Recombinant Bacillus subtilis Uncharacterized N-acetyltransferase YdfB (ydfB)

What is YdfB and what is its predicted function in Bacillus subtilis?

YdfB is an uncharacterized N-acetyltransferase in Bacillus subtilis that likely belongs to the GCN5-related N-acetyltransferase (GNAT) superfamily. While its precise function remains to be fully elucidated, sequence analysis suggests it may be involved in transferring acetyl groups to specific substrates. Based on genomic context analysis, YdfB may function in metabolic regulation pathways or stress responses. Sequence homology studies with characterized acetyltransferases indicate potential roles in protein modification or metabolite detoxification . To determine its function, researchers should consider multiple approaches including gene knockout studies, substrate screening assays, and comparative proteomics between wild-type and ΔydfB strains.

How is YdfB related to other characterized systems in B. subtilis?

YdfB exists in proximity to the YdfHI two-component system, which has been shown to regulate ydfJ transcription. YdfJ belongs to the RND (resistance-nodulation-cell division) superfamily . This genomic organization suggests potential co-regulation or functional relationships within this genetic neighborhood. The YdfHI two-component system consists of a sensor kinase (YdfH) and a response regulator (YdfI) that have been shown to specifically bind to promoter regions containing a tandem repeat sequence consisting of two conserved 12-mer sequences (GCCCRAAYGTAC) . Researchers investigating YdfB should consider potential regulatory interactions with the YdfHI system through promoter analysis and transcription studies.

What expression systems are most suitable for recombinant YdfB production?

Multiple expression systems can be utilized for YdfB production, with E. coli and yeast offering the best yields and shorter turnaround times . For researchers requiring post-translational modifications necessary for correct protein folding or activity retention, expression in insect cells with baculovirus or mammalian cells is recommended . The table below summarizes the key characteristics of different expression systems for YdfB:

Selection of the appropriate system depends on research objectives, focusing on yield for structural studies or authentic modifications for functional characterization.

What are the optimal conditions for heterologous expression of YdfB in E. coli?

When expressing YdfB in E. coli, researchers should consider multiple optimization parameters:

• Strain selection: BL21(DE3) derivatives are recommended for their reduced protease activity.

• Vector design: pET-series vectors with T7 promoters and N-terminal His-tags facilitate efficient expression and purification.

• Growth conditions: Initial cultivation at 37°C until OD600 reaches 0.6-0.8, followed by induction with 0.5-1.0 mM IPTG.

• Induction parameters: Reducing temperature to 16-25°C post-induction and extending expression time to 16-20 hours significantly improves soluble protein yield.

• Media composition: Enriched media (2xYT or TB) generally yields higher biomass and protein production compared to standard LB media.

For difficult-to-express constructs, co-expression with molecular chaperones (GroEL/GroES) or fusion with solubility-enhancing tags (MBP, SUMO) may improve yield and solubility. Systematic optimization using design-of-experiments approaches, similar to those used in B. subtilis chassis engineering studies, can increase expression efficiency .

How can I purify recombinant YdfB to ensure retention of enzymatic activity?

A multi-step purification protocol designed to maintain YdfB stability and activity includes:

• Cell lysis: Sonication or high-pressure homogenization in buffer containing 50 mM Tris-HCl (pH 8.0), 300 mM NaCl, 10% glycerol, 5 mM β-mercaptoethanol, and protease inhibitors.

• Initial purification: Immobilized metal affinity chromatography (IMAC) using Ni-NTA resin with an imidazole gradient (20-300 mM).

• Secondary purification: Size exclusion chromatography using a Superdex 75/200 column equilibrated with 20 mM HEPES (pH 7.5), 150 mM NaCl, 5% glycerol, 1 mM DTT.

• Activity preservation: Addition of stabilizing agents (5 mM MgCl2, 1 mM acetyl-CoA) to storage buffer and maintaining protein concentration above 1 mg/mL.

• Storage: Flash-freezing in liquid nitrogen and storage at -80°C in small aliquots to prevent multiple freeze-thaw cycles.

Throughout the purification process, monitoring enzyme activity using acetyltransferase assays (DTNB-based colorimetric detection of CoA release) ensures that functional protein is being retained.

What genetic modification techniques are most effective for creating YdfB knockout or overexpression strains in B. subtilis?

