://phylot.biobyte.de) and visualized using the interactive Tree of Life tool, iTOLv7 (https://itol.embl.de) [104].

Bacterial strains and growth conditions

The strains used in this study are described in S1 Table. Escherichia coli strains were grown in Lysogeny Broth (LB) (BD Biosciences), and S. aureus strains were grown in Tryptic Soy Broth (TSB) (BD Biosciences). For experiments with no or low glucose (3.5 mM), S. aureus strains were growin in TSB without dextrose (BD Biosciences) with or without D-glucose supplementation (Amresco). Unless stipulated, strains were grown at 37°C, shaking at 200 RPM. For strains harboring a ΔlipL mutation, branched-chain carboxylic acids (BCCAs) (10 mM isobutyric acid [Sigma-Aldrich], 9 mM 2-methylbutyric acid [Alfa Aesar], 9 mM isovaleric acid [Sigma-Aldrich]) and 10 mM sodium acetate (NaAc; Sigma-Aldrich) were added to the media to promote growth [23,61]. When needed, media were supplemented with the following agents of selection: ampicillin (100 µg/ml), chloramphenicol (10 µg/ml), kanamycin (50 µg/ml), cadmium chloride (0.1 mM), anhydrous tetracycline (1 μg/ml) (AnTet), and sodium citrate (10 mM).

Generation of in-frame deletion mutants

Oligonucleotide pairs (S2 Table) were designed to amplify fragments of ~500–1000 nucleotides upstream and downstream of the targeted genes for mutagenesis using S. aureus LAC genomic DNA as a template. Purified amplicons were then used as templates in a splicing by overlap extension (SOE) PCR to yield the final 1,000–2,000 bp amplicon containing a fusion of the upstream and downstream gene fragments. Each amplicon was digested with KpnI and SacI restriction endonucleases and ligated into the multiple cloning site (MCS) of pIMAY using T4 DNA ligase [105]. Ligation reactions were transformed into E. coli IM08B [46], and transformants containing the ligated amplicon were verified by PCR. Plasmids were purified from IM08B and subsequently transformed into S. aureus competent cells by electroporation (1800 V, 10 μF, 600 Ω, 2 mm cuvette). Mutagenesis was performed as previously described [47]. Briefly, S. aureus cells containing pIMAY plasmids were grown at 30°C to allow for plasmid replication. Plasmid recombination into the chromosome was induced at 37°C with selection on chloramphenicol. To facilitate plasmid excision, cells were returned to the permissive temperature for plasmid replication (30°C) and passaged without antibiotic to promote plasmid loss. Bacteria were then plated on TSA plates supplemented with AnTet and incubated at 30°C to counter-select for cells that still contain the pIMAY plasmid. Chloramphenicol sensitive and AnTet-resistant colonies were screened for the desired mutation by PCR.

Generation of complement strains and phage transduction

Complementation strains were generated using the pJC1111 plasmid [48]. Genes for complementation were amplified from S. aureus genomic DNA using the primer pairs listed in S2 Table, while the constitutive PHELP promoter was amplified from the pIMAY plasmid as template [47]. Purified amplicons were fused by SOE PCR and subsequently cloned into the MCS of pJC1111 using Sac1 and Sal1 restriction endonucleases for digestion and T4 DNA ligase for ligation. The recombinant plasmids were propagated in E. coli DH5α and transformed into SaPI-1 integrase-expressing S. aureus (RN9011) to allow single-copy integration in the chromosome at the SaPI-1 site [48]. Bacteriophage Φ11 was used to package the integrated complementation plasmids from RN9011, and the phage was used for transduction of genetic material into the recipient strain of interest, as previously described [106]. Briefly, a single colony of the RN9011 donor strain was grown overnight at 37°C with shaking. The overnight culture was diluted to an OD600 of 0.2 in TSB. 5 mL of diluted culture was added to 5 mL of TMG buffer (10 mM Tris pH 7.5, 5 mM MgCl2, 0.01% gelatin (v/v), 5 mM CaCl2) in a 15 mL conical tube containing 100 μL of Φ11 phage and incubated at room temperature overnight until lysis was complete. The following day, 100 μL of the filter sterilized phage lysate was added to an overnight culture of the recipient strain and incubated at 37°C with shaking for 20 minutes. The infected recipient was washed three times with 1 mL of 40 mM sodium citrate and then plated on TSA supplemented with 0.1 mM cadmium chloride and 40 mM sodium citrate to select for transductants. All transductants were confirmed by PCR.

Generation of Δagr Δpta ΔcidC strain

A marked Δagr::tet mutation was transduced into a Δpta ΔcidC mutant strain, as described above, to generate the Δagr::tet Δpta ΔcidC mutant strain. The Δagr::tet mutation spans the agr operon [58].

Generation of 6x-Histidine tagged Pta and LipL expression plasmids

The pta and lipL genes were amplified from S. aureus LAC genomic DNA using the primer pairs in S2 Table. The resulting amplicons were cloned into the pET21a (Novagen) expression vector using Nde1 and Sal1 restriction endonucleases for digestion and T4 DNA ligase for ligation. The resulting plasmids were transformed into chemically competent E. coli DH5α. Plasmids were purified from DH5α and transformed into chemically competent E. coli lysY/Iq (NEB). All recombinant expression plasmids were verified by whole plasmid sequencing (Plasmidsaurus).

Purification of 6x-Histidine-tagged proteins

To purify Pta-6xHis and LipL-6xHis, a single colony of E. coli lysY/Iq containing pET21a-pta-6xHis or pET21a-lipL-6xHis was used to start an overnight culture in 20 mL of LB at 37°C with shaking at 200 RPM. The bacteria were diluted (1:100) in 1 L of fresh LB and incubated at 37°C with shaking at 200 RPM until reaching an OD600 of ~0.3. Protein expression was induced by supplementing the culture with IPTG (0.1 mM) and incubating at 37°C for 3 hours with shaking at 200 RPM. Following induction, bacteria were collected by centrifugation at 10000 RPM for 20 min, and pellets were stored at -80°C until use. Frozen bacterial pellets were thawed and resuspended in 60 mL lysis buffer (25 mM imidazole, 50 mM Tris-HCl, 300 mM NaCl, 1 mM phenylmethylsulfonyl fluoride (PMSF), pH 8). The bacterial suspensions were sonicated on an ice bath for 10 minutes with intervals of 10 s ON and 50 s OFF at an amplitude of 340 W using a Branson 550 Sonicator. Cell debris was removed by centrifugation at 15000 RPM for 30 min, and the lysate was collected and passed through a 0.22 µm syringe filter. The clarified lysates were then mixed with 1 ml of nickel-NTA resin (Qiagen), preequilibrated with lysis buffer, and incubated on a rotisserie overnight a 4°C. After incubation, the mixture was poured into a glass gravity flow chromatography column (Bio-Rad), and the resin was washed with 50 mL of lysis buffer, followed by elution of the bound protein with 6 ml elution buffer (500 mM imidazole, 50 mM Tris-HCl, 300 mM NaCl, pH 8). Purified proteins were dialyzed at 4°C in 10-kDa molecular weight cutoff (MWCO) dialysis cassettes (Thermo Scientific). Dialysis conditions were as follows: 1 L buffer 1 (100 mM imidazole, 50 mM Tris-HCl, 300 mM NaCl, pH 8) for 3 hours, 1 L buffer 2 (25 mM imidazole, 50 mM Tris-HCl, 300 mM NaCl, pH 8) for 3 hours, 1 L buffer 3 (50 mM Tris-HCl, 300 mM NaCl, pH 8) overnight, and 1 L buffer 4 (50 mM Tris-HCl, 300 mM NaCl, pH 8) for 3 hours. Protein concentration was measured using a bicinchoninic acid (BCA) kit (Thermo Scientific). Protein purity was confirmed by resolving the purified proteins using sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), followed by staining gels with Coomassie blue. Purified proteins were stored in aliquots at -80°C until use.

