Abstract

   The coordination of public and private goods production is essential
   for bacterial adaptation to environmental changes. Quorum sensing (QS)
   regulates this balance by mediating the trade‐off between the communal
   benefits of “public goods,” such as siderophores and antibiotics, and
   the individual metabolic needs fulfilled by “private goods,” such as
   intracellular metabolites utilized for growth and survival. Pseudomonas
   fluorescens 2P24 harbors a LasI/LasR‐type QS system, MupI/MupR, which
   regulates mupirocin production through signaling molecules. This study
   explores how QS coordinates carbon and nitrogen metabolism to optimize
   the production of key secondary metabolites, including
   2,4‐diacetylphloroglucinol (2,4‐DAPG), mupirocin, and siderophores,
   which serve as public goods. Loss of QS disrupts this balance by
   enhancing the Krebs cycle, denitrification, pyruvate anaplerosis, and
   ammonium assimilation, lead to halted 2,4‐DAPG and mupirocin synthesis
   and increased siderophore production. In the absence of QS, elevated
   siderophore production compensates for iron acquisition, ensuring rapid
   cellular growth. Under nutrient‐limited or high cell density
   conditions, MupR regulates carbon and nitrogen fluxes to sustain public
   goods production. These findings highlight QS as a key environmental
   sensor that fine‐tunes resource allocation, bacterial fitness, and
   adaptation to ecological and nutritional conditions, suggesting the
   potential for QS‐targeted approaches to enhance antibiotic production
   and agricultural sustainability.

   Keywords: carbon and nitrogen metabolism, gene transcription, public
   goods, quorum sensing, transcription factor
     __________________________________________________________________

   Pseudomonas fluorescens 2P24 utilizes a LasI/LasR‐type quorum sensing
   (QS) system, MupI/MupR, to regulate carbon and nitrogen metabolism for
   optimal production of secondary metabolites as public goods, including
   2,4‐diacetylphloroglucinol, mupirocin, and siderophores. QS acts as a
   sensor, regulating metabolic fluxes to maintain energy and nutrient
   homeostasis, enabling facultative cooperation, and supporting long‐term
   adaptation to environmental changes.

   graphic file with name ADVS-12-2412224-g004.jpg

1. Introduction

   Quorum sensing (QS) is a pivotal mechanism of bacterial cell‐to‐cell
   communication, relying on bacterial population density and coordination
   of social behavior.^[ [46]^1 ^] It involves the production of
   extracellular signaling molecules called autoinducers, which accumulate
   as cell‐population density increases.^[ [47]^2 ^] Bacteria use the QS
   system to regulate the expression of genes associated with the
   production of public goods, orchestrating a range of microbial
   behaviors such as bioluminescence, biofilm formation, mobility,
   virulence factor production, antibiotic synthesis, siderophore
   production, and diverse protease secretion.^[ [48]^3 , [49]^4 ^]
   However, producing these public goods imposes a metabolic burden on
   microbial communities, affecting the balance between communal benefits
   and individual costs in sophisticated environments.^[ [50]^5 , [51]^6
   ^] Strains that do not produce public goods, often referred to as
   “cheaters,” tend to produce private goods, benefiting from the public
   goods produced by others without bearing the cost of production.^[
   [52]^7 ^] Cheaters can be controlled by cooperator cells through
   various policing mechanisms, yet in some cases, nonproducing strains
   are not penalized and continue to participate in community
   cooperation.^[ [53]^8 , [54]^9 ^] This behavior is elucidated by the
   Black Queen Hypothesis, which provides a cost‐benefit selection
   framework suggesting that the loss of costly functional genes can
   improve growth efficiency within a microbial community.^[ [55]^10 ,
   [56]^11 , [57]^12 ^]

   The function of QS and its role in enhancing cooperative behavior
   remains a topic of debate. While QS is conventionally perceived as a
   cell density‐dependent mechanism that facilitates the production and
   sharing of public goods among bacterial communities, recent studies
   posit QS as a sensor for individual bacteria cells to monitor signal
   levels and adapt to their physical environment.^[ [58]^13 , [59]^14 ^]
   In this context, individual cells produce and monitor signal levels to
   infer their local physical constraints. In crowded conditions, QS may
   help maintain homeostatic primary metabolism, balancing the production
   of public goods and private goods and addressing trade‐offs inherent in
   microbial communities. The acyl‐homoserine lactone (AHL) system has
   been extensively studied in the QS system from Gram‐negative
   bacteria.^[ [60]^15 , [61]^16 ^] It involves LuxI‐type enzymes that
   synthesize autoinducers like AHLs by catalyzing the transfer of an acyl
   group, bound to acyl carrier protein (ACP) from fatty acid
   biosynthesis, to S‐adenosylmethionine, enabling the formation of AHLs
   that interact with LuxR‐type transcriptional regulators to modulate QS
   target genes.^[ [62]^17 ^] AHLs are small lipid‐based signaling
   molecules in the QS systems of Gram‐negative bacteria, consisting of a
   homoserine lactone ring covalently linked to an acyl side chain, with
   the acyl group typically ranging from C4 to C18 carbons, either
   saturated or unsaturated, and these structural variations influence the
   specificity of AHLs for their corresponding LuxR‐type receptors,
   thereby affecting the sensitivity and functionality of the QS signaling
   cascade.^[ [63]^16 ^] AHLs are closely intertwined with the metabolism
   of bacterial substances, influencing both anabolism and catabolism.
   This metabolic interplay, primarily involving carbon, nitrogen, and
   sulfur metabolism, enables bacteria to rapidly adapt to harsh
   environments, such as nutrient scarcity and extreme survival
   conditions.^[ [64]^18 ^]

   For instance, in the rice pathogen Burkholderia glumae, the QS system
   TofI/R activates the expression of the transcription factor QsmR to
   downregulate pstI expression and slow glucose uptake. Simultaneously,
   the QsmR from B. glumae negatively regulates pathways, such as
   glycolysis, amino acids and nucleic acids biosynthesis, energy
   metabolism, and nitrogen metabolism. In addition, the QsmR upregulated
   the Krebs cycle in B. glumae.^[ [65]^19 , [66]^20 ^] Similarly,
   Yersinia pestis expresses a typical QS system for downregulating the
   glucose and nucleic acid metabolism while upregulating the Krebs
   cycle.^[ [67]^21 ^] The opportunistic human pathogen Pseudomonas
   aeruginosa uses LasI/R and RhlI/R to positively regulate the Krebs
   cycle, amino acids and nucleic acid metabolism, and negatively regulate
   denitrification.^[ [68]^22 , [69]^23 ^] These observations highlight
   that cell density, often linked to nutrient‐limited conditions, plays a
   pivotal role in QS‐regulated metabolic adjustments. The role of QS in
   regulating metabolic responses under environmental stress is indeed
   complex and how it intricately coordinates primary and secondary
   metabolism pathways to ensure survival in various sophisticated growth
   conditions remains uncertain. The heterogeneity in QS among bacteria
   like Pseudomonas, Vibrio, and Xanthomonas emphasizes a “division of
   labor” that allows for performing distinct tasks and shared resource
   utilization, ultimately benefiting overall community fitness.^[ [70]^12
   , [71]^24 , [72]^25 ^] Still, questions persist about how QS manages
   homeostatic metabolism to balance the trade‐offs between primary
   metabolism and secondary metabolism, adapting to nutritional dynamics
   within microbial communities.

   The study of QS‐mediated coordination of bacterial metabolism and
   social behaviors is important for understanding how this cooperative
   communication system adapts to enhance fitness. Pseudomonas fluorescens
   2P24, isolated from the wheat rhizosphere, produces various secondary
   metabolites, including 2,4‐diacetylphloroglucinol (2,4‐DAPG), known for
   its potent inhibitory effects against a broad spectrum of soil‐borne
   pathogens.^[ [73]^26 ^] In addition to 2,4‐DAPG, the genome of P.
   fluorescens 2P24 also contains gene clusters for mupirocin, siderophore
   pyoverdine, and hydrogen cyanide biosynthetic gene clusters,
   highlighting the significant role of these secondary metabolites in
   determining bacterial fitness. Notably, P. fluorescens 2P24 harbors a
   LasI/LasR acyl homoserine lactone‐dependent QS system within the
   mupirocin biosynthesis gene cluster, designated as MupI/MupR. In P.
   fluorescens NCIMB 10586, the LasI homolog MupI synthesizes a signaling
   molecule that activates MupR, modulating the expression of genes
   responsible for mupirocin biosynthesis, thereby adding an additional
   layer of complexity to bacterial communication and regulation of
   secondary metabolite production.^[ [74]^27 ^] Here, we examined the
   role of QS‐mediated regulation of secondary metabolites production in
   P. fluorescens 2P24 by modulating the metabolic capabilities of
   microbial communities.