For genetic manipulation of YdfB in B. subtilis, several proven methodologies exist:

• Gene knockout: The Cre/lox system has demonstrated high efficiency for marker removal in B. subtilis. This approach involves:

  • Amplification of upstream and downstream regions (~800 bp each) flanking ydfB

  • Fusion PCR with a lox71-zeo-lox66 fragment

  • Transformation into B. subtilis and selection for Zeor resistance

  • Marker excision using Cre recombinase

• Overexpression: Integration-based approaches are preferable for stable expression:

  • Vector construction with a strong promoter (P43 or Pspac)

  • Homologous recombination at neutral genomic loci (amyE or lacA)

  • Selection using appropriate markers (typically Kanr)

• Reporter fusion: For studying ydfB regulation:

  • Fusion of the ydfB promoter region to reporter genes (lacZ, gfp)

  • Integration at neutral genomic loci

  • Monitoring expression under various growth conditions

These genetic tools allow for comprehensive characterization of YdfB function in vivo and complement biochemical studies with recombinant protein.

How does iron availability affect YdfB expression and function in B. subtilis?

Studies of B. subtilis iron acquisition systems suggest potential connections between iron homeostasis and YdfB function. The identification of the novel Efe acquisition factor, which coordinates iron response with population density under iron-replete conditions, provides a framework for investigating YdfB in relation to iron metabolism . While direct evidence linking YdfB to iron acquisition is limited, researchers should consider:

• Expression analysis: Monitoring ydfB transcription under varying iron concentrations using qRT-PCR or reporter fusions.

• Comparative proteomics: Examining the acetylome of B. subtilis under iron-replete versus iron-limited conditions to identify YdfB-dependent acetylation patterns.

• Functional assays: Testing whether ΔydfB strains show altered growth or stress responses under iron limitation.

• Regulatory interactions: Investigating potential cross-talk between YdfB and iron-responsive transcription factors like Fur.

Researchers could leverage experimental designs similar to those used in characterizing the Efe acquisition factor, including growth in iron-depleted media supplemented with various iron sources and examination of transcriptional responses .

What structural features distinguish YdfB from other acetyltransferases, and how can these be leveraged for functional studies?

While a high-resolution structure of YdfB has not been reported in the provided literature, computational structural biology approaches can provide valuable insights:

• Homology modeling: Using crystal structures of related N-acetyltransferases as templates to generate a predicted YdfB structure.

• Active site analysis: Identifying catalytic residues through sequence alignment with characterized acetyltransferases and computational docking of acetyl-CoA.

• Substrate binding pocket characterization: Molecular dynamics simulations to identify potential substrate-binding regions and specificity determinants.

• Structure-guided mutagenesis: Design of point mutations targeting:

  • Predicted catalytic residues (typically conserved His, Tyr, Ser)

  • Substrate binding residues

  • Protein stability determinants

The structural information can then be used to design experiments testing substrate specificity, developing specific inhibitors, or engineering YdfB variants with altered catalytic properties.

How does YdfB interact with the YdfHI two-component system, and what are the implications for B. subtilis stress responses?

The YdfHI two-component system has been shown to regulate transcription through binding to a tandem repeat sequence (GCCCRAAYGTAC) in promoter regions . Investigating the relationship between YdfB and this regulatory system requires:

• Promoter analysis: Examination of the ydfB promoter region for potential YdfI binding sites using bioinformatic approaches and DNase I footprinting.

• Expression correlation: Comparing ydfB expression in wild-type and ΔydfHI strains under various growth conditions using qRT-PCR or RNA-seq.

• Protein-protein interactions: Investigating potential direct interactions between YdfB and components of the YdfHI system using bacterial two-hybrid assays, co-immunoprecipitation, or surface plasmon resonance.

• Phenotypic analysis: Comparing the phenotypes of ΔydfB, ΔydfHI, and double knockout strains under various stress conditions to identify shared or distinct response patterns.

Understanding these regulatory relationships could provide insights into the physiological roles of YdfB and its integration into B. subtilis stress response networks.

What experimental approaches can be used to identify the natural substrates of YdfB?

