ABSTRACT Acetylation is a broadly conserved mechanism of covalently modifying the proteome to precisely control protein activity. In bacteria, central metabolic enzymes and regulatory proteins, including those involved in virulence, can be targeted for acetylation. In this study, we directly link a putative acetylation system to metabolite-dependent virulence in the pathogen Vibrio cholerae . We demonstrate that the cobB and yfiQ genes, which encode homologs of a deacetylase and an acetyltransferase, respectively, modulate V. cholerae metabolism of acetate, a bacterially derived short-chain fatty acid with important physiological roles in a diversity of host organisms. In Drosophila melanogaster , a model arthropod host for V. cholerae infection, the pathogen consumes acetate within the gastrointestinal tract, which contributes to fly mortality. We show that deletion of cobB impairs growth on acetate minimal medium, delays the consumption of acetate from rich medium, and reduces virulence of V. cholerae toward Drosophila . These impacts can be reversed by complementing cobB or by introducing a deletion of yfiQ into the Δ cobB background. We further show that cobB controls the accumulation of triglycerides in the Drosophila midgut, which suggests that cobB directly modulates metabolite levels in vivo . In Escherichia coli K-12, yfiQ is upregulated by cAMP-cAMP receptor protein (CRP), and we identified a similar pattern of regulation in V. cholerae , arguing that the system is activated in response to similar environmental cues. In summary, we demonstrate that proteins likely involved in acetylation can modulate the outcome of infection by regulating metabolite exchange between pathogens and their colonized hosts. IMPORTANCE The bacterium Vibrio cholerae causes severe disease in humans, and strains can persist in the environment in association with a wide diversity of host species. By investigating the molecular mechanisms that underlie these interactions, we can better understand constraints affecting the ecology and evolution of this global pathogen. The Drosophila model of Vibrio cholerae infection has revealed that bacterial regulation of acetate and other small metabolites from within the fly gastrointestinal tract is crucial for its virulence. Here, we demonstrate that genes that may modify the proteome of V. cholerae affect virulence toward Drosophila , most likely by modulating central metabolic pathways that control the consumption of acetate as well as other small molecules. These findings further highlight the many layers of regulation that tune bacterial metabolism to alter the trajectory of interactions between bacteria and their hosts.
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Decoding allosteric regulation by the acyl carrier protein
Enzymes in multistep metabolic pathways utilize an array of regulatory mechanisms to maintain a delicate homeostasis [K. Magnuson, S. Jackowski, C. O. Rock, J. E. Cronan, Jr,
- NSF-PAR ID:
- 10221454
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 118
- Issue:
- 16
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- Article No. e2025597118
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Fatty acid biosynthesis (FAB) is an essential and highly conserved metabolic pathway. In bacteria, this process is mediated by an elaborate network of protein•protein interactions (PPIs) involving a small, dynamic acyl carrier protein that interacts with dozens of other partner proteins (PPs). These PPIs have remained poorly characterized due to their dynamic and transient nature. Using a combination of solution-phase NMR spectroscopy and protein-protein docking simulations, we report a comprehensive residue-by-residue comparison of the PPIs formed during FAB in
Escherichia coli . This technique describes and compares the molecular basis of six discrete binding events responsible forE. coli FAB and offers insights into a method to characterize these events and those in related carrier protein-dependent pathways. -
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This dataset contains sequence information, three-dimensional structures (from AlphaFold2 model), and substrate classification labels for 358 short-chain dehydrogenase/reductases (SDRs) and 953 S-adenosylmethionine dependent methyltransferases (SAM-MTases).
The aminoacid sequences of these enzymes were obtained from the UniProt Knowledgebase (https://www.uniprot.org). The sets of proteins were obtained by querying using InterPro protein family/domain identifiers corresponding to each family: IPR002347 (SDRs) and IPR029063 (SAM-MTases). The query results were filtered by UniProt annotation score, keeping only those with score above 4-out-of-5, and deduplicated by exact sequence matches.
The structures were submitted to the publicly available AlphaFold2 protein structure predictor (J. Jumper et al., Nature, 2021, 596, 583) using the ColabFold notebook (https://colab.research.google.com/github/sokrypton/ColabFold/blob/v1.1-premultimer/batch/AlphaFold2_batch.ipynb, M. Mirdita, S. Ovchinnikov, M. Steinegger, Nature Meth., 2022, 19, 679, https://github.com/sokrypton/ColabFold). The model settings used were msa_model = MMSeq2(Uniref+Environmental), num_models = 1, use_amber = False, use_templates = True, do_not_overwrite_results = True. The resulting PDB structures are included as ZIP archives
The classification labels were obtained from the substrate and product annotations of the enzyme UniProtKB records. Two approaches were used: substrate clustering based on molecular fingerprints and manual substrate type classification. For the substate clustering, Morgan fingerprints were generated for all enzymatic substrates and products with known structures (excluding cofactors) with radius = 3 using RDKit (https://rdkit.org). The fingerprints were projected onto two-dimensional space using the UMAP algorithm (L. McInnes, J. Healy, 2018, arXiv 1802.03426) and Jaccard metric and clustered using k-means. This procedure generated 9 clusters for SDR substrates and 13 clusters for SAM-MTases. The SMILES representations of the substrates are listed in the SDR_substrates_to_cluster_map_2DIMUMAP.csv and SAM_substrates_to_13clusters_map_2DIMUMAP.csv files.
The following manually defined classification tasks are included for SDRs: NADP/NAD cofactor classification; phenol substrate, sterol substrate, coenzyme A (CoA) substrate. For SAM-MTases, the manually defined classification tasks are: biopolymer (protein/RNA/DNA) vs. small molecule substrate, phenol subsrates, sterol substrates, nitrogen heterocycle substrates. The SMARTS strings used to define the substrate classes are listed in substructure_search_SMARTS.docx.
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Abstract Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation - an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in
Pseudomonads , that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains ofEscherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones. -
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ABSTRACT Kinetic, thermodynamic, and structural properties of the aminoglycoside
N3‐ acetyltransferase‐VIa (AAC‐VIa) are determined. Among the aminoglycosideN3 ‐acetyltransferases, AAC‐VIa has one of the most limited substrate profiles. Kinetic studies showed that only five aminoglycosides are substrates for this enzyme with a range of fourfold difference ink catvalues. Larger differences inK M(∼40‐fold) resulted in ∼30‐fold variation ink cat/K M. Binding of aminoglycosides to AAC‐VIa was enthalpically favored and entropically disfavored with a net result of favorable Gibbs energy (ΔG < 0). A net deprotonation of the enzyme, ligand, or both accompanied the formation of binary and ternary complexes. This is opposite of what was observed with several other aminoglycosideN3 ‐acetyltransferases, where ligand binding causes more protonation. The change in heat capacity (ΔCp) was different in H2O and D2O for the binary enzyme–sisomicin complex but remained the same in both solvents for the ternary enzyme–CoASH–sisomicin complex. Unlike, most other aminoglycoside‐modifying enzymes, the values of ΔCp were within the expected range of protein‐carbohydrate interactions. Solution behavior of AAC‐VIa was also different from the more promiscuous aminoglycosideN3 ‐acetyltransferases and showed a monomer‐dimer equilibrium as detected by analytical ultracentrifugation (AUC). Binding of ligands shifted the enzyme to monomeric state. Data also showed that polar interactions were the most dominant factor in dimer formation. Overall, thermodynamics of ligand‐protein interactions and differences in protein behavior in solution provide few clues on the limited substrate profile of this enzyme despite its >55% sequence similarity to the highly promiscuous aminoglycosideN3 ‐acetyltransferase. Proteins 2017; 85:1258–1265. © 2017 Wiley Periodicals, Inc.