   By integrating the transcriptome, metabolome, and ChIP‐seq analysis, we
   investigated impact of QS on the metabolic flux and gene transcription
   involved in secondary metabolite production in P. fluorescens 2P24. The
   loss of the QS function drastically alters the expression of genes
   involved in the Krebs cycle, fatty acid, amino acid metabolism, and
   denitrification, decreases the key Krebs cycle intermediate
   2‐oxoglutarate (2‐OG), completely inhibit the production of
   carbon‐based secondary metabolites like AHL, 2,4‐DAPG, and mupirocin,
   while increase nitrogen‐based pyoverdine production. In conditions of
   high cell density, MupR acts as a metabolic brake, restricting the
   Krebs cycle and adjusting metabolic flux from carbon to nitrogen
   metabolism, resulting in higher level of 2‐OG compared to the loss of
   QS function mutant, which indicate QS as environmental sensor for
   orchestrating the balance between the primary metabolism and secondary
   metabolism. In the absence of QS control, increased pyoverdine
   production serves as a complementary system for bacterial growth,
   ensuring sufficient iron acquisition which is vital for cellular
   processes and overall fitness. The ecological and nutritional
   environment profoundly influences the spectrum of secondary metabolites
   produced by bacteria, with QS regulation markedly enhancing this
   diversity. By understanding how MupR‐mediated metabolic regulation
   governs the production of these metabolites, this study will bridge
   fundamental QS function with its practical applications, highlighting
   the potential of QS‐targeted approaches to optimize microbial
   metabolism for antibiotic production or promote sustainability in
   agricultural ecosystems.

2. Results

2.1. QS Positively Regulated Polyketide 2,4‐DAPG and Mupirocin and Negatively
Regulated Pyoverdine

   To assess the impact of QS on the metabolism of P. fluorescens 2P24, we
   monitored the growth of the wild‐type 2P24, the ΔmupR, and the ΔmupI
   mutant strains in KB medium. The molecular basis of QS was further
   explored using Foldseek^[ [75]^28 ^] to identify the homologs of MupI
   in the Protein Data Bank (PDB).^[ [76]^29 ^] The analysis revealed the
   highest similarity to LasI from P. aeruginosa PAO1, with a sequence
   identity of 55.2% and a root mean square deviation (RMSD) of 2.58 Å,
   indicating substantial structural conservation. LasI from P. aeruginosa
   is involved in the constitutive production of the QS signaling molecule
   3‐oxo‐C12‐HSL, which activates the LasR receptor and regulates
   QS‐dependent genes in P. aeruginosa.^[ [77]^30 ^] This structural
   similarity suggests that MupI play an analogous role in P. fluorescens
   2P24. LC‐MS analysis confirmed that MupI predominantly synthesizes
   3‐oxo‐C10‐HSL, with lesser amounts of 3‐oxo‐C12‐HSL also present
   (Figure [78] 1A). Interestingly, the QS null mutants, the mutant ΔmupR
   and the mutant ΔmupI, exhibited accelerated growth during the late
   exponential phase compared to the wild type strain (WT)
   (Figure [79]1B). Supplementation of 2 × 10^−6 m of exogenous
   3‐oxo‐C10‐HSL restored the growth rate of the mutant ΔmupI strain to
   that WT level, suggesting that QS regulates the growth restraint during
   stationary phases, particularly under nutrient scarcity.

Figure 1.

   Figure 1
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   The regulation of cell growth and public goods production of P.
   fluorescens 2P24 by QS. A) HPLC and LC‐MS analysis of AHLs produced by
   P. fluorescens 2P24. HPLC represents the samples of an extract prepared
   from the culture medium of P. fluorescens 2P24, ΔmupI mutant strain,
   the standard chemicals of 3‐oxo‐C10‐HSL and 3‐oxo‐C12‐HSL (left).
   Further analysis of MS/MS spectra confirmed the identity of
   3‐oxo‐C10‐HSL with m/z 270.2 and 3‐oxo‐C12‐HSL with m/z 298.2 extracted
   from the culture medium of P. fluorescens 2P24 (right). B) Difference
   of growth curves (colony‐forming units [CFU] per mL) between P.
   fluorescens 2P24 and the QS null mutants. CFU were determined by
   performing serial dilutions for plating on LB agar. The QS null mutants
   grew more rapidly at the late exponential and the early stationary
   phase than did the wild type. The initial cell turbidity was 0.1 at
   600 nm. C) Quantitative analysis of 2,4‐DAPG, mupirocin, and pyoverdine
   production, the cell growth of ΔmupI (top panel) and ΔmupR (bottom
   panel) mutants compared with wide type P. fluorescens 2P24. Error bars
   denote standard deviations (n = 3). Statistical analyses were performed
   using the t‐test and two‐way ANOVA, p < 0.0001 is displayed as ****p
   < 0.001 is displayed as ***p < 0.01 is displayed as **p < 0.05 is
   displayed as *.

   2,4‐DAPG has been previously characterized as a key secondary
   metabolite produced by P. fluorescens 2P24.^[ [81]^26 ^] Further genome
   analysis using antiSMASH^[ [82]^31 ^] identified additional
   biosynthetic gene clusters for mupirocin and pyoverdine, highlighting
   the metabolic versatility of this strain. Notably, mupirocin
   biosynthetic genes share 85% similarity with those in P. fluorescens
   NCIMB 10586, while pyoverdine genes exhibit 50% similarity to those in
   P. protegens Pf‐5. Metabolite quantification using LC‐MS and HPLC
   confirmed mupirocin synthesis (Figure [83]S1A, Supporting Information),
   while pyoverdine was characterized by intrinsic fluorescence and the
   Chrome Azurol S (CAS) assay for siderophore activity (Figure [84]S1B,
   Supporting Information).

   We measured these public goods production in P. fluorescens 2P24,
   QS‐deficient strains ΔmupR and ΔmupI, and their complemented
   counterparts, ΔmupR::pBBR5‐mupR and ΔmupI::pBBR5‐mupI (Figure [85]1C).
   In P. fluorescens 2P24, mupirocin maintains a steady concentration
   postsynthesis, whereas 2,4‐DAPG levels rise during early growth phases
   and decline at higher cell densities (Figure [86]S2A,B, Supporting
   Information). However, the QS null mutants did not produce either
   mupirocin or 2,4‐DAPG, indicating a critical role of QS in its
   synthesis. Compared to the wild‐type strain, pyoverdine production was
   higher in the QS null mutants ΔmupR and ΔmupI (Figure [87]S2C,
   Supporting Information). Complementation of the QS‐null mutants fully
   restored the production of all public goods, with ΔmupR::pBBR5‐mupR
   showing significantly enhanced mupirocin production compared to the
   wild type. Furthermore, the biofilm produced by the QS‐deficient
   strains ΔmupR and ΔmupI was significantly reduced compared to the
   wild‐type (Figure [88]S3, Supporting Information), highlighting the
   essential role of MupI/MupR QS system in regulating the production of
   public goods.

   Mupirocin and 2,4‐DAPG, polyketide antibiotics produced by P.
   fluorescens 2P24, are synthesized through polyketide biosynthesis
   pathways involving the iterative condensation of carboxylic acid
   building blocks like acetyl‐CoA or malonyl‐CoA, catalyzed by polyketide
   synthase (PKS) enzymes.^[ [89]^32 , [90]^33 , [91]^34 ^] The
   biosynthesis of pyoverdine, a siderophore crucial for iron acquisition
   and microbial competition, is mediated by non‐ribosomal peptide
   synthetases (NRPSs).^[ [92]^35 ^] NRPSs are large multifunctional
   enzymes that assemble peptide chains using amino acid precursors.^[
   [93]^36 ^] During pyoverdine biosynthesis, carbon resources are
   directed toward essential amino acid precursors, such as l‐lysine,
   d‐aspartic acid, and l‐threonine, to ensure the availability of
   building blocks for siderophore synthesis.^[ [94]^37 ^] The
   biosynthesis of polyketide antibiotics like mupirocin and 2,4‐DAPG
   diverts acyl‐CoA fluxes away from central carbon metabolism, while
   pyoverdine production reallocates carbon toward essential amino acid
   precursors.

   In the absence of QS regulation, the overproduction of pyoverdine in
   QS‐deficient mutants may compensate for the lack of mupirocin and
   2,4‐DAPG production, providing a competitive advantage in iron‐limited
   environments. However, this increased pyoverdine synthesis may disrupt
   the cooperative behaviors typically mediated by QS, such as the
   collective production of other public goods like polyketide
   antibiotics. These shifts may affect the overall viability and fitness
   of bacterial communities, with potential trade‐offs arising from the
   metabolic cost of excessive siderophore production. The metabolic costs
   of producing large amounts of pyoverdine could reduce the overall
   fitness of QS‐deficient mutants, underscoring the delicate balance
   between resource allocation and the benefits of public goods
   production. This indicates that QS in P. fluorescens 2P24 could
   prioritize specific metabolic pathways, regulating microbial energy
   metabolism to balance growth with the production of public goods
   critical for community fitness and survival.

2.2. MupR Is a Transcriptional Regulator for the Coordination of Primary
Carbon and Nitrogen Metabolism

   To elucidate the regulatory mechanisms mediated by MupR in P.
   fluorescens 2P24, we used ChIP‐seq analysis combined with promoter
   fusion reporter systems and RT‐qPCR. Results from four independent
   ChIP‐seq experiments and KEGG enrichment analysis are summarized in
   Table [95]S3 and Figure [96]S4 (Supporting Information). Validation of
   these targets was achieved through EGFP‐based promoter fusion assays
   and RT‐qPCR. We discovered that MupR binds to the promoters of the gene
   clusters responsible for mupirocin and 2,4‐DAPG biosynthesis, but not
   to those of the pyoverdine cluster. This indicates that MupR may
   directly regulate the gene transcription associated with mupirocin and
   2,4‐DAPG production. Combined with ChIP‐seq analysis and operon‐mapper
   prediction, we evaluated the transcriptional units of the mupirocin and
   2,4‐DAPG biosynthetic clusters and genes of the relative fluorescence
   of plasmid‐borne EGFP reporter fusions in 2P24 and ΔmupR strains. MupR
   positively regulates key functions involved in the biosynthesis of
   antibiotics 2,4‐DAPG (Figure [97]S5A, Supporting Information) and
   mupirocin (Figure [98]S5B, Supporting Information). Within the mup gene
   cluster, seven promoters exhibited significantly reduced expression and
   one showed slightly decreased expression in the mupR mutant compared to
   the wide type 2P24 strain, indicating activation by MupR. In addition,
   RT‐qPCR analysis confirmed the downregulation of these eight target
   genes). Within the phl cluster, differential expression patterns were
   observed, phlF promoter was upregulated, phlA was significantly
   downregulated, and phlD showed no change in the ΔmupR mutant compared
   to wild‐type 2P24, suggesting the role of MupR in both repression and
   activation of transcription within this cluster. However, upon further
   RT‐qPCR analysis, all four genes were downregulated.