Identifying the natural substrates of YdfB requires a multi-faceted approach:

• In vitro substrate screening:

  • Testing acetylation of synthetic peptide libraries

  • Screening metabolite libraries using LC-MS to detect modified products

  • Activity-based protein profiling using reactive acetyl-CoA analogs

• Comparative proteomics:

  • Acetylome analysis comparing wild-type and ΔydfB strains

  • Stable isotope labeling (SILAC) to quantify acetylation differences

  • Enrichment of acetylated peptides using anti-acetyllysine antibodies

• Metabolomics approaches:

  • Untargeted metabolomics comparing wild-type and ΔydfB strains

  • Stable isotope tracing to track acetyl group transfer in vivo

  • Analysis of metabolite profiles under conditions where ydfB expression is induced

• Genetic interaction mapping:

  • Synthetic genetic array analysis to identify genes with functional relationships to ydfB

  • Suppressor screens to identify mutations that rescue ΔydfB phenotypes

  • Epistasis analysis with genes involved in related metabolic pathways

Integration of these complementary approaches increases the likelihood of identifying physiologically relevant YdfB substrates.

How can I design comprehensive phenotypic screens to elucidate YdfB function in B. subtilis?

A systematic approach to phenotypic analysis includes:

• Growth condition screening:

  • Testing growth rates in various media (minimal vs. complex)

  • Examining growth under different carbon and nitrogen sources

  • Measuring survival under stress conditions (pH, temperature, osmotic, oxidative)

• Biofilm and motility assays:

  • Quantifying biofilm formation using crystal violet staining

  • Analyzing swarming and swimming motility on semi-solid agar

  • Examining cell morphology using microscopy

• Metabolic profiling:

  • Measuring key metabolic parameters (ATP levels, NAD+/NADH ratio)

  • Analyzing central carbon flux using 13C-labeled substrates

  • Quantifying secondary metabolite production

• Antibiotic and environmental stress resistance:

  • Determining minimum inhibitory concentrations for various antibiotics

  • Measuring survival after exposure to environmental stressors

  • Assessing recovery from stationary phase or nutrient limitation

What computational tools and databases are most useful for analyzing YdfB function and evolution?

A comprehensive computational toolkit for YdfB analysis includes:

• Sequence analysis tools:

  • BLAST and PSI-BLAST for identifying homologs

  • Multiple sequence alignment tools (MUSCLE, Clustal Omega)

  • Phylogenetic analysis software (MEGA, PhyML, MrBayes)

• Structural prediction resources:

  • AlphaFold2 or RoseTTAFold for protein structure prediction

  • CASTp or POCASA for binding pocket analysis

  • HADDOCK or AutoDock for ligand docking

  • I-TASSER for template-based modeling

• Functional annotation databases:

  • InterPro and Pfam for domain identification

  • STRING for protein-protein interaction prediction

  • SubtiWiki for B. subtilis-specific information

  • BRENDA for enzyme function data

• Comparative genomics resources:

  • MicrobesOnline for genomic context analysis

  • EggNOG for orthologous group assignment

  • KEGG for metabolic pathway mapping

  • PATRIC for bacterial comparative genomics

Integration of these computational approaches with experimental data provides a robust framework for hypothesis generation and validation regarding YdfB function.

What are the most sensitive assays for measuring YdfB acetyltransferase activity?

Several complementary assays can be employed to measure YdfB activity with varying sensitivities:

• Colorimetric assays:

  • DTNB (Ellman's reagent) for detection of CoA production (detection limit: ~1-5 μM)

  • Ferric hydroxamate assay for acetylated products (detection limit: ~10 μM)

• Fluorescence-based methods:

  • Fluorescent acetyl-CoA analogs (detection limit: ~50-500 nM)

  • CPM (7-diethylamino-3-(4-maleimidophenyl)-4-methylcoumarin) for free thiol detection (detection limit: ~10-100 nM)

• Radiometric techniques:

  • [14C]- or [3H]-labeled acetyl-CoA incorporation (detection limit: ~1-10 nM)

  • Filter binding or TCA precipitation for protein substrates

• Mass spectrometry approaches:

  • Direct LC-MS/MS detection of acetylated products (detection limit: ~1-10 nM)

  • Multiple reaction monitoring (MRM) for targeted analysis

  • MALDI-TOF for intact protein mass shifts

Selection of the appropriate assay depends on the specific research question, available equipment, and the nature of potential substrates. For initial characterization, colorimetric assays offer accessibility, while MS-based methods provide the highest specificity for substrate identification.