RNA purification

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. The following day, 250 μL of overnight culture was added to 25 mL of TSB + BCCAs in a 250 mL flask. Flasks were placed at 37°C with shaking at 200 RPM. For RNA sequencing, cultures were grown to late exponential phase (OD600 = 0.6) and for qPCR, strains were grown for 6 hours. 10 mL of each culture was removed and subsequently normalized to the OD600 of the strain with the lowest turbidity to ensure equivalent biomass. Cultures were centrifuged at 11000 RPM and washed twice with 15 mL PBS. Cell pellets were fixed in 15 mL of a 1:1 ethanol: acetone solution and stored at -80°C until RNA extraction. RNA was subsequently purified using a RNeasy Micro kit (Qiagen) with an additional DNase digestion using Turbo DNase (Thermo). Briefly, bacterial pellets were thawed on ice and centrifuged for 15 minutes at 4000 RPM at 4°C to remove the ethanol:acetone solution. The pellet was air-dried and was washed twice with 500 μL of 1x PBS, followed by suspension of the washed pellet in 500 μL RLT buffer containing 10 μL/mL of β-mercaptoethanol. Suspensions were transferred to RNase-free Lysing Matrix B tubes (MP Biomedicals). Tubes were placed in a Fast Prep-24 5G (MP Biomedicals) bead disruption system, followed by two sequential cell lysis steps at 5.0 speed for 20 s and 4.5 speed for 20 s. Samples were kept on ice for 5 minutes between the two lysis steps. After lysis, samples were centrifuged at 10000 RPM for 20 min, and the supernatant was removed. 500 μL of RLT buffer was added to supernatants and the samples were vortexed, followed by addition of 500 μL of 100% ethanol to precipitate the RNA, followed by addition to a Qiagen RNeasy spin column. All remaining steps were performed according to the manufacturer’s protocol. The RNA was eluted in 40 μL of DEPC-treated water. A second DNase digestion was conducted using 1 U Turbo DNase in solution (Invitrogen). The RNA was precipitated with 100% ethanol, added to an RNeasy spin column, washed 3 times in 450 μL wash buffer, and eluted in 50 μL of DEPC-treated water. The purified RNA was quantified via Nanodrop and RNA quality was assessed either by resolving the RNA on a 1.2% agarose/formaldehyde gel or by tape station analysis. RNA was stored at -80°C until cDNA synthesis or RNA sequencing.

qRT-PCR and RNA sequencing

For qRT-PCR, cDNA was first synthesized from 5 ng of purified RNA using the GoScript reverse transcription system following the manufacturer’s protocol (Promega). Gene expression was assessed using SYBR Green (Bio-Rad) with the primer pairs listed in S2 Table on a QuantStudio 5 real-time PCR system. Fold change relative to housekeeping genes (gyrB or sigA) was calculated using the threshold cycle (2 − ΔΔCT) method. RNA sequencing was completed by SeqCoast Genomics LLC. Briefly, samples were prepared for RNA sequencing using an Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus Microbiome and IDT For Illumina Unique Dual Indexes. Sequencing was performed on the Illumina NextSeq2000 platform using a 300-cycle flow cell kit to produce 2 x 150 bp paired reads. Read demultiplexing, read trimming, and run analytics were performed using DRAGEN v4.2.7, an on-board analysis software on the NextSeq2000. The quality of the sequencing data was first assessed using FastQC v0.12.0. Next, all reads were trimmed and quality filtered using BBDuk v39.33 employing Illumina’s adapters and the program’s default settings. To remove any potential contaminating reads, the data were subjected to another round of quality processing. This was performed by splitting the reads and removing the contaminating reads, using BBSplit v39.33 and the reference genome of S. aureus subsp. aureus LAC. Due to the lower support of S. aureus subsp. aureus LAC reference genome (NC_007793) in the downstream analysis tools and databases, the processed reads were instead aligned to the reference genome of S. aureus subsp. aureus TCH1516 using Bowtie 2 v2.5.4. SAMtools v1.22.1 were then employed to convert the output files of Bowtie 2, followed by the counting of the mapped reads to the genomic features using featureCounts (from the Subread package, v2.1.1). Finally, differential expression analysis was conducted employing DESeq2 (version 1.40.2). Specifically, count matrices and sample metadata were imported with the DESeqDataSetFromMatrix function and normalized using DESeq2’s median-of-ratios method. Afterwards, gene-wise dispersions were estimated, and a negative-binomial generalized linear model was fit to the counts using a design formula that included the condition factor. Statistical significance of coefficients was assessed using Wald test, and resulting p-values were adjusted for multiple testing by the Benjamini–Hochberg procedure to control the false discovery rate. Log2-fold changes were reported after effect-size shrinkage using the apeglm method, which provides a more stable and interpretable log-fold change estimate for ranking and visualization. Genes with adjusted p-value ≤ 0.05 were considered differentially expressed and consequently further analyzed. The data obtained from the differential expression analysis were further processed employing Pathview v1.48.0 for mapping and rendering the differentially expressed genes on relevant pathway graphs, clusterProfiler v4.16.0 for gene set enrichment analysis, and the individual genes manually parsed using Microsoft Excel (v2505). Normalized and mapped reads were visualized in Integrative Genomics Viewer (IGV).

Pathway analysis

Functional pathway enrichment was carried out using approaches similar to those described in a prior study [107]. In summary, the set of differentially expressed genes was assigned to biological pathways using the free Database for Annotation, Visualization and Integrated Discovery (DAVID) provided by NIAID/NIH [108,109]. Gene identifiers were converted to NCTC8325 locus tags in the SAOUHSC ortholog format with the help of AureoWiki, an online resource for S. aureus. The DAVID analysis returned unbiased functional annotations, suggested pathway groupings, and the number of genes associated with each pathway.

Growth curves

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. Strains containing a ΔlipL mutation were grown with complete BCCAs overnight. The next day, strains were washed three times with 5 mL 1 x PBS and subcultured 1:100 (2 μL into 198 μL fresh TSB) in a flat-bottom 96-well plate (Costar) in technical triplicate. Strains were grown in TSB + BCCAs without the addition of sodium acetate. The plate was incubated in a Tecan Spark plate reader at 37°C with orbital shaking at 3 mm with a frequency of 180 RPM. Bacterial growth was monitored by measuring OD600 every hour for 24 hours.