   Further analysis of ChIP‐seq data focused on key enzymes from TCA
   cycle, revealing extensive regulation by MupR (Figure [99] 2A). MupR
   negatively regulates key functions involved in the TCA cycle. MupR
   directly binds to the promoters of several critical enzymes including
   citrate synthase (gltA), pyruvate carboxylase subunit A (pycA),
   aconitate hydratase B (acnB), 2‐oxoglutarate dehydrogenase subunit E1
   (sucA), and succinate dehydrogenase b556 subunit (sdhC), leading to
   increased transcriptional levels in the ΔmupR strain and suggesting
   that QS can slow down the TCA cycle. Conversely, MupR upregulates
   oxaloacetate decarboxylase (bcpA), a carboxy‐lyase that converts
   oxaloacetate into pyruvate,^[ [100]^38 ^] indicating a shift in
   metabolic fluxes and potentially altering energy production pathways.
   MupR repressed genes involved in glycerol metabolism, specifically
   glycerol‐3‐phosphate dehydrogenase (glpD) and
   glyceraldehyde‐3‐phosphate dehydrogenase (gap1). In addition, it
   negatively regulates succinyl‐CoA: CoA‐transferase (aarC), which plays
   a role in detoxifying acetate by converting it into acetyl‐CoA and
   succinate,^[ [101]^39 ^] further illustrating QS involved in regulating
   both primary and secondary metabolic pathways. Interestingly, there are
   pyruvate metabolisms subject to negative regulation by MupR. MupR binds
   to the promoter of pyruvate carboxylase (pycA) and pyruvate
   dehydrogenase E1 component (aceE), repressing its transcription, which
   is crucial for converting pyruvate to oxaloacetate and acyl‐CoA
   respectively,^[ [102]^40 , [103]^41 ^] an anaplerotic reaction
   replenishing TCA cycle intermediates. The malonyl CoA‐acyl carrier
   protein transacylase (fabD) that is responsible for malonyl‐CoA
   precursor flux to fatty acid biosynthesis,^[ [104]^42 ^] is repressed
   and limited by the QS system. The glutamine synthetase (GS)/glutamate
   synthase (GOGAT) cycle is critical for nitrogen assimilation,^[
   [105]^43 ^] the expression of glutamine synthetase (glnA1) and
   glutamate synthase large subunit (gltB) was repressed by MupR,
   indicating a QS regulation of nitrogen assimilation (Figure [106]2B).
   This repression of gene transcription related to nitrogen assimilation
   may decrease the availability of amino acid precursors, potentially
   leading to a reduction in pyoverdine production. MupR downregulated the
   transcript levels of respiration chain genes cyoA, nuoA, cytochrome c5
   family protein (Figure [107]2C), further suggests a metabolic
   adjustment toward enhanced respiratory chain.

Figure 2.

   Figure 2
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   The transcription factor MupR plays a key role in regulating carbon
   metabolism, amino acid metabolism, and the respiratory chain in P.
   fluorescens 2P24. A) Relative expression level of glpD, gap1, bcpA,
   aceE, fadD, acnB, sucA, sdhC, gltA, pycA, sera, and aarC as ChIP‐seq
   targets from carbon metabolism were quantified by RT‐PCR (top panel).
   The differentially expressed regulatory genes were evaluated in WT and
   ΔmupR strains, in which the reporter gene egfp was placed under the
   control of glpD, gap1, bcpA, aceE, fadD, acnB, sucA, sdhC, gltA, pycA,
   serA, and aarC promoters (bottom panel). B) Relative expression level
   of gltB, glnA1, C0J56_RS19720, gltS, and wbmI as ChIP‐seq targets from
   the amino acid metabolism were quantified by RT‐PCR (top panel). The
   differentially expressed regulatory genes were evaluated in WT and
   ΔmupR strains, in which the reporter gene egfp was placed under the
   control of gltB, glnA1, C0J56_RS19720, gltS, and wbmI promoters (bottom
   panel). C) Relative expression level of C0J56_RS25795, cyoA, nuoA, and
   C0J56_RS00200 as ChIP‐seq targets from the respiratory chain were
   quantified by RT‐PCR (top panel). The differentially expressed
   regulatory genes were evaluated in WT and ΔmupR strains, in which the
   reporter gene egfp was placed under the control of gltB, glnA1,
   C0J56_RS19720, gltS, and wbmI promoters (bottom panel). The
   fluorescence activities were measured, and illustrated the relative
   fluorescent units (RFU) that normalized to a 1 ml culture with OD[600]
   = 1. Error bars denote standard deviations (n = 3). Statistical
   analyses were performed using the t‐test and two‐way ANOVA, p < 0.0001
   is displayed as ****p < 0.001 is displayed as ***p < 0.01 is displayed
   as **p < 0.05 is displayed as *. D) This schematic represents the
   influence of MupR on the genes, metabolites, and biological pathways in
   P. fluorescens 2P24, integrating data from ChIP‐seq analyses. It
   visually categorizes genes as activated (red) or repressed (blue) by
   QS, and arrows indicate the direction of metabolic flux influenced by
   MupR. This diagram also proposes a general model for flux distribution
   in P. fluorescens 2P24.

   MupR repressed the genes involved in TCA cycle and nitrogen
   assimilation while simultaneously promoting the synthesis of key
   secondary metabolites like 2,4‐DAPG and mupirocin. In contrast, MupR
   regulation of gene involved in nitrogen assimilation and pyoverdine
   production is suppressed, likely to accommodate slower bacterial growth
   and reduced iron acquisition needs under nutrient‐limited conditions
   (Figure [109]2D). MupR regulates the transcription of genes related to
   the key carbon and nitrogen metabolisms, potentially controlling
   metabolic fluxes toward public goods production. It suggests that MupR
   is not merely a passive responder to stress but actively regulates
   metabolic pathways to maintain energy and nutrient homeostasis, playing
   a vital role in the bacterium's long‐term adaptation to dynamic
   environments.

2.3. ΔmupR Affects Gene Transcription, Extending Not Only to Public Goods but
Also from Carbon Metabolism to Nitrogen Metabolism

   Given the substantial impact of MupR on growth and public goods
   production at high cell densities in P. fluorescens 2P24, we aimed to
   explore its effects through global transcriptomic analysis. Three
   biological replicates of wild‐type 2P24 and ΔmupR were cultured to the
   early stationary phase. Total RNA was isolated and subjected to
   RNA‐seq, yielding 16.36–16.57 million reads per replicate. 41% of the
   genome was expressed in WT cells. Differential gene expression analysis
   was conducted for all transcripts that mapped onto the P. fluorescens
   2P24 genome. From the refined data set of 5546 genes, 725 genes were
   differentially regulated in the ΔmupR strain (p‐value < 0.05, log[2]
   fold change > |1.5|), corresponding to 13% of the genome. Specifically,
   61 genes were upregulated and 664 genes were downregulated in the ΔmupR
   compared to WT, as detailed in Figures [110] 3A and [111]S5 (Supporting
   Information). Notably, among the downregulated genes were 33 genes from
   the mupirocin biosynthetic gene cluster and 7 genes from the 2,4‐DAPG
   cluster. Conversely, five genes involved in pyoverdine biosynthesis
   were upregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes
   and Genomes (KEGG) pathway enrichment analyses of downregulated genes
   in ΔmupR revealed significant enrichment in crucial biological pathway.
   Notably, the metabolism pathways associated with amino acid metabolism,
   carbohydrate metabolism, fatty acid biosynthesis, ABC transporters, and
   Type II and Type III secretion systems were prominently affected
   (Figure [112]3B and Table [113]S5, Supporting Information).

Figure 3.

   Figure 3
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   MupR from P. fluorescens 2P24 as a QS transcription factor controls the
   transcriptional regulation of genes related to public goods extending
   from carbon metabolism to nitrogen metabolism. A) The comparative
   transcriptomic analysis of the ΔmupR and WT strains. Volcano plot of
   DEGs with 664 downregulated genes (red dot) and 61 upregulated genes
   (blue dot) in the ΔmupR strain compared with WT strain. The gray dots
   refer to the genes with no significant expression change. B) GO
   enrichment analysis of the differentially expressed proteins in the
   ΔmupR strain. The enriched GO terms with p < 0.05 were displayed. C)
   Summary of MupR affecting transcription of genes and related biological
   pathways in P. fluorescens 2P24. DEGs were indicated in black borders.
   The red up arrows and the blue down arrows indicate MupR‐mediated
   upregulated and downregulated genes, respectively. Metabolites
   abbreviations are as follows: G6P, glucose‐6‐phosphate; F6P,
   fructose‐6‐phosphate; FBP, fructose‐1,6bisphosphate; DHAP,
   dihydroxyacetone phosphate; 6PG, 6‐phosphogluconate; 2KDPG,
   2‐keto‐3deoxy‐6‐phosphogluconate; 2K6PG, 2‐keto‐6‐phosphogluconate;
   GAP, glyceraldehyde‐3‐phosphate; 3PG, 3‐phosphoglycerate; PEP,
   phosphoenolpyruvate; Pyr, pyruvate; AcCoA, acetyl‐coenzyme A; OAA,
   oxaloacetate; CIT, citrate; ICT, isocitrate; 2OG, 2‐ketoglutarate; SUC,
   succinate; SuCoA, succinate‐CoA; FUM, fumarate; MAL, malate. Gene
   abbreviations refer to the encoded enzymes, namely: phl, 2,4‐DAPG
   biosynthetic genes; mup, mupirocin biosynthetic genes; pvd, pyoverdine
   biosynthetic gene. cyoABE; aerobic quinol oxidase bo3 subunits; narH,
   nitrate reductase; nirQS, nitrite reductases; and norBC, nitric oxide
   reductase.

   Dihydroxy‐acid dehydratase plays a role in the biosynthesis of the
   branched‐chain amino acids valine, leucine, and isoleucine, as well as
   in the biosynthesis of pantothenate and coenzyme A (CoA),^[ [115]^44 ^]
   is downregulated in the ΔmupR mutant. The glycerate kinase, which
   converts glycerate to 2‐phospho‐glycerate in the nonphosphorylated
   Entner‐Doudoroff pathway,^[ [116]^45 ^] is notably downregulated in the
   ΔmupR mutant. In contrast, the transcription of pyruvate carboxylase,
   catalyzing the ATP‐dependent carboxylation of pyruvate to oxaloacetate
   thus enhancing the TCA cycle,^[ [117]^46 ^] was increased. In the ΔmupR
   mutant, there was a notable upregulation of genes involved in aerobic
   respiration and denitrification, indicating a significant metabolic
   shift (Figure [118]3B). This upregulation includes genes encoding the
   aerobic quinol oxidase bo3 subunits (cyoABE)^[ [119]^47 ^] and
   components of the denitrification pathway such as nitrate
   reductase‐related narH, nitrite reductases‐related nirQS, nitric oxide
   reductase (norBC), and a Crp/Fnr family transcriptional regulator.^[
   [120]^48 ^] In addition, the upregulation of ytfE and hmpA, which
   encode proteins associated with the bacterial response to oxidative and
   nitrosative stress and play roles in nitric oxide detoxification under
   aerobic conditions,^[ [121]^49 , [122]^50 ^] further suggesting a
   metabolic adjustment toward enhanced respiratory chain in the ΔmupR
   mutant. The significant downregulation and upregulation of these genes
   involved in public goods production, carbon metabolism, and nitrogen
   metabolism in the ΔmupR mutant were verified by RT‐qPCR (Figure
   [123]S6, Supporting Information).

   The ΔmupR mutant enhances gene transcription related to aerobic
   respiration, likely increasing ATP production through oxidative
   phosphorylation, which provides more energy to support rapid cellular
   growth. Concurrently, the upregulation of denitrification pathways
   facilitates the conversion of nitrate to nitrogen gas, influencing the
   bacterial redox state by balancing electron flow and maintaining redox
   homeostasis of ΔmupR mutant. This process also affects nitrogen
   cycle‐related substances, such as nitrate and nitrite, which are
   reduced and processed within the cell. Together, these metabolic
   adjustments to energy production compensate for the increased energy
   demands required for rapid cellular growth in the absence of QS
   control, with the upregulated denitrification pathway playing a pivotal
   role in maintaining cellular homeostasis (Figure [124]3C).

   Under QS control at high bacterial density, alterations of gene
   transcription in the TCA cycle that could slow energy production, along
   with shifts in carbohydrate and fatty acid metabolism, may redirect
   central carbon intermediates to enhance the synthesis of key
   carbon‐based secondary metabolites, such as 2,4‐DAPG and mupirocin.
   These metabolic adjustments, coupled with the upregulation of the
   denitrification pathway, reflect a re‐prioritization of cellular energy
   production and metabolic process. Simultaneously, the downregulation of
   amino acid assimilation pathways reduces the availability of essential
   precursors for the synthesis of key nitrogen‐based secondary
   metabolites, such as siderophore, further contributing to the rewiring
   of both carbon and nitrogen metabolism.

2.4. Quorum‐Sensing Regulator MupR Binding Site Is Required for Control of
Gene Activation and Repression

   Similar to other LuxR‐family regulators, MupR comprises an N‐terminal
   ligand‐binding domain (LBD) and a C‐terminal DNA‐binding domain (DBD),
   exhibiting 41% and 29% sequence similarity with LasR and QscR from P.
   aeruginosa, respectively (Figure [125] 4A). Structural modeling of
   MupR, predicted using AlphaFold3,^[ [126]^51 ^] reveals a
   domain‐swapping homodimer configuration. The N‐terminal LBD facilitates
   dimerization and binds AHLs, while the C‐terminal DBD features a
   canonical helix‐turn‐helix motif essential for recognizing dyad
   symmetry in DNA. The LBD is structured as an α‐β‐α sandwich comprising
   beta strands β1–β5 and alpha helices α1–α5. MupR superimposes onto QscR
   of P. aeruginosa (pdb code 3SZT) with RMSD value of 4.358 Å, indicating
   structural similarity. Moreover, 3‐oxo‐C10‐HSL is accommodated within a
   binding cavity of MupR, similar to the interaction of 3‐oxo‐C10‐HSL
   observed in QscR (Figure [127]4B). A structural model of MupR dimer was
   docked with 3‐oxo‐C10‐HSL by AutoDock vina and the AHL binding site was
   compared with those in LasR and QscR from P. aeruginosa (Figure
   [128]S7, Supporting Information). Within the N‐terminal LBD, the
   conserved residues Tyr51, Trp55, and Asp68, which are critical for AHL
   binding in LasR and QscR from P. aeruginosa, are also present in MupR.
   These residues form key interactions with the AHL molecule,
   underscoring the functional importance of this binding configuration in
   the QS mechanism.

Figure 4.

   Figure 4
   [129]Open in a new tab

   MupR is a member of the LuxR family of transcription factors. A)
   Sequence alignment of MupR with LuxR family members LasR and QscR from
   P. aeruginosa. Ligand‐binding domain (LBD) and DNA‐binding domain (DBD)
   are boxed. Residues involved in hydrogen‐bonding interactions with AHLs
   were shown in green boxes, showing the conserved key amino acids that
   mediate AHL binding across the LuxR family. B) The cartoon
   representation of AlphaFold3 predicted model of MupR dimer model. The
   two monomers are colored in purple and pink, respectively. The MupR
   superimposed on QscR in complex with 3‐oxo‐C10‐HSL (pdb code 3SZT),
   which is colored in gray. The orientation of the LBDs in MupR and QscR
   is similar. C) The model MupR_DNA complex with docked 3‐oxo‐C10‐HSL
   features monomers in green and lemon, with bound 2,4‐DAPG depicted in
   cyan. Top panel show alignments of DNA binding motifs for activated and
   repressed MupR targets promoters from ChIP‐seq data.

   This AHL‐binding and the subsequent DNA‐binding are crucial for
   regulatory role of MupR in gene expression, which is evidenced by
   validated binding sites on the promoters of target genes, leading to
   gene activation or repression. As summarized in Table [130]S4
   (Supporting Information), the distance between the binding sites and
   the transcriptional start sites (TSS) for each target gene is listed.
   MupR predominantly binds upstream of the TSS for most target genes
   (mmpB, mupF, macpC, mupO, macpE, mupI, glpD, glnA1, gltB, acnB, fabD,
   aceE, gltA, aarC, nuoA, cyoA). Interestingly, MupR bind around the ‐10
   or ‐35 box of most target genes within the mupiroicn biosynthetic
   cluster (mmpB, mupF, macpC, mupO, macpE, and mupI), leading to
   significant activation of transcription for these genes. For the target
   genes associated with amino acid metabolism (glnA1 and gltB), MupR
   bound to the upstream remote to the TSS, to repress the transcription
   of these genes. For the target genes related to carbon metabolism and
   respiratory chain, MupR exhibits more complex binding patterns. It
   binds upstream of the TSS for genes such as glpD, acnB, fabD, aceE,
   gltA, aarC, nuoA, and cyoA) or downstream of the TSS for genes such as
   sdhC, sucA and C0J56_RS00200, to repress the transciption of these
   genes. While for the target genes within the 2,4‐DAPG biosynthetic gene
   cluster (phlA and phlF), MupR binds downstream of the TSS, which
   activated phlA and repressed phlF, respectively. The validated binding
   sites of MupR at the promoters of genes were classified into two groups
   for gene activation and repression, respectively. Using AlphaFold3,^[
   [131]^51 ^] a structural model of MupR_DNA complex was generated and
   then docked with 3‐oxo‐C10‐HSL by AutoDock vina. Analysis with the MEME
   (multiple EM for motif elicitation) algorithm revealed two types of
   binding motifs derived from upregulated and downregulated MupR ChIP‐seq
   targets (Figure [132]4C; Table [133]S4 and Figure [134]S8, Supporting
   Information). Deleting these core MupR binding motifs from target gene
   promoters altered their transcriptional activity. Assessment using
   plasmid‐borne EGFP reporter fusions in both wild‐type 2P24 and ΔmupR
   strains showed these modifications hindered activation and partially
   alleviated repression of EGFP expression, confirming the critical
   nature of these motifs in gene regulation (Figure [135]S9, Supporting
   Information). This study fundamentally advances our understanding of
   the molecular mechanisms behind QS regulation in P. fluorescens 2P24,
   emphasizing the critical interaction between MupR and its DNA targets
   within the context of bacterial community.

2.5. MupR Elicits the Readjustment of Metabolic Fluxes, Rerouting Carbon Flux
to Nitrogen Metabolic Pathways

   To further elucidate the role of MupR in the metabolic network of P.
   fluorescens 2P24, key metabolites were quantified using LC‐MS/MS,
   comparing the metabolic profiles of the ΔmupR with its WT strain during
   the stationary phase. A total of 257 metabolites significantly differed
   in abundance between ΔmupR and WT (the p‐value < 0.05, variable
   importance in the projection (VIP) > 1 the metabolites are listed in
   Table [136]S6 and Figure [137]S10 (Supporting Information). The results
   confirmed a significant reduction in the levels of mupirocin and
   2,4‐DAPG in the mutant ΔmupR strain, aligning with earlier HPLC
   analyses. Notably, pyoverdine could not be quantified due to its
   unidentified molecular structure.

   The deletion of mupR was associated with increased levels of
   glucose‐6‐phosphate (G6P) and glycerol 3‐phosphate (G3P), crucial
   metabolites in the glycolysis, gluconeogenesis, and glycerophospholipid
   biosynthesis pathways (Figure [138] 5A). In addition, glutarate levels
   were elevated in the ΔmupR mutant, suggesting its catabolism through
   the glutarate hydroxylation and the glutaryl‐CoA dehydrogenation
   pathways, facilitating its entry into the TCA cycle. These changes
   indicate a potential redirection of carbon flux toward the glycolysis
   pathways and TCA cycle, underscoring a broader regulatory role for MupR
   beyond secondary metabolite synthesis. Conversely, metabolites central
   to nitrogen assimilation, such as 2‐oxoglutarate (2OG) and glutamate
   (Glu), were diminished in the mutant strain. This suggests a possible
   role for MupR in coordinating nitrogen metabolism, potentially through
   the regulation of ammonium assimilation. Moreover, nicotinamide adenine
   dinucleotide (NAD) levels were reduced in the ΔmupR mutant strain,
   impacting redox homeostasis and energy metabolism due to changes in the
   NADH/NAD ratio. This dysregulation highlights the multifaceted
   influence of MupR on bacterial metabolism. Phospholipid metabolism also
   appeared altered, with an increase in phosphatidylethanolamine (PE) and
   decreases in phosphatidylglycerol (PG), phosphatidylcholine (PC),
   phosphatidylserine (PS), and phosphatidic acid (PA), suggesting that
   mupR deletion affects membrane lipid composition. The increase in PE
   might be an adaptive response to maintain membrane integrity under
   altered metabolic conditions caused by the absence of MupR.

Figure 5.

   Figure 5
   [139]Open in a new tab

   In vivo metabolic flux distribution in P. fluorescens 2P24 controlled
   by QS. A) Volcano plot of the metabolic profile with 131 downregulated
   metabolites (red dot) and 126 upregulated metabolites (blue dot) in the
   ΔmupR strain compared with WT strain. The horizontal axis represents
   log[2]fold change > |0| in metabolite content, and the vertical axis
   represents log[10]VIP > 0, the p‐value < 0.05. B) Schematic
   illustration show that QS moderates the tricarboxylic acid (TCA) cycle
   and restricts denitrification pathways, maintaining cellular energy
   homeostasis to balance the production of public goods and private goods
   in P. fluorescens 2P24. In addition, metabolites are color‐coded to
   show increases (red) or decreases (blue) in metabolic flux, depending
   on QS activity. This diagram also proposes a general model for flux
   distribution in P. fluorescens 2P24, detailing how QS modulation
   affects metabolic pathways.

   Collectively, these findings highlight the broad impact of the mupR
   deletion on metabolic pathways in P. fluorescens 2P24, affecting
   secondary metabolite production, carbon and nitrogen metabolism,
   phospholipid metabolism, and cellular energetics, which could
   significantly influence bacterial membrane composition and overall
   cellular physiology.

3. Conclusion

   Bacterial collective sensing, often mediated through QS, enables
   individual bacteria to produce and detect signaling molecules, thereby
   synchronizing its behavior across the community. QS systems differ
   among bacterial species, reflecting evolutionary adaptations to
   specific ecological niches. In P. aeruginosa, a complex QS network
   organized into multiple interconnected systems that utilize both AHLs
   and quinolone signals, with the Las system primarily controlling
   virulence factors via the LasR receptor, the Rhl system regulating
   biofilm formation and motility through the RhlR receptor, and the PQS
   system functioning independently to influence iron acquisition and
   antibiotic resistance.^[ [140]^52 ^] In contrast, P. fluorescens
   utilizes the simpler PcoI/PcoR system,^[ [141]^53 ^] primarily involved
   in biocontrol, while B. glumae employs the TofI/TofR system and
   additional regulatory genes like qsmR, expanding its QS network beyond
   AHL signaling to include virulence factors.^[ [142]^54 ^] The
   evolutionary origin and maintenance of QS are controversial. While some
   propose that QS evolved as a form of social communication to enhance
   collective behavior and fitness,^[ [143]^2 , [144]^55 ^] others suggest
   it serves as a sensor system that allows bacteria to monitor and
   respond to a complex array of environmental signals, thereby enabling
   adaptive responses that are critical for survival, competition, and
   cooperation within ecological niches.^[ [145]^56 , [146]^57 , [147]^58
   ^]

   QS is fundamentally about sensing cell density, enabling bacteria to
   coordinate behaviors based on the population density^[ [148]^2 ^]
   However, it functions not merely as an ON‐OFF switch but as a
   sophisticated tuning mechanism, enhancing their response to varying
   physical environments.^[ [149]^58 ^] QS can finely tune various
   metabolic pathways related to nutrient acquisition and utilization.^[
   [150]^18 ^] QS in B. glumae acts as a metabolic brake, slowing down
   primary metabolism in crowded conditions to ensure homeostasis.^[
   [151]^20 ^] This involves the coordinated regulation of glucose uptake,
   energy production, and nucleotide biosynthesis, preventing metabolic
   imbalances and ensuring efficient resource utilization. In P.
   aeruginosa, QS leads to significant metabolic alterations, including
   TCA cycle changes and amino acid and fatty acid metabolism.^[ [152]^59
   ^] QS inhibitors like resveratrol can significantly alter the
   metabolome of P. aeruginosa, affecting pathways related to oxidative
   stress and energy metabolism.^[ [153]^60 ^] Histidine metabolic
   imbalance impacts the expression of type III secretion genes through QS
   pathways in P. aeruginosa, linking nitrogen metabolism to virulence
   factor production.^[ [154]^61 ^] The integration of AI‐2‐based QS with
   metabolic cues in Escherichia coli influences the expression of genes
   related to amino acid uptake and catabolism, ensuring efficient
   utilization of environmental amino acids.^[ [155]^62 ^] Similarly, QS
   in Vibrio harveyi controls the expression of genes involved in nutrient
   uptake, including those related to sugar transport and the biosynthesis
   of methionine and thiamine.^[ [156]^63 ^] Thus, QS can finely tune
   bacterial metabolism to optimize nutrient acquisition and utilization,
   ensuring that the bacterial community can adapt to changing
   environmental conditions and maintain optimal growth and survival. The
   mechanisms of QS‐regulated cooperation in the production of public
   goods, particularly in the context of the metabolism involved in
   synthesizing carbon‐ and nitrogen‐based secondary metabolites, have yet
   to be fully demonstrated in bacterial communities.

   We demonstrate that the QS system in P. fluorescens 2P24 imposes
   metabolic restrictions by regulating the expression of genes and
   metabolites, thereby maintaining the production of secondary
   metabolites within a cooperative carbon and nitrogen metabolism
   (Figure [157]5B). We integrated transcriptome, metabolome, and ChIP‐seq
   data to dissect the QS‐regulated metabolic network for secondary
   metabolites production in P. fluorescens 2P24. MupR decreases the
   levels of G6P, G3P and d‐sedoheptulose 7‐phosphate, which are
   associated with glycerol metabolism and pentose phosphate pathway, were
   significantly higher in ΔmupR mutant. Similarly, concentrations of
   UDP‐d‐galactose, glutaric acid, l‐2‐hydroxyglutaric acid,
   3‐oxo‐dodecanoic acid, as well as fatty acid metabolites such as
   (S)‐3‐hydroxyoctanoic acid, 10‐hydroxy capric acid,
   3s‐hydroxy‐dodecanoic acid were significantly decreased in ΔmupR
   mutant. Meanwhile, the concentration of S‐adenosylmethionine (SAM) and
   5′‐methylthioadenosine (5′‐MTA) that related to AHLs biosynthesis were
   substantially decreased in ΔmupR mutant (Figure [158]5A). When QS is
   active, MupR represses transcriptional levels of aceE, gltA, pycA,
   acnB, sucA, and sdhC genes which encode the key enzymes from the TCA
   cycle. MupR reduces the level of glutarate, which can be converted to
   glutaryl‐CoA and succinate by succinyl‐CoA transferase, with the
   resulting succinate being fed into the TCA cycle for energy production.
   MupR downregulates malonyl CoA‐acyl carrier protein transacylase fabD
   for reducing the fatty acid synthesis and keeps phospholipids PE at a
   low level while increasing PG, PC, PS, and PA. PE is the major
   phospholipid in Gram‐negative bacteria.^[ [159]^64 ^] This implies that
   acetyl‐CoA and malonyl‐CoA can be accumulated, facilitating the QS
   system to synthesize polyketide antibiotics such as 2,4‐DAPG and
   mupirocin. These results indicate that QS allows bacteria to restrict
   the TCA cycle and enhance the biosynthesis of lipids and amino acids,
   as these pathways are interconnected with central carbon metabolism.

   MupR repressed the gene transcriptional level of sucA gene, which
   encoded the 2‐oxoglutarate dehydrogenase E1 subunit responsible for
   converting 2OG to succinyl‐CoA.^[ [160]^65 ^] However, MupR does not
   affect isocitrate dehydrogenase, which is involved in the oxidative
   decarboxylation of isocitrate to 2OG. This indicates that these two
   steps of the TCA cycle work together to accumulate and increase 2OG
   levels. Indeed, metabolomic analysis showed that the levels of the key
   metabolite 2OG in the TCA cycle and Glu, were increased under the QS
   system. 2OG acts as a signaling molecule of nitrogen limitation, and
   regulates the activity of enzymes involved in nitrogen assimilation.^[
   [161]^66 ^] MupR represses the genes glnA1 and gltB in GS‐GOGAT pathway
   for ammonium assimilation and amino acid synthesis. The GS‐GOGAT
   pathway in bacteria is critical for assimilating ammonium into
   glutamine and glutamate, linking nitrogen metabolism with central
   carbon metabolism.^[ [162]^67 , [163]^68 ^] The accumulation levels of
   2‐OG reflect the cellular nitrogen/carbon status. This downregulation
   of ammonium assimilation genes ensures a balanced metabolic flow,
   supporting the synthesis of both carbon‐ and nitrogen‐based public
   goods, thereby maintaining metabolic homeostasis.

   MupR also downregulates genes involved in the denitrification pathway,
   including nitrate reductase‐related narH, nitrite reductases‐related
   nirQS, nitric oxide reductase (norBC), and a Crp/Fnr family
   transcriptional regulator downregulated by MupR. Additionally, MupR
   downregulates ytfE, which is associated with the bacterial response to
   oxidative and nitrosative stress,^[ [164]^49 ^] and hmpA, which plays a
   role in nitric oxide detoxification under aerobic conditions.^[
   [165]^50 ^] These downregulated genes from the denitrification pathway
   imply a metabolic shift from energy‐intensive metabolism for cell
   growth toward energy‐efficient metabolism for the production of public
   goods. We also find that the QS system maintains a low ratio of
   NADH/NAD+, indicating sufficient electron transport chain and leading
   to energy production. These findings indicate that MupR slows down the
   TCA cycle or limits denitrification pathways to maintain homeostasis
   and functions as a metabolic brake to regulate energy production for
   cellular metabolism. Specifically, the downregulation of ammonium
   assimilation and amino acid synthesis may limit the availability of
   nitrogen precursors for siderophore synthesis. Concurrently,
   carbohydrate and fatty acid metabolism alterations shift central carbon
   intermediates toward the biosynthesis of key secondary metabolites such
   as 2,4‐DAPG and mupirocin, while decelerating energy production via the
   TCA cycle.

   MupR plays a key role in regulating the balance between central
   metabolism and secondary metabolite production in P. fluorescens 2P24.
   By inhibiting respiration through the TCA cycle and denitrification
   pathways, MupR conserves energy and resources while promoting the
   synthesis of key carbon‐based secondary metabolites, including AHLs,
   2,4‐DAPG and mupirocin. In contrast, the production of nitrogen‐based
   secondary metabolites, such as siderophores, is suppressed under
   nutrient‐limited conditions, reflecting a shift in metabolic
   priorities. This metabolic reorganization helps to balance cellular
   energy demands, ensuring optimal survival in fluctuating environments.
   Our findings demonstrate that QS functions as a multifaceted regulatory
   mechanism, enabling facultative cooperation and acting as a
   sophisticated sensor system that allows bacteria to monitor their
   intracellular carbon and nitrogen status. By coordinating carbon and
   nitrogen metabolic fluxes, QS helps maintain a balanced homeostasis of
   energy and nutrients, optimizing public goods in response to
   environmental changes, thereby supporting long‐term bacterial
   adaptation.

   While the evolutionary origin of the QS system is debated, it is
   evident that the production of QS signal molecules, such as AHLs, is
   closely linked to intracellular carbon metabolism pathways. By
   modifying bacterial metabolic activities, the QS system mimics the
   effects of caloric restriction and induces the production of
   carbon‐based secondary metabolites and AHL signals. The metabolic
   feedback loops mediated by QS benefit individual bacterial cells and
   the microbial community by imposing stricter control over nutrient
   utilization and cellular energy consumption under high cell density
   conditions. In summary, the QS system may evolve from metabolic
   byproducts to an environmental sensor that ensures the homeostasis of
   carbon/nitrogen metabolism in individual cells under crowded
   conditions, making it a cooperative activity. By shedding light on the
   balance between private and public goods, our findings offer new
   insights into how QS coordinates metabolic fluxes in response to
   changing environmental conditions. This work addresses fundamental
   questions regarding the coexistence of cooperation and competition in
   microbial evolution and opens new avenues for exploring the dynamics of
   bacterial cell‐cell communication and its implications for microbial
   community behavior.

4. Experimental Section

Bacterial Strains, Plasmids, Primers, Culture Conditions, and Chemical
Compounds

   The bacterial strains and plasmids used in this study are listed in
   Table [166]S1 (Supporting Information). The primers used in this study
   are listed in Table [167]S2 (Supporting Information). Bacteria were
   grown routinely in Luria‐Bertani (LB) broth (10 g L^−1 tryptone, 5 g
   L^−1 yeast extract, 10 g L^−1 NaCl, pH 7.2) or LB agar (LB broth plus
   1.5% agar), except that P. fluorescens strains were cultured at 28 °C,
   and Escherichia coli strains were cultured at 37 °C. For the synthesis
   of secondary metabolites or AHL extraction, P. fluorescens were grown
   in King's B (KB) medium with shaking at 200 rpm. Antibiotics used for
   selection were as follows: for E. coli, ampicillin at 100 µg mL,
   gentamicin at 15 µg mL^−1, kanamycin at 30 µg mL^−1 for P. fluorescens,
   ampicillin at 100 µg mL^−1, gentamicin at 50 µg mL^−1, kanamycin at
   30 µg mL^−1. 2,4‐DAPG was purchased from Toronto Research Chemicals
   (North York, Canada); Mupirocin ointment (containing 2% mupirocin) was
   purchased from pharmacy; all the AHLs including 3‐oxo‐C[6]‐HSL,
   3‐oxo‐C[8]‐HSL, 3‐oxo‐C[10]‐HSL, and 3‐oxo‐C[12]‐HSL were purchased
   from Sigma‐Aldrich (Merck, Germany).

Construction and Complementation of P. fluorescens 2P24 Mutants

   For the generation of markerless genomic deletion mutants, a
   kanamycin‐resistance (kanR) selection and sucrose counterselection
   (sacB) process was used. This strategy provided specificity in gene
   deletions through homologous recombination while avoiding the retention
   of selection markers, ensuring a clean genomic background. The
   pK18mobsacB‐based deletion vector construct was transformed into
   chemically competent E. coli S17‐1λpir for intergenic conjugation with
   P. fluorescens 2P24. This plasmid has the pMB1 replicon, which does not
   function in P. fluorescens. Therefore, kanamycin selects for plasmids
   that were integrated into the Pseudomonas chromosome by homologous
   recombination. This vector also includes sacB that encodes levansucrase
   from Bacillus subtilis, which confers a lethal periplasmic sucrose
   polymerization in Gram‐negative bacteria. Biparental mating involved
   mixing overnight donor (E. coli S17‐1λpir) and acceptor (P.
   fluorescens) cultures in a 1:1 ratio and incubating on nonselective LB
   agar at 28 °C. Resulting colonies were selected on LB containing
   kanamycin and ampicillin for initial selection, followed by
   counterselection on 10% sucrose LB for double crossover mutants. About
   50% of excisions should contain the mutation, because the chances of
   integration and excision events occurring on either homologous arm
   flanking mutations are equal. Mutants were confirmed by PCR using
   gene‐specific primers, ensuring the right size of PCR products and
   precise deletion of the target gene without affecting flanking regions.

   Two DNA fragments flanking the mupR gene were amplified by PCR using
   primer pairs mupR‐F1/R1 to amplify 500 bp upstream of the ATG codon of
   mupR and mupR‐F2/R2 to amplify 500 bp downstream of the TAA stop codon
   of mupR. These fragments were joined by overlap extension PCR to create
   the mutator fragment for mupR gene deletion. The construct was digested
   with EcoRI and HindIII and ligated into pK18mobsacB to generate
   pK18‐ΔmupR, which was introduced into P. fluorescens 2P24. The deletion
   of mupR was confirmed by colony PCR using the external primers mupR‐F1
   and mupR‐R2. PCR products were run on a 1% agarose gel to verify the
   correct size and purity, confirming successful deletion of the mupR
   gene. A similar strategy was used for mupI deletion, with primer pairs
   mupI‐F1/R1 and mupI‐F2/R2 amplifying the flanking regions and
   generating deletion mutant of mupI. The deletion construct, pK18‐ΔmupI,
   was confirmed by PCR after introduction into P. fluorescens 2P24.
   Sequential deletion of mupR and mupI was performed to generate the
   ΔmupRΔmupI double mutant. Internal deletions of pvdL (12476 bp) and
   pvdDJI (29049 bp) were created using a similar overlap extension PCR
   strategy with respective flanking primers pvdL‐F1/R1 and pvdL‐F2/R2 or
   pvdDJI‐F1/R1 and pvdDJI F2/R2. To ensure the specificity of the gene
   deletions, colony PCR was performed on several independent colonies for
   ΔpvdL and ΔpvdDJI mutants to verify the correct size of the PCR
   products. Stability of the mutants was ensured by growing the strains
   in nonselective medium for several generations. For each strain, the
   stability of the deletion was periodically checked by colony PCR.

   For complementation, the complete open reading frames (ORFs) of target
   genes along with their upstream regulatory regions were PCR amplified
   and cloned into the broad‐host‐range vector pBBR5pemIK. For example,
   the mupR ORF and its upstream region (899 bp) were amplified using
   mupR‐C1/C2, digested with KpnI and HindIII, and ligated to pBBR5pemIK
   to create complementation construct pBBR5‐mupR. This construct was
   introduced into ΔmupR by biparental mating and the successful
   complementation was confirmed by PCR and phenotypic analysis.
   Complementation of ΔmupI and ΔmupRΔmupI was achieved using constructs
   carrying mupI or both mupR and mupI. To create a P. fluorescens strain
   expressing N‐terminally FLAG‐tagged MupR, a 3 × FLAG‐(GGGS)3 fragment
   was PCR amplified using mupRFLAG1/mupRFLAG2 and assembled with
   linearized pBBR5‐mupR using a seamless cloning kit (Sangon, China).
   This construct was introduced into ΔmupR by biparental mating.
   Successful expression of FLAG‐tagged MupR was confirmed by PCR and
   Western blotting using an anti‐FLAG antibody. The FLAG tag allowed for
   easy detection and isolation of the recombinant protein for subsequent
   functional and biochemical analyses.

Biofilm Formation Assays

   A biofilm detection experiment was performed as reported previously
   with minor modification.^[ [168]^26 ^] In brief, overnight bacterial
   culture was transferred to a 1.5‐mL EP tube containing 0.5 mL KB medium
   at an OD[600] of 0.01 and cultured statically at 28 °C for 24 h.
   Crystal violet (0.1%) was used to stain biofilm adhered to the tubes
   for 20 min. The tubes were washed thoroughly with ddH[2]O until the
   waste liquid is colorless, and the remaining crystal violet was fully
   dissolved in 200 µL of 95% ethanol and the absorbance was detected at
   570 nm.

Quantification of Mupirocin and 2,4‐DAPG

   P. fluorescens 2P24 and derivative strains were inoculated at a
   starting OD[600] of 0.02 in 50 mL King's B medium and cultured for
   60 h. After 24 h of the fermentation culture, 1 mL of culture broth was
   collected every 12 h and centrifuged at 12 000 rpm for 10 min, then the
   supernatant was filtered through 0.22 µm MCE syringe filter and further
   analyzed by high‐performance liquid chromatography (LC‐2030plus,
   SHIMADZU, Japan) equipped with a SHIMSEN Superb II C18 column (4.6 mm ×
   150 mm, 4.6 µm, SHIMADZU, Japan). To quantify the production of
   Mupirocin, sample fractions were separated isocratically by elution
   with 40:60 (vol/vol) acetonitrile‐NH[4]H[2]PO[4] (5 g L^−1) over 10 min
   at 230 nm with a flow rate of 1 mL min^−1. To quantify the production
   of DAPG, separation was achieved with mobile phase water/acetonitrile
   gradient (5%–100% acetonitrile with 0.1% TFA) over 15 min at 270 nm
   with a flow rate of 1 mL min^−1. Compared with the standard profile of
   Mupirocin and DAPG, quantification was performed by integrating the
   area under the curve at the corresponding wavelength. Data was
   processed with GraphPad Prism version 10.2.1 (GraphPad Software, USA).
   Three independent experiments were performed and the error bars were
   calculated.

Detection and Measurement of Pyoverdine Production

   To visualize the fluorescence of pyoverdine production in liquid
   cultures, strains were inoculated in 50 mL King's B medium, then
   different time‐point culture broths were collected and compared their
   fluorescences under UV light. Alternatively, the liquid version of the
   CAS assay was used, where 100 µL cell‐free supernatant or fresh King's
   B medium as a control reference was added to an equal volume of CAS
   assay solution in a 96‐well plate. After 2 h of static incubation at
   room temperature, the OD[630] of the cell‐free supernatant (A) or fresh
   King's B medium (Ar) was then measured using a microplate reader
   (SpectraMax iD3, Molecular Devices, USA). Pyoverdine induces a color
   change in CAS assay solution and pyoverdine production can thus be
   quantified by the following formula: 1‐A÷Ar. Pyoverdine‐based
   fluorescence of P. fluorescens 2P24 and derivative strains were
   quantified using a microplate reader by recording emission at 447 nm
   upon excitation at 400 nm. Pyoverdine production levels (relative
   fluorescence units, RFU) were scaled by dividing fluorescence reading
   by OD[600]. Assays were performed in at least three duplicates.

Chromatin Immunoprecipitation and ChIP‐seq Analysis

   Chromatin immunoprecipitation (ChIP) assay was performed as previously
   described but with some variations.^[ [169]^69 ^] For ChIP, four
   biological replicates of P. fluorescens 2P24 and derivative strains
   were grown under the conditions specified in the experimental design.
   ΔmupR::pBBR5‐3xFLAG‐mupR strains were grown in three 20 mL volumes of
   KB medium at 28 °C for 16 h. DNA was cross‐linked to transcription
   factors with 1% formaldehyde, and the cross‐linking was stopped by
   125 × 10^−3 m glycine. The harvest cells were washed twice with 20 mL
   Tris buffer (20 × 10^−3 m Tris‐HCl pH 7.5, 150 × 10^−3 m NaCl), then
   resuspended in 500 µL IP buffer (15 × 10^−3 m HEPES pH 8.0, 125 × 10^−3
   m NaCl, 1 × 10^−3 m EDTA, 1% Triton X‐100, 0.1% sodium deoxycholate, 1
   tablet cocktail‐inhibitors (Roche)). Chromosomal DNA was sheared by
   sonication to fragments ranging from 100 to 500 bp on average, which
   was confirmed by agarose gel electrophoresis. The samples were
   centrifuged to collect the supernatant at 12 000 rpm at 4 °C for
   10 min, after which 50 µL of each was set aside for total DNA
   extraction (input). Then 40 µL anti‐FLAG magnetic beads (Biolinkedin,
   L‐1011) were washed with 1 mL five times and added to the remaining
   supernatant. The mixtures were then incubated on a rotating wheel at 4
   °C overnight. The samples were placed on a magnetic separator to
   collect the pellets, and the collected pellets were sequentially washed
   four times with IP buffer and twice with TE buffer (10 × 10^−3 m
   Tris‐HCl pH 8.0, 1 × 10^−3 m EDTA). The pellets and 50 µL input samples
   (set aside earlier) were incubated with 100 µL elution buffer A (50 ×
   10^−3 m Tris‐HCl pH 7.6, 10 × 10^−3 m EDTA, 1% SDS) at 65 °C for
   10 min. The pellets were collected by magnetic separator and
   re‐exported with 150 µL elution buffer B (10 × 10^−3 m Tris‐HCl pH 8.0,
   1 × 10^−3 m EDTA, 0.67% SDS). The two‐step elution samples were
   combined (IP sample) and incubated at 65 °C overnight to reverse the
   cross‐links. An equal volume of proteinase K solution (0.4 mg mL^−1
   proteinase K and 0.04 mg mL^−1 glycogen in TE buffer) was added to the
   IP samples and incubated at 58 °C for 2 h. Then 55 µL 4 m LiCl was
   added to the samples and mix well. The DNA was then precipitated,
   dissolved in 25 µL nuclease‐free water, and stored for further
   analysis.

   ChIP‐seq libraries were prepared and sequenced on Illumina Hiseq or
   Novaseq by GENEWIZ, Inc. (Suzhou, China). Raw sequencing data in FASTQ
   format were processed using Cutadapt (v1.9.1) to remove adapter
   sequences, low‐quality bases (below Q20), and PCR artifacts. The clean
   reads were aligned to the genomic DNA sequence of P. fluorescens 2P24
   (Accession No. [170]NZ_CP025542.1) using the bowtie2 software (v2.2.6).
   The enriched peaks were identified using MACS2 (v2), and annotated
   using ChIPseeker (v3.11). Finally, MEME Suite analysis was performed to
   identify the MupR binding motif.

RNA‐Seq Analysis

   Overnight cultures of P. fluorescens 2P24 and ΔmupR mutant were
   inoculated into 50 mL KB medium at a final OD[600] of 0.02. For RNA‐seq
   sampling, each strain was set up with three parallel replicates. After
   20 h of incubation at 28 °C with shaking at 200 rpm, P. fluorescens
   2P24 and ΔmupR mutant was collected at the late exponential phase
   (OD[600] = 4) by centrifuging at 4 °C. RNA extraction and transcriptome
   sequencing was conducted by OE Biotech (Shanghai, China). The samples
   with an RNA integrity number of ≥7 subjected to the subsequent
   analysis. After removing rRNAs and fragmenting RNAs, cDNAs were
   synthesized and further processed for library construction. Then these
   library sequencing were performed on the Illumina HiSeq 2500 (San
   Diego, CA).

   Sequenced reads containing the adapter, poly‐N and low‐quality bases (Q
   < 20) were cleaned by Trimmomatic (v0.36). The clean reads were mapped
   onto the complete genome of the P. fluorescence 2P24 (GenBank Accession
   No. [171]NZ_CP025542.1) using Rockhopper 2 (v2). The mRNA abundance of
   genes was calculated using the reads per kilobase per million mapped
   reads (RPKM) method. The biological replicates of P. fluorescens 2P24
   and the ΔmupR mutant exhibited strong inter‐repeat correlation, with
   Pearson correlation coefficients exceeding 0.9, confirming the
   reliability and consistency of the transcriptomic data. The
   differential gene expression between P. fluorescence 2P24 and ΔmupR
   mutant (ΔmupR mutant vs wild‐type 2P24) was analyzed using the DeSeq2
   normalized method on a bioconductor platform. The transcripts with the
   adjusted P‐value < 0.05 and the absolute fold change ≥ 1.5 deemed as
   the differentially expressed genes (DEGs). Further enrichment analyses
   including GO and KEGG were performed for these DEGs.

Purification and LC‐MS Analysis of AHLs

   For AHL extraction, 10 mL overnight cultured P. fluorescens 2P24 were
   inoculated into four 200 mL volumes of King's B medium, incubated at 28
   °C with shaking at 200 rpm for different times, ΔmupI mutant was also
   inoculated as control. The whole 200 mL supernatant was extracted twice
   with equal volumes of ethyl acetate, then the combined extracts were
   evaporated to 5 mL and ultimately to dryness by lyophilization. Samples
   were dissolved in 500 µL LC/MS grade ethyl acetate.

   AHLs were then analyzed by high‐resolution mass spectrometry (HRMS).
   The LC‐MS measurements were carried out on an Accela UPLC system
   (Thermo Scientific, Germany) equipped with an Accucore C18 column
   (2.6 µm, 100 × 2.1 mm) coupled with a TSQ Quantis mass spectrometer
   (Thermo Scientific, Germany) with an electrospray ionization (ESI)
   source. The ESI was used in positive mode with the positive ion spray
   voltage set at 3.5 kV, the ion transfer tube temperature at 275 °C and
   the vaporizer temperature at 75 °C. The scan range of MS was set to m/z
   100–500 with a scan rate of 1000 Da s^−1. LC method was used as
   follows: flow rate = 0.1 mL min^−1, linear gradient 20%–100% MeCN in
   water containing 0.1% formic acid over 30 min.

Reverse Transcription‐Quantitative PCR

   P. fluorescens 2P24 and mutants were grown under the same conditions as
   those used for 2,4‐DAPG and mupirocin quantification, and 1 mL culture
   broth was collected after 20 h incubation. Total bacterial RNA was
   extracted from P. fluorescens using a bacteria RNA extraction kit
   (Vazyme, China). RNA samples were reverse‐transcribed to cDNAs using
   the HiScript III RT SuperMix for qPCR (+gDNA wiper) (Vazyme, China)
   following the manufacturer's protocol. Real‐time PCR assays were
   performed on ABI QuantStudio 6 (Thermo Scientific, Germany) with the
   AceQ Universal SYBR qPCR Master Mix (Vazyme, China). All gene threshold
   cycle (C[T] ) values were normalized to those of 16S rRNA, and the
   expression levels of genes were calculated by the 2^‐ΔΔCT method. For
   RT‐qPCR assays, experiments were set up in triplicate, with three
   technical repeats per sample.

Metabolome Analysis

   P. fluorescens 2P24 and ΔmupR mutant strain were cultured in 50 mL KB
   medium for 36 h, with seven parallel replicates for each strain.
   Culture aliquots (2 mL) were collected and normalized to the same
   OD[600]. Intracellular metabolites of P. fluorescens 2P24 and ΔmupR
   mutant were extracted as follows. The cell pellets were resuspended in
   1 mL cold methanolic solution of internal standards (4 µg mL^−1) plus
   200 µL chloroform, then the mixtures were ultrasonicated for 3 min and
   extracted at 60 Hz for 20 min, all the extraction procedures were
   performed in ice‐water. After centrifugation at 12 000 rpm, 4 °C for
   10 min, the supernatants were collected and volatilized to dryness,
   then dissolved in 300 µL methanol: water (v/v = 4:1) and filtered with
   0.22 µm strainers. The metabolite profile was analyzed with ACQUITY
   UPLC system (Waters, USA) tandem Q‐Exactive mass spectrometer system
   (Thermo Scientific, Germany), equipped with an ACQUITY UPLC HSS T3
   column (1.8 µm, 100 mm × 2.1 mm). Water (0.1% formic acid) and
   acetonitrile (0.1% formic acid) were used as mobile phase, with a
   linear gradient of 5% acetonitrile to 100% acetonitrile in water
   containing 0.1% formic acid at a flow rate of 0.35 mL min^−1. Both
   ESI‐positive and ESI‐negative ion modes were scanned ranging from 100
   to 1200 m/z, and data‐dependent acquisition (DDA) mode was applied to
   acquire data.

   The raw data were processed using Progenesis QI (v3.0, Waters, USA)
   based on public databases, including the Human Metabolome Database
   (HMDB), lipid maps (v2.3), and METLIN Database and LuMet‐Animal (3.0).
   To ensure data quality and reproducibility, multivariate and univariate
   statistical analyses were performed using the OECloud platform
   ([172]https://cloud.oebiotech.com, OE Biotech, Shanghai, China). To
   reduce the impact of noise and high variance, the data were first
   normalized and logarithmically transformed. Principal component
   analysis (PCA) was then performed to explore the overall distribution
   of the samples and to identify potential outliers. A 95% confidence
   interval in the PCA score plot was used to define the threshold for
   outlier detection. For more detailed analysis, orthogonal projections
   to latent structures‐discriminant analysis (OPLS‐DA) were applied to
   model the first principal component. To assess the robustness and
   predictive ability of the OPLS‐DA model, 200 permutation tests were
   conducted. The model's performance was evaluated using the R ^2 Y and Q
   ^2 parameters derived from sevenfold cross‐validation. The R ^2 Y value
   was 0.995, indicating strong model interpretability, while the Q ^2
   value was −0.655, suggesting the model's predictive accuracy.

   Variable importance in projection (VIP) scores were calculated to
   assess the contribution of each metabolite to the model. Metabolites
   with VIP > 1 and P‐values < 0.05 (from Student's t‐test) were
   considered significantly altered. Finally, differential metabolites
   were selected based on VIP > 1 and P‐value < 0.05, and pathway
   enrichment analysis was performed using KEGG annotations to interpret
   the biological relevance of these changes.

Transcriptional Reporter Assay

   The plasmid pSEVA225E was used for transcriptional reporter assay,
   which contains a promoterless egfp. To construct this plasmid, the
   coding region of EGFP was amplified using primer pair
   225egf‐F/225egfp‐R and the plasmid pEGFP‐N1 as a template. Then the
   resultant PCR fragment was digested with HindIII and SpeI, and ligated
   into pSEV225T (GenBank Accession No. [173]KC847299.1) to generate the
   plasmid pSEVA225E. To verify the transcriptional regulation of MupR,
   promoters of potential target genes were fused to the promoterless
   egfp. These pSEVA225E‐based reporter constructs were transferred into
   P. fluorescens 2P24 and ΔmupR separately. Strains were cultured in 5 mL
   King's B medium at 28 °C with shaking. Culture broths were collected at
   different time points, and cell pellets were washed once with sterile
   water and resuspended in sterile water. Simultaneously, 200‐µL
   suspensions of each sample were transferred to a transparent 96‐well
   plate and a black 96‐well plate. Using a microplate reader (SpectraMax
   iD3, Molecular Devices, USA), the OD[600] was measured to monitor the
   cell density, and the green fluorescens of bacteria were monitored by
   measuring emission at 535 nm with an excitation at 485 nm. For each
   measurement, the relative fluorescence unit (RFU) was scaled by
   dividing the green fluorescence value by the corresponding OD[600].
   Each data point represents the average of three technical replicates
   from three independent biological replicates.

Statistical Analysis

   Statistical analyses were performed using GraphPad Prism version
   10.2.1. A two‐way ANOVA with multiple comparisons test was used to
   assess significance between all groups. For comparisons between two
   means, a two‐tailed Student's t‐test was applied. Unless otherwise
   stated, data are presented as mean ± standard deviation (SD).

Conflict of Interest

   The authors declare no conflict of interest.

Data Availability

   Untarget metabolomic data used in this publication were deposited to
   EMBL‐EBI Metabolights database with the identifier MTBLS10731.The
   ChIP‐seq data files were submitted to the National Center for
   Biotechnology Information (NCBI) under Accession No. PRJNA1138317. The
   RNA‐seq data sets were submitted to the National Center for
   Biotechnology Information (NCBI) under Accession No. PRJNA1138253.

Supporting information

   Supporting Information
   [174]ADVS-12-2412224-s001.docx^ (13.5MB, docx)

Acknowledgements