How can isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR) be optimized for studying YdfB interactions with ligands and proteins?

Optimization of biophysical methods for YdfB interaction studies requires careful consideration of multiple parameters:

For ITC:

• Sample preparation:

  • Purified YdfB at 20-50 μM in the cell

  • Ligand concentration in the syringe at 10-20× protein concentration

  • Matched buffers with minimal heats of dilution

  • Degassing to prevent bubble formation

• Experimental parameters:

  • Temperature selection (typically 25°C)

  • Injection volume (2-10 μL)

  • Spacing between injections (180-300 seconds)

  • Stirring speed (300-400 rpm)

• Data analysis:

  • Subtraction of reference injections

  • Model selection (single-site, sequential binding, etc.)

  • Global fitting for multiple experiments

For SPR:

• Surface preparation:

  • Immobilization of YdfB via amine coupling or capture approaches

  • Surface density optimization (typically 1000-5000 RU)

  • Reference surfaces for non-specific binding correction

• Running conditions:

  • Flow rate optimization (typically 30-50 μL/min)

  • Temperature control (typically 25°C)

  • Regeneration condition screening

• Experimental design:

  • Multi-cycle kinetics vs. single-cycle kinetics

  • Concentration series (typically spanning 0.1-10× expected KD)

  • Contact and dissociation times based on expected kinetics

These biophysical techniques provide complementary information about binding thermodynamics (ITC) and kinetics (SPR), offering insights into YdfB interaction mechanisms.

What strategies can effectively determine the oligomeric state and conformational dynamics of YdfB?

Understanding YdfB's quaternary structure and conformational behavior requires multiple complementary approaches:

The data from these complementary approaches can be integrated to build a comprehensive model of YdfB's structural organization and dynamic behavior, providing insights into its mechanism of action.

How can genome-wide approaches be used to place YdfB in the context of B. subtilis physiology?

Several genome-wide methodologies can provide a systems-level understanding of YdfB function:

• Transcriptomics:

  • RNA-seq comparing wild-type and ΔydfB strains under various conditions

  • Time-course analysis during growth phases or stress responses

  • Transcript profiling in strains overexpressing ydfB

• Proteomics:

  • Global proteome analysis using quantitative mass spectrometry

  • Acetylome profiling to identify YdfB-dependent acetylation events

  • Protein turnover analysis using pulse-chase labeling

• Metabolomics:

  • Untargeted metabolite profiling in wild-type versus ΔydfB strains

  • Flux analysis using 13C-labeled carbon sources

  • Secretome analysis to identify extracellular metabolite differences

• Functional genomics:

  • Transposon sequencing (Tn-seq) to identify genetic interactions

  • CRISPRi screens for synthetic lethality/sickness

  • Suppressor screens to identify genes that compensate for ydfB deletion

Integration of these multi-omics data can position YdfB within metabolic networks and cellular processes, similar to approaches used in characterizing the lifespan engineering of B. subtilis chassis cells .

What is the relationship between YdfB and population density signaling in B. subtilis?

The connection between YdfB and population density signaling warrants investigation based on parallels with the Efe acquisition factor, which coordinates iron response with population density :

• Quorum sensing interactions:

  • Analysis of ydfB expression in response to cell density and quorum-sensing molecules

  • Testing for acetylation of quorum-sensing regulators (ComA, DegU)

  • Examination of biofilm formation and competence development in ΔydfB strains

• Secretome analysis:

  • Characterization of extracellular factors produced by wild-type versus ΔydfB strains

  • Fractionation and activity testing of conditioned media

  • Mass spectrometry identification of differentially secreted proteins/peptides

• Co-culture experiments:

  • Mixed culture growth of wild-type and ΔydfB strains to test competitive fitness

  • Cross-feeding assays to identify metabolic dependencies

  • Cell-density-dependent gene expression analysis in mixed populations

These approaches could reveal whether YdfB, like the Efe acquisition factor, participates in coordinating cellular responses with population density under specific environmental conditions.

How can I address poor solubility and stability issues when working with recombinant YdfB?

When encountering solubility or stability challenges with YdfB, consider these systematic approaches:

• Solubility enhancement strategies:

  • Fusion with solubility tags (MBP, SUMO, GST, TrxA)

  • Co-expression with molecular chaperones (GroEL/GroES, DnaK/DnaJ/GrpE)

  • Expression at lower temperatures (16-20°C)

  • Addition of solubility enhancers to lysis buffer (5-10% glycerol, 0.1-0.5% Triton X-100, 50-500 mM NaCl)

  • Testing different pH conditions (typically pH 6.5-8.5)

• Stability optimization:

  • Buffer screening (HEPES, Tris, phosphate, MES)

  • Addition of stabilizing agents:

    • Osmolytes (glycerol, sucrose, trehalose)

    • Reducing agents (DTT, β-mercaptoethanol, TCEP)

    • Divalent cations (Mg2+, Mn2+, Ca2+)

    • Ligands (acetyl-CoA, CoA)

  • Limited proteolysis to identify and remove unstable regions

  • Surface engineering to increase hydrophilicity

• Storage considerations:

  • Flash freezing in liquid nitrogen rather than slow freezing

  • Addition of cryoprotectants (10-20% glycerol)

  • Storage at high protein concentration (>1 mg/mL)

  • Avoidance of multiple freeze-thaw cycles

Systematic testing of these variables using small-scale expression and stability assays can identify optimal conditions before scaling up production.

What approaches can resolve difficulties in detecting YdfB acetyltransferase activity?

When enzymatic activity is difficult to detect, consider these troubleshooting strategies:

• Enzyme quality assessment:

  • Verify protein folding using circular dichroism or fluorescence spectroscopy

  • Confirm identity and integrity by mass spectrometry

  • Check for inhibitory contaminants using activity assays with control enzymes

  • Ensure removal of potential inhibitors during purification

• Assay optimization:

  • Screen multiple buffer systems (pH 6.0-9.0)

  • Test cofactor requirements (metal ions, reducing agents)

  • Optimize substrate concentrations (typically 1-10× expected Km)

  • Increase enzyme concentration or extend incubation time

  • Reduce background by using highly pure substrates

• Alternative detection methods:

  • If colorimetric assays fail, try more sensitive fluorescence-based approaches

  • Consider radiometric assays for highest sensitivity

  • Use mass spectrometry to directly detect acetylated products

  • Try in-gel activity assays for mixtures of potential substrates

• Substrate considerations:

  • Test a wider range of potential substrates

  • Consider that substrate may require specific modifications or cofactors

  • Evaluate whether the enzyme requires activation factors present in vivo

Systematic variation of these parameters can often reveal conditions under which activity becomes detectable.

How can contradictory results between in vitro biochemical studies and in vivo phenotypic analyses of YdfB be reconciled?

Discrepancies between in vitro and in vivo observations are common in protein characterization and can be addressed through:

• Critical evaluation of experimental conditions:

  • Assess whether in vitro conditions (pH, salt, temperature) reflect the cellular environment

  • Consider whether post-translational modifications present in vivo are missing in recombinant protein

  • Evaluate whether cofactors or interaction partners required in vivo are absent in vitro

• Complementary approaches:

  • Use cell extracts as a bridge between purified systems and in vivo conditions

  • Perform in-cell enzyme assays using cell-permeable substrates

  • Develop genetic reporters that respond to enzyme activity in vivo

• Refined hypothesis development:

  • Consider whether YdfB has multiple functions in different contexts

  • Evaluate potential moonlighting activities unrelated to acetyltransferase function

  • Assess indirect effects of YdfB deletion on cellular physiology

• Advanced in vivo approaches:

  • Use catalytically inactive YdfB mutants to distinguish enzymatic from structural roles

  • Apply rapid degradation systems to distinguish acute from adaptive effects

  • Employ cell-specific or condition-specific expression systems

Integration of results from these complementary approaches typically leads to a more nuanced understanding of protein function that reconciles apparently contradictory observations.

What are the most promising strategies for determining the physiological role of YdfB in B. subtilis?

To elucidate YdfB's physiological function, several innovative approaches show promise:

• Systematic phenotypic profiling:

  • High-throughput growth phenotyping across hundreds of conditions

  • Fitness measurements in competition assays

  • Stress resistance profiling with quