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.
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.
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.
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.
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.
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.
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.
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.
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.