Metabolite quantification

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. The following day, 250 μL of overnight culture was added to 25 mL of TSB + BCCAs without sodium acetate in a 250 mL flask. Flasks were placed at 37°C with shaking at 200 RPM. For glucose, lactate, and formate measurements, 120 μL of culture was removed every hour for six hours. For acetate measurements, 60 μL of culture was collected every three hours for 12 hours, with a final collection at 24 hours. Samples were collected in 1.5 mL Eppendorf tubes at each time point and were centrifuged at 13000 RPM for 5 minutes. The cellfree supernatant was stored at -20°C until assaying metabolite levels. Acetate, glucose, formate, and D- and L-lactate concentrations were determined using kits purchased from R-Biopharm, according to the manufacturer’s protocol with minor changes. Briefly, for all metabolites, 10 μL of each sample was incubated with 200 μL of reagent 1 for 3 minutes at room temperature in a flat-bottom 96-well plate (Costar) in technical triplicate. Following the primary incubation, 50 μL of reagent 2 was added to the reaction mixture and incubated for 15 minutes. A Tecan Spark plate reader was used to read the absorbance at 340 nm for each metabolite. Final calculations of metabolite concentrations were determined using a standard curve.

Intracellular pyruvate quantification

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. The following day, 250 μL of overnight culture was added to 25 mL of TSB + BCCAs without sodium acetate in a 250 mL flask and placed at 37°C with shaking at 200 RPM. At 3 hours, cultures were normalized to the lowest optical density and 1 mL of normalized culture was added to 1.5 mL Eppendorf tubes, centrifuged at 10,000 RPM for two minutes, and washed twice with 1 mL 1x PBS. The bacterial suspension was mixed with pyruvate assay buffer from a commercial Pyruvate Assay Kit (Abcam) and transferred to screw cap microcentrifuge tubes (Fisher Scientific), which were preloaded with 250 µL of 0.1 mm glass beads (Electron Microscopy Sciences). Tubes were placed in a Fast Prep-24 5G (MP Biomedicals) bead disruption system, followed by two sequential cell lysis steps at 5.0 speed for 20 s and 4.5 speed for 20 s. Samples were kept on ice for 5 minutes between the two lysis steps. After lysis, samples were centrifuged at 10000 RPM for 20 min, and 150 µL of the supernatant was collected and assayed according to the manufacturer’s protocol.

Determination of protein lipoylation and densitometry

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. Overnight cultures were diluted 1:100 in 10 mL fresh TSB in 50 mL conical tubes and incubated for 9 hours at 37°C with shaking at 200 RPM. Bacteria were centrifuged at 8000 RPM for 10 minutes, supernatants were removed, and cell pellets were resuspended in 1 mL 1x PBS. Bacterial suspensions were transferred to screw cap microcentrifuge tubes (Fisher Scientific), which were preloaded with 250 µL of 0.1 mm glass beads (Electron Microscopy Sciences). Tubes were placed in a Fast Prep-24 5G (MP Biomedicals) bead disruption system, followed by two sequential cell lysis steps at 5.0 speed for 20 s and at 4.5 speed for 20 s. Samples were kept on ice for 5 minutes between the two lysis steps. After lysis, samples were centrifuged at 11,000 RPM for 20 minutes, and 150 µL of the supernatant was collected in 1.5 mL centrifuge tubes containing 50 µL of 4X SDS sample buffer (0.2 M Tri-HCl, pH 6.8, 8% SDS, 5.5 M glycerol, 0.02 M EDTA, 0.6 M β-mercaptoethanol, and 6 mM Bromophenol blue). Samples were boiled for 10 minutes and stored at -20°C. Thawed cell lysates were loaded onto 15% polyacrylamide gels after normalizing to the original OD600 of the culture, followed by SDS-PAGE at 100 V for 2 hours. Resolved proteins were either stained with Coomassie blue or were transferred to 0.2 μm Immobilon polyvinylidene difluoride (PVDF) membranes (Millipore Sigma) at 20 V for 90 min. After transfer, membranes were incubated for 1 hour in Tris-buffered saline + 0.1% TWEEN 20 (Amresco) (TBST) supplemented with 5% bovine serum albumin (BSA) (GoldBio) and human IgG (Sigma) (1:2,000). Rabbit polyclonal α-lipoic acid antibody (Calbiochem) was added to the membranes at a 1:7,500 dilution followed by incubation overnight at 4°C. The following day, the membrane was washed three times for 10 minutes each in ∼20 mL of TBST. Alkaline phosphatase (AP)-conjugated goat anti-rabbit IgG (H + L) (Invitrogen) was then added at a 1:5000 dilution in 5% BSA in TBST for 1 hour followed by three 10 minutes washes in ∼20 mL of TBST. Membranes were developed with 5-bromo-4-chloro-3-indoyl-phosphate/nitro blue tetrazolium color development substrate (GoldBio). Densitometry analysis was performed using the ImageJ software on four independent experiments to determine the lipoylation of each band relative to the control band set at a value of 1.

Bacterial Adenylate Cyclase Two-Hybrid (BACTH) system

S. aureus pta and lipL genes were amplified (S2 Table) and cloned into plasmids pKT25 and pUT18c to generate translational fusions with the T25 or T18 domains of the Bordetella pertussis adenylate cyclase [51]. To clone the lipL gene into BACTH vectors, Sma1 and Pst1 restriction endonucleases were used for digestion and T4 DNA ligase for ligation. To clone the pta gene into BACTH vectors, Sma1 and Xba1 restriction endonucleases were used for digestion and T4 DNA ligase for ligation. The resulting plasmids were transformed into E. coli DH5α and plated on LB agar containing kanamycin (50 μg/mL) or ampicillin (100 μg/mL). Transformants containing the ligated amplicon were verified by PCR. The recombinant plasmids were purified from DH5α E. coli and then co-transformed into E. coli strain BTH101 and plated on LB agar containing both kanamycin (50 μg/mL) and ampicillin (100 μg/mL). To assay for protein-protein interactions, single colonies were inoculated into 3 mL LB in 15 mL conical tubes containing both antibiotics overnight. The following day, strains were diluted 1:100 and grown for 6 hours at 30°C with shaking at 200 RPM. Upon reaching late-exponential phase (~6 hours), 10 μL culture was spotted on LB agar containing IPTG (0.5 mM), ampicillin (100 μg/mL), kanamycin (50 μg/mL), and X-Gal (100 μg/mL). Plates were incubated for 24 hours at 30°C to allow for bacterial growth. An interaction was defined by the presence of blue color relative to positive and negative controls. The negative control, empty BACTH plasmids, yield colorless colonies. The positive control was BTH101 co-transformed with pKT25-zip and pUT18C-zip, plasmids expressing leucine zipper - adenylate cyclase fusions that dimerize to yield blue colonies.

β-galactosidase activity was quantified based on previous methods [110]. Briefly, single colonies were inoculated in 3 mL LB in 15 mL conical tubes containing both antibiotics overnight. The next day, the cultures were diluted 1:100 in 3 mL LB and grown for 6 hours with IPTG (0.5 mM), ampicillin (100 μg/mL) and kanamycin (50 μg/mL) with shaking at 200 RPM at 30°C until reaching an OD600 ~ 1.0. Strains were OD normalized and 100 μL of each sample was added to a 96-well plate (Costar) in triplicate. The cultures were centrifuged at 4000 RPM, and the bacterial pellets were resuspended in 80 μL of Z-buffer (60 mM Na₂HPO₄·7H₂O, 40 mM NaH₂PO₄·H₂O, 10 mM KCl, 1 mM MgSO₄, 50 mM β-mercaptoethanol, pH 7). The resuspended cells were then permeabilized with 10 μL of 0.1% SDS and 10 μL of chloroform. Plates were centrifuged at 4000 RPM, the supernatant was transferred to a new 96-well plate, mixed with 20 μL ONPG (4 mg/mL), and the reaction was allowed to proceed for 15–30 min. Reactions were stopped by adding 30 μL 1 M Na2CO3 and absorbance was measured at 420 nm. The negative control, BTH101 carrying the empty pKT25 and pUT18c plasmids, and the positive control, BTH101 containing pKT25-zip and pUT18c-zip plasmids, are described above. β-galactosidase activity is reflected relative to the negative and positive controls, with the negative control assigned an activity value of 0 in arbitrary units and positive control assigned an activity of 1000 arbitrary units.

Microscale Thermophoresis (MST)

Experiments were performed as described previously with minor modifications [111]. Briefly, pure recombinant Pta was labeled with a NanoTemper 2nd Generation Red N-hydroxysuccinimide (NHS) Dye (Nanotemper Technologies). For protein labeling, Pta was first buffer exchanged into buffer M (20 mM MES, 100 mM NaCl, 10% glycerol, pH 7.5) to remove incompatible buffer components. 10 µM Pta was mixed with 3X excess of the Red NHS dye (300 µM) and incubated in the dark for 30 minutes for the dye to react with the protein. The protein-dye mixture was passed through a gel filtration column (Column B, Nanotemper Technologies) to remove unreacted and excess dye. For a 1:1 protein-dye conjugate, the degree of label (DOL) of the protein was determined using the formula: A650/195,000/M/cm × concentration of labeled protein. A650; absorbance at 650 nm, and 195,000/M/cm is the molar absorbance of the Red NHS dye. A 1:1 protein dye ratio occurred at a DOL value between 0.6 and 1. After labeling, protein samples were aliquoted into 10µL volumes, flash frozen using liquid nitrogen, and stored at -80oC until used. For microscale thermophoresis experiments, the unlabeled protein partner was serially diluted in low-binding tubes with buffer M supplemented with 1 mM BME and 0.05% Tween 20, pH 7.5, and titrated against 20 nM of the labeled proteins. The protein mixtures were loaded into standard Monolith NT.115 capillary tubes, and thermophoresis was determined using the following parameters: 20% excitation power and high MST Power at 25°C.

Thermophoresis results were analyzed using the PALMIST [112] and GUSSI [112] analysis pipeline. Briefly, data from the MST software (Mo. Control v1.6.1) were imported into the PALMIST software and a preset T-jump (TJ) was applied to the data using a 1:1 binding model with a 95% confidence interval. Datasets were examined for kinetic effects to ensure that thermophoresis achieved equilibrium. After data analysis, GUSSI was used for figure rendering. The top panel in Fig 4B indicates the normalized fluorescence data points, the middle panel represents the binding curve, and the lower panel represents the residuals (a plot between the fitted line and the data). Error bars indicate the standard deviation of four independent replicates.

Murine infection models

S. aureus strains were struck onto fresh TSA plates and incubated overnight at 37°C with shaking at 200 RPM. The next day, a single colony from the plate was inoculated into 3 mL of TSB in a 15 mL conical tube and incubated overnight at 37°C with shaking at 200 RPM. The overnight cultures were diluted 1:100 in 3 mL fresh TSB and grown for 3 h at 37°C with shaking at 200 RPM. Bacteria were pelleted by centrifugation at 3900 RPM at 4°C for 5 minutes. The cells were washed three times with 5 mL of 1X PBS. Bacterial cell suspensions were normalized to an OD600 of ~0.32 (~1 × 108 CFU/mL), and serial dilutions were plated onto TSA plates to enumerate CFU and ensure accuracy of inocula. Six-week-old female Swiss Webster mice (Envigo) were anesthetized with ketamine/xylazine (100/10 mg/kg) via intraperitoneal injection. For systemic infections, 100 μL of OD-normalized S. aureus in PBS (~1.0 × 107 CFU) was injected directly into the bloodstream via the retro-orbital sinus. Mice were monitored daily. At 96 h postinfection, mice were euthanized, and the kidneys were recovered, homogenized, serially diluted, dilutions were plated onto tryptic soy agar followed by incubation at 37°C overnight to enumerate CFU. For skin infections, bacterial suspensions (~1.0 × 107 CFU) were injected intradermally into anesthetized mice on each side of a shaved flank region. Mice were monitored daily. At 72 h postinfection, mice were euthanized, and abscesses were excised, homogenized, and plated to enumerate CFU.

Statistical analysis

For in vitro growth assays, western blots, and metabolite quantifications, data shown are representative of at least three independent experiments conducted in triplicate. qRT-PCR experiments included two independent biological replicates conducted in technical triplicate with all data shown. All animal studies include combined data from at least two independent experiments. Statistical analyses were conducted using GraphPad Prism version 10. Comparisons among three or more groups were conducted using either one-way ANOVA followed by Tukey’s post hoc test or Kruskal–Wallis test followed by Dunn’s post-test, whereas differences between two groups were analyzed with the Mann–Whitney test. A p-value below 0.05 was considered statistically significant. Statistical significance is indicated as follows: *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001.

Supporting information

S1 Fig. Growth of WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL strains in TSB and TSB + BCCAs [10 mM isobutyric acid (IB), 9 mM 2-methylbutyric acid (2MB), 9 mM isovaleric acid (IV) + 10 mM sodium acetate (NaAc)] containing 0 mM glucose (A) or 3.5 mM glucose (B).

(C) Quantification of glucose, acetate, lactate and formate from WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL culture supernatants over time in TSB with 0 mM glucose. (D) Quantification of glucose, acetate, lactate and formate from WT, Δpta, ΔlipL, Δpta + pta, and ΔlipL + lipL culture supernatants over time in TSB with 3.5 mM glucose. Each metabolite quantification assay is representative of three independent experiments, with each timepoint measured in technical triplicate. Errors bars indicate standard deviation from the mean.

https://doi.org/10.1371/journal.ppat.1014183.s001

(TIF)

S2 Fig. (A) qRT-PCR analysis of RNA extracted from WT, Δpta, and ΔlipL strains at 3 and 6 hours of growth.

qRT-PCR experiments were conducted with two biological replicates in technical triplicate. (B) Top - schematic of the cid operon. Bottom - normalized and mapped transcript reads across the cid operon in WT and ΔlipL strains. (B) Bacterial adenylate cyclase two-hybrid (BACTH) assay was used to test interactions between N-terminal-tagged Pta with LipL and C-terminal-tagged Pta with E2-PDH. Graph displays β-galactosidase activity (Miller Units) from E. coli BTH101 co-transformed with pUT18-pta and pKT25-lipL, pUT18C-pta and pKT25-pdhC, pUT18C-zip and pKT25-zip (positive control – PC) or pUT18C and pKT25 vectors (negative control – NC). ****, p < 0.0001 by one-way ANOVA with Tukey’s post hoc test. Cultures of E. coli BTH101strains co-transformed with the aforementioned plasmid combinations were also spotted on LB agar plates with X-Gal as an indicator. Data are representative of at least three independent experiments. (D) AlphaFold3 prediction of the interaction between Pta (blue) and E2-PDH (green). pTM (0.48) and an ipTM (0.2) are displayed graphically to the right of the model.

https://doi.org/10.1371/journal.ppat.1014183.s002

(TIF)

S2 Table. List of Oligonucleotides used in this study.

https://doi.org/10.1371/journal.ppat.1014183.s004

(PDF)

S3 Table. Significant differentially expressed genes (ΔlipL mutant compared to WT S. aureus).

https://doi.org/10.1371/journal.ppat.1014183.s005

(XLSX)

Acknowledgments

We thank Christoper Curme for his assistance with the pathway analysis. We are also grateful to the members of the Alonzo laboratory for their valuable discussions and constructive feedback on the manuscript.

References

  1. 1. Zorzoli A, Grayczyk JP, Alonzo F 3rd. Staphylococcus aureus tissue infection during sepsis is supported by differential use of bacterial or host-derived lipoic acid. PLoS Pathog. 2016;12(10):e1005933. pmid:27701474
  2. 2. Juttukonda LJ, Berends ETM, Zackular JP, Moore JL, Stier MT, Zhang Y, et al. Dietary manganese promotes staphylococcal infection of the heart. Cell Host Microbe. 2017;22(4):531-542.e8. pmid:28943329
  3. 3. Balasubramanian D, Harper L, Shopsin B, Torres VJ. Staphylococcus aureus pathogenesis in diverse host environments. Pathog Dis. 2017;75(1):ftx005. pmid:28104617
  4. 4. Richardson AR. Virulence and metabolism. Microbiol Spectr. 2019;7(2):7.2.39. pmid:31025624
  5. 5. Teoh WP, Chen X, Laczkovich I, Alonzo F III. Staphylococcus aureus adapts to the host nutritional landscape to overcome tissue-specific branched-chain fatty acid requirement. Proc Natl Acad Sci USA. 2021;118(13):e2022720118.
  6. 6. Chen X, Teoh WP, Stock MR, Resko ZJ, Iii FA. Branched chain fatty acid synthesis drives tissue-specific innate immune response and infection dynamics of Staphylococcus aureus. PLOS Pathogens. 2021;17(9):e1009930.
  7. 7. Richardson AR, Somerville GA, Sonenshein AL. Regulating the intersection of metabolism and pathogenesis in gram-positive bacteria. Microbiol Spectr. 2015;3(3):3.3.11. pmid:26185086
  8. 8. Tong SYC, Davis JS, Eichenberger E, Holland TL, Fowler VG Jr. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin Microbiol Rev. 2015;28(3):603–61. pmid:26016486
  9. 9. Naghavi M, Vollset SE, Ikuta KS, Swetschinski LR, Gray AP, Wool EE, et al. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050. The Lancet. 2024;404(10459):1199–226. pmid:39299261
  10. 10. Chen X, Alonzo F. Bacterial lipolysis of immune-activating ligands promotes evasion of innate defenses. Proc Natl Acad Sci U S A. 2019;116(9):3764–73. pmid:30755523
  11. 11. Watson SP, Clements MO, Foster SJ. Characterization of the starvation-survival response of Staphylococcus aureus. J Bacteriol. 1998;180(7):1750–8. pmid:9537371
  12. 12. Jenul C, Horswill AR. Regulation of Staphylococcus aureus virulence. Microbiol Spectr. 2019;7(2):10.1128/microbiolspec.gpp3-0031–2018. pmid:30953424
  13. 13. Tuganova A, Popov KM. Role of protein–protein interactions in the regulation of pyruvate dehydrogenase kinase activity. Biochem J. 2005;387(1):147–53. pmid:15504108
  14. 14. Durek P, Walther D. The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles. BMC Syst Biol. 2008;2:100. pmid:19032748
  15. 15. Aboulwafa M, Zhang Z, Saier MH Jr. Protein:Protein interactions in the cytoplasmic membrane apparently influencing sugar transport and phosphorylation activities of the e. coli phosphotransferase system. PLoS One. 2019;14(11):e0219332. pmid:31751341
  16. 16. Burckhardt RM, Buckner BA, Escalante-Semerena JC. Staphylococcus aureus modulates the activity of acetyl-Coenzyme A synthetase (Acs) by sirtuin-dependent reversible lysine acetylation. Mol Microbiol. 2019;112(2):588–604. pmid:31099918
  17. 17. Kelliher JL, Radin JN, Grim KP, Párraga Solórzano PK, Degnan PH, Kehl-Fie TE. Acquisition of the phosphate transporter NptA enhances Staphylococcus aureus pathogenesis by improving phosphate uptake in divergent environments. Infect Immun. 2017;86(1):e00631-17. pmid:29084897
  18. 18. Kelliher JL, Radin JN, Kehl-Fie TE. PhoPR contributes to Staphylococcus aureus growth during phosphate starvation and pathogenesis in an environment-specific manner. Infect Immun. 2018;86(10):e00371-18. pmid:30061377
  19. 19. Vitko NP, Grosser MR, Khatri D, Lance TR, Richardson AR. Expanded glucose import capability affords Staphylococcus aureus optimized glycolytic flux during infection. mBio. 2016;7(3):10.1128/mbio.00296-16.
  20. 20. Kaiser JC, Omer S, Sheldon JR, Welch I, Heinrichs DE. Role of BrnQ1 and BrnQ2 in branched-chain amino acid transport and virulence in Staphylococcus aureus. Infect Immun. 2015;83(3):1019–29. pmid:25547798
  21. 21. Frank MW, Yao J, Batte JL, Gullett JM, Subramanian C, Rosch JW. Host fatty acid utilization by Staphylococcus aureus at the infection site. mBio. 2020;11(3):e00920-20.
  22. 22. Thomsen IP, Liu GY. Targeting fundamental pathways to disrupt Staphylococcus aureus survival: clinical implications of recent discoveries. JCI Insight. 2018;3(5):e98216. pmid:29515041
  23. 23. Martin N, Lombardía E, Altabe SG, de Mendoza D, Mansilla MC. A lipA (yutB) mutant, encoding lipoic acid synthase, provides insight into the interplay between branched-chain and unsaturated fatty acid biosynthesis in Bacillus subtilis. J Bacteriol. 2009;191(24):7447–55. pmid:19820084
  24. 24. Christensen QH, Cronan JE. Lipoic acid synthesis: a new family of octanoyltransferases generally annotated as lipoate protein ligases. Biochemistry. 2010;49(46):10024–36. pmid:20882995
  25. 25. Cronan JE. Assembly of lipoic acid on its cognate enzymes: an extraordinary and essential biosynthetic pathway. Microbiol Mol Biol Rev. 2016;80(2):429–50. pmid:27074917
  26. 26. Teoh WP, Resko ZJ, Flury S, Alonzo F 3rd. Dynamic relay of protein-bound lipoic acid in Staphylococcus aureus. J Bacteriol. 2019;201(22):e00446-19. pmid:31451544
  27. 27. Wolfe AJ. The acetate switch. MMBR. 2005;69(1):12–50.
  28. 28. Sadykov MR, Thomas VC, Marshall DD, Wenstrom CJ, Moormeier DE, Widhelm TJ, et al. Inactivation of the Pta-AckA pathway causes cell death in Staphylococcus aureus. J Bacteriol. 2013;195(13):3035–44. pmid:23625849
  29. 29. Schütze A, Benndorf D, Püttker S, Kohrs F, Bettenbrock K. The impact of ackA, pta, and ackA-pta mutations on growth, gene expression and protein acetylation in Escherichia coli K-12. Front Microbiol [Internet]. 2020 [cited 2023 May 9];11. Available from: https://www.frontiersin.org/articles/10.3389/fmicb.2020.00233
  30. 30. Shahreen N, Ahn J, Alsiyabi A, Chowdhury NB, Shinde D, Chaudhari SS, et al. A thermodynamic bottleneck in the TCA cycle contributes to acetate overflow in Staphylococcus aureus. mSphere. 2025;10(1):e0088324. pmid:39745366
  31. 31. Troitzsch A, Loi VV, Methling K, Zühlke D, Lalk M, Riedel K, et al. Carbon source-dependent reprogramming of anaerobic metabolism in Staphylococcus aureus. J Bacteriol. 2021;203(8):e00639-20. pmid:33526614
  32. 32. Fuchs S, Pané-Farré J, Kohler C, Hecker M, Engelmann S. Anaerobic gene expression in Staphylococcus aureus. J Bacteriol. 2007;189(11):4275–89. pmid:17384184
  33. 33. Yang SJ, Rice KC, Brown RJ, Patton TG, Liou LE, Park YH, et al. A lysR-type regulator, cidR, is required for induction of the Staphylococcus aureus cidABC operon. J Bacteriol. 2005;187(17):5893–900. pmid:16109930
  34. 34. Rice KC, Nelson JB, Patton TG, Yang S-J, Bayles KW. Acetic acid induces expression of the Staphylococcus aureus cidABC and lrgAB murein hydrolase regulator operons. J Bacteriol. 2005;187(3):813–21. pmid:15659658
  35. 35. Rice KC, Mann EE, Endres JL, Weiss EC, Cassat JE, Smeltzer MS, et al. The cidA murein hydrolase regulator contributes to DNA release and biofilm development in Staphylococcus aureus. Proc Natl Acad Sci U S A. 2007;104(19):8113–8. pmid:17452642
  36. 36. Thomas VC, Sadykov MR, Chaudhari SS, Jones J, Endres JL, Widhelm TJ, et al. A central role for carbon-overflow pathways in the modulation of bacterial cell death. PLoS Pathog. 2014;10(6):e1004205. pmid:24945831
  37. 37. Patton TG, Rice KC, Foster MK, Bayles KW. The Staphylococcus aureus cidC gene encodes a pyruvate oxidase that affects acetate metabolism and cell death in stationary phase. Mol Microbiol. 2005;56(6):1664–74. pmid:15916614
  38. 38. Endres JL, Chaudhari SS, Zhang X, Prahlad J, Wang SQ, Foley LA. The Staphylococcus aureus CidA and LrgA proteins are functional holins involved in the transport of by-products of carbohydrate metabolism. mBio. 2021;13(1):e0282721.
  39. 39. Chaudhari SS, Thomas VC, Sadykov MR, Bose JL, Ahn DJ, Zimmerman MC, et al. The LysR-type transcriptional regulator, CidR, regulates stationary phase cell death in Staphylococcus aureus. Mol Microbiol. 2016;101(6):942–53. pmid:27253847
  40. 40. Thurlow LR, Stephens AC, Hurley KE, Richardson AR. Lack of nutritional immunity in diabetic skin infections promotes Staphylococcus aureus virulence. Sci Adv. 2020;6(46):eabc5569. pmid:33188027
  41. 41. Spalding MD, Prigge ST. Lipoic acid metabolism in microbial pathogens. Microbiol Mol Biol Rev. 2010;74(2):200–28. pmid:20508247
  42. 42. Choueiry F, Xu R, Zhu J. Adaptive metabolism of Staphylococcus aureus revealed by untargeted metabolomics. J Proteome Res. 2022;21(2):470–81. pmid:35043624
  43. 43. Vitko NP, Spahich NA, Richardson AR. Glycolytic dependency of high-level nitric oxide resistance and virulence in Staphylococcus aureus. mBio. 2015;6(2):e00045-15.
  44. 44. Somerville GA, Chaussee MS, Morgan CI, Fitzgerald JR, Dorward DW, Reitzer LJ, et al. Staphylococcus aureus aconitase inactivation unexpectedly inhibits post-exponential-phase growth and enhances stationary-phase survival. Infect Immun. 2002;70(11):6373–82. pmid:12379717
  45. 45. Halsey CR, Lei S, Wax JK, Lehman MK, Nuxoll AS, Steinke L. Amino acid catabolism in Staphylococcus aureus and the function of carbon catabolite repression. mBio. 2017;8(1):e01434-16. pmid:28196956
  46. 46. Monk IR, Shah IM, Xu M, Tan MW, Foster TJ. Transforming the untransformable: application of direct transformation to manipulate genetically Staphylococcus aureus and Staphylococcus epidermidis. mBio. 2012;3(2):e00277-11. pmid:22434850
  47. 47. Monk IR, Stinear TP. From cloning to mutant in 5 days: rapid allelic exchange in Staphylococcus aureus. Access Microbiol. 2021;3(2):000193. pmid:34151146
  48. 48. Chen J, Yoong P, Ram G, Torres VJ, Novick RP. Single-copy vectors for integration at the SaPI1 attachment site for Staphylococcus aureus. Plasmid. 2014;76:1–7. pmid:25192956
  49. 49. Somerville GA, Saïd-Salim B, Wickman JM, Raffel SJ, Kreiswirth BN, Musser JM. Correlation of acetate catabolism and growth yield in Staphylococcus aureus: implications for host-pathogen interactions. Infect Immun. 2003;71(8):4724–32. pmid:12874354
  50. 50. Schlag S, Fuchs S, Nerz C, Gaupp R, Engelmann S, Liebeke M, et al. Characterization of the oxygen-responsive NreABC regulon of Staphylococcus aureus. J Bacteriol. 2008;190(23):7847–58. pmid:18820014
  51. 51. Karimova G, Pidoux J, Ullmann A, Ladant D. A bacterial two-hybrid system based on a reconstituted signal transduction pathway. Proc Natl Acad Sci U S A. 1998;95(10):5752–6. pmid:9576956
  52. 52. Battesti A, Bouveret E. The bacterial two-hybrid system based on adenylate cyclase reconstitution in Escherichia coli. Methods. 2012;58(4):325–34. pmid:22841567
  53. 53. Won HI, Watson SM, Ahn J-S, Endres JL, Bayles KW, Sadykov MR. Inactivation of the Pta-AckA pathway impairs fitness of Bacillus anthracis during overflow metabolism. J Bacteriol. 2021;203(9):e00660-20. pmid:33593944
  54. 54. Torres VJ, Benson MA, Voyich JM. Staphylococcus aureus pathogenesis and virulence factor regulation. In: Regulation of bacterial virulence [Internet]. John Wiley & Sons, Ltd; 2012 [cited 2026 Feb 26]. p. 58–78. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1128/9781555818524.ch4 https://doi.org/10.1128/9781555818524.ch4
  55. 55. Alonzo F 3rd, Torres VJ. The bicomponent pore-forming leucocidins of Staphylococcus aureus. Microbiol Mol Biol Rev. 2014;78(2):199–230. pmid:24847020
  56. 56. Benson MA, Lilo S, Wasserman GA, Thoendel M, Smith A, Horswill AR, et al. Staphylococcus aureus regulates the expression and production of the staphylococcal superantigen-like secreted proteins in a Rot-dependent manner. Mol Microbiol. 2011;81(3):659–75. pmid:21651625
  57. 57. Anil A, Braza RED, Liu B, Altouma V, Adedeji C, Welling A, et al. Staphylococcus aureus exhibits spatiotemporal heterogeneity in Sae activity during kidney abscess development. mBio. 2025;16(12):e0204325. pmid:41369255
  58. 58. Stock MR, Fang L, Johnson KR, Cosgriff C, Teoh WP, Alonzo F 3rd. Characterization of MroQ-dependent maturation and export of the Staphylococcus aureus accessory gene regulatory system autoinducing peptide. Infect Immun. 2022;90(10):e0026322. pmid:36073934
  59. 59. Jordan SW, Cronan JE Jr. The Escherichia coli lipB gene encodes lipoyl (octanoyl)-acyl carrier protein:protein transferase. J Bacteriol. 2003;185(5):1582–9. pmid:12591875
  60. 60. Miller JR, Busby RW, Jordan SW, Cheek J, Henshaw TF, Ashley GW, et al. Escherichia coli LipA is a lipoyl synthase: in vitro biosynthesis of lipoylated pyruvate dehydrogenase complex from octanoyl-acyl carrier protein. Biochemistry. 2000;39(49):15166–78. pmid:11106496
  61. 61. Martin N, Christensen QH, Mansilla MC, Cronan JE, de Mendoza D. A novel two-gene requirement for the octanoyltransfer reaction of Bacillus subtilis lipoic acid biosynthesis. Mol Microbiol. 2011;80(2):335–49. pmid:21338420
  62. 62. Christensen QH, Martin N, Mansilla MC, de Mendoza D, Cronan JE. A novel amidotransferase required for lipoic acid cofactor assembly in Bacillus subtilis. Mol Microbiol. 2011;80(2):350–63. pmid:21338421
  63. 63. Freiberg C, Brunner NA, Schiffer G, Lampe T, Pohlmann J, Brands M, et al. Identification and characterization of the first class of potent bacterial acetyl-CoA carboxylase inhibitors with antibacterial activity. J Biol Chem. 2004;279(25):26066–73. pmid:15066985
  64. 64. Singh VK, Sirobhushanam S, Ring RP, Singh S, Gatto C, Wilkinson BJ. Roles of pyruvate dehydrogenase and branched-chain α-keto acid dehydrogenase in branched-chain membrane fatty acid levels and associated functions in Staphylococcus aureus. J Med Microbiol. 2018;67(4):570–8. pmid:29498620
  65. 65. Satiaputra J, Eijkelkamp BA, McDevitt CA, Shearwin KE, Booker GW, Polyak SW. Biotin-mediated growth and gene expression in Staphylococcus aureus is highly responsive to environmental biotin. Appl Microbiol Biotechnol. 2018;102(8):3793–803. pmid:29508030
  66. 66. Laczkovich I, Teoh WP, Flury S, Grayczyk JP, Zorzoli A, Alonzo F 3rd. Increased flexibility in the use of exogenous lipoic acid by Staphylococcus aureus. Mol Microbiol. 2018;109(2):150–68. pmid:29660187
  67. 67. Gaupp R, Schlag S, Liebeke M, Lalk M, Götz F. Advantage of upregulation of succinate dehydrogenase in Staphylococcus aureus biofilms. J Bacteriol. 2010;192(9):2385–94. pmid:20207757
  68. 68. Hammer ND, Reniere ML, Cassat JE, Zhang Y, Hirsch AO, Indriati Hood M, et al. Two heme-dependent terminal oxidases power Staphylococcus aureus organ-specific colonization of the vertebrate host. mBio. 2013;4(4):e00241-13. pmid:23900169
  69. 69. Xu T, Han J, Zhang J, Chen J, Wu N, Zhang W, et al. Absence of protoheme IX farnesyltransferase CtaB causes virulence attenuation but enhances pigment production and persister survival in MRSA. Front Microbiol. 2016;7:1625. pmid:27822202
  70. 70. Hammer ND, Schurig-Briccio LA, Gerdes SY, Gennis RB, Skaar EP. CtaM is required for menaquinol oxidase aa3 function in Staphylococcus aureus. mBio. 2016;7(4):e00823-16.
  71. 71. Chaudhari SS, Kim M, Lei S, Razvi F, Alqarzaee AA, Hutfless EH. Nitrite derived from endogenous bacterial nitric oxide synthase activity promotes aerobic respiration. mBio. 2017;8(4):e00887-17. pmid:28765220
  72. 72. Rice KC, Patton T, Yang S-J, Dumoulin A, Bischoff M, Bayles KW. Transcription of the Staphylococcus aureus cid and lrg murein hydrolase regulators is affected by sigma factor B. J Bacteriol. 2004;186(10):3029–37. pmid:15126464
  73. 73. Sadykov MR, Windham IH, Widhelm TJ, Yajjala VK, Watson SM, Endres JL, et al. CidR and CcpA synergistically regulate Staphylococcus aureus cidABC expression. J Bacteriol. 2019;201(23):e00371-19. pmid:31501288
  74. 74. Wolfe AJ, Chang D-E, Walker JD, Seitz-Partridge JE, Vidaurri MD, Lange CF, et al. Evidence that acetyl phosphate functions as a global signal during biofilm development. Mol Microbiol. 2003;48(4):977–88. pmid:12753190
  75. 75. Kim JN, Ahn S-J, Burne RA. Genetics and physiology of acetate metabolism by the Pta-Ack pathway of Streptococcus mutans. Appl Environ Microbiol. 2015;81(15):5015–25. pmid:25979891
  76. 76. Presecan-Siedel E, Galinier A, Longin R, Deutscher J, Danchin A, Glaser P, et al. Catabolite regulation of the pta gene as part of carbon flow pathways in Bacillus subtilis. J Bacteriol. 1999;181(22):6889–97. pmid:10559153
  77. 77. Huthmacher C, Gille C, Holzhütter H-G. A computational analysis of protein interactions in metabolic networks reveals novel enzyme pairs potentially involved in metabolic channeling. J Theor Biol. 2008;252(3):456–64. pmid:17988690
  78. 78. Xu QS, Jancarik J, Lou Y, Kuznetsova K, Yakunin AF, Yokota H, et al. Crystal structures of a phosphotransacetylase from Bacillus subtilis and its complex with acetyl phosphate. J Struct Funct Genomics. 2005;6(4):269–79. pmid:16283428
  79. 79. Iyer PP, Lawrence SH, Luther KB, Rajashankar KR, Yennawar HP, Ferry JG, et al. Crystal structure of phosphotransacetylase from the methanogenic archaeon Methanosarcina thermophila. Structure. 2004;12(4):559–67. pmid:15062079
  80. 80. Xu QS, Shin D-H, Pufan R, Yokota H, Kim R, Kim S-H. Crystal structure of a phosphotransacetylase from Streptococcus pyogenes. Proteins. 2004;55(2):479–81. pmid:15048838
  81. 81. Rado TA, Hoch JA. Phosphotransacetylase from Bacillus subtilis: purification and physiological studies. Biochim Biophys Acta. 1973;321(1):114–25. pmid:4201530
  82. 82. Brinsmade SR, Escalante-Semerena JC. In vivo and in vitro analyses of single-amino acid variants of the Salmonella enterica phosphotransacetylase enzyme provide insights into the function of its N-terminal domain. J Biol Chem. 2007;282(17):12629–40. pmid:17339319
  83. 83. Campos-Bermudez VA, Bologna FP, Andreo CS, Drincovich MF. Functional dissection of Escherichia coli phosphotransacetylase structural domains and analysis of key compounds involved in activity regulation. FEBS J. 2010;277(8):1957–66. pmid:20236319
  84. 84. Oberlies G, Fuchs G, Thauer RK. Acetate thiokinase and the assimilation of acetate in methanobacterium thermoautotrophicum. Arch Microbiol. 1980;128(2):248–52. pmid:6111300
  85. 85. Bologna FP, Campos-Bermudez VA, Saavedra DD, Andreo CS, Drincovich MF. Characterization of Escherichia coli EutD: a phosphotransacetylase of the ethanolamine operon. J Microbiol. 2010;48(5):629–36. pmid:21046341
  86. 86. Acetate kinase and phosphotransacetylase. In: Methods in enzymology [Internet]. Academic Press; 2011 [cited 2026 Feb 26]. p. 219–31. Available from: https://www.sciencedirect.com/science/chapter/bookseries/pii/B9780123851123000111
  87. 87. Cherkasov A, Hsing M, Zoraghi R, Foster LJ, See RH, Stoynov N, et al. Mapping the protein interaction network in methicillin-resistant Staphylococcus aureus. J Proteome Res. 2011;10(3):1139–50. pmid:21166474
  88. 88. Cheung GYC, Wang R, Khan BA, Sturdevant DE, Otto M. Role of the accessory gene regulator agr in community-associated methicillin-resistant Staphylococcus aureus pathogenesis. Infect Immun. 2011;79(5):1927–35. pmid:21402769
  89. 89. Thompson TA, Brown PD. Association between the agr locus and the presence of virulence genes and pathogenesis in Staphylococcus aureus using a Caenorhabditis elegans model. Int J Infect Dis. 2017;54:72–6. pmid:27915107
  90. 90. Cheung GYC, Bae JS, Otto M. Pathogenicity and virulence of Staphylococcus aureus. Virulence. 2021;12(1):547–69. pmid:33522395
  91. 91. Wang B, Zhao A, Novick RP, Muir TW. Activation and inhibition of the receptor histidine kinase AgrC occurs through opposite helical transduction motions. Mol Cell. 2014;53(6):929–40. pmid:24656130
  92. 92. Wang B, Zhao A, Xie Q, Olinares PD, Chait BT, Novick RP, et al. Functional plasticity of the AgrC receptor histidine kinase required for staphylococcal virulence. Cell Chem Biol. 2017;24(1):76–86. pmid:28065658
  93. 93. Brown AJ, Goldsworthy SM, Barnes AA, Eilert MM, Tcheang L, Daniels D, et al. The Orphan G protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem. 2003;278(13):11312–9. pmid:12496283
  94. 94. Le Poul E, Loison C, Struyf S, Springael JY, Lannoy V, Decobecq ME, et al. Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. J Biol Chem. 2003;278(28):25481–9. pmid:12711604
  95. 95. Nakajima A, Nakatani A, Hasegawa S, Irie J, Ozawa K, Tsujimoto G, et al. The short chain fatty acid receptor GPR43 regulates inflammatory signals in adipose tissue M2-type macrophages. PLoS One. 2017;12(7):e0179696. pmid:28692672
  96. 96. Ang Z, Xiong D, Wu M, Ding JL. FFAR2-FFAR3 receptor heteromerization modulates short-chain fatty acid sensing. FASEB J. 2018;32(1):289–303. pmid:28883043
  97. 97. Schlatterer K, Beck C, Schoppmeier U, Peschel A, Kretschmer D. Acetate sensing by GPR43 alarms neutrophils and protects from severe sepsis. Commun Biol. 2021;4(1):928. pmid:34330996
  98. 98. Galvão I, Tavares LP, Corrêa RO, Fachi JL, Rocha VM, Rungue M, et al. The metabolic sensor GPR43 receptor plays a role in the control of Klebsiella pneumoniae infection in the lung. Front Immunol. 2018;9:142. pmid:29515566
  99. 99. Sencio V, Barthelemy A, Tavares LP, Machado MG, Soulard D, Cuinat C, et al. Gut dysbiosis during influenza contributes to pulmonary pneumococcal superinfection through altered short-chain fatty acid production. Cell Rep. 2020;30(9):2934-2947.e6. pmid:32130898
  100. 100. Schlatterer K, Peschel A, Kretschmer D. Short-chain fatty acid and FFAR2 activation – A new option for treating infections? Front Cell Infect Microbiol. 2021;11:785833. pmid:34926327
  101. 101. Xu W, Bradstreet TR, Zou Z, Hickerson S, Zhou Y, He H, et al. Reprogramming aerobic metabolism mitigates Streptococcus pyogenes tissue damage in a mouse necrotizing skin infection model. Nat Commun. 2025;16(1):2559. pmid:40089471
  102. 102. Overbeek R, Begley T, Butler RM, Choudhuri JV, Chuang H-Y, Cohoon M, et al. The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res. 2005;33(17):5691–702. pmid:16214803
  103. 103. Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42(Database issue):D206-14. pmid:24293654
  104. 104. Letunic I, Bork P. Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res. 2024;52(W1):W78–82. pmid:38613393
  105. 105. Monk IR, Tree JJ, Howden BP, Stinear TP, Foster TJ. Complete bypass of restriction systems for major Staphylococcus aureus lineages. mBio. 2015;6(3):e00308-15. pmid:26015493
  106. 106. Acosta IC, Albers A, Fang L, Serrato G, Teoh WP, Glanville DG, et al. Staphylococcus aureus exploits lipoic acid salvage to combat host oxidative stress. Cell Rep. 2025;44(8):116095. pmid:40751910
  107. 107. Urso A, Monk IR, Cheng Y-T, Predella C, Wong Fok Lung T, Theiller EM, et al. Staphylococcus aureus adapts to exploit collagen-derived proline during chronic infection. Nat Microbiol. 2024;9(10):2506–21. pmid:39134708
  108. 108. Huang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57. pmid:19131956
  109. 109. Sherman BT, Hao M, Qiu J, Jiao X, Baseler MW, Lane HC, et al. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 2022;50(W1):W216–21. pmid:35325185
  110. 110. Miller J. Assay of β-galactosidase. In: Experiments in molecular genetics. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory; 1972. p. 352–5.
  111. 111. Agbavor C, Torres M, Inniss NL, Latimer S, Minasov G, Shuvalova L, et al. Structural analysis of extracellular ATP-independent chaperones of streptococcal species and protein substrate interactions. mSphere. 2025;10(2):e01078-24.
  112. 112. Scheuermann TH, Padrick SB, Gardner KH, Brautigam CA. On the acquisition and analysis of microscale thermophoresis data. Anal Biochem. 2016;496:79–93. pmid:26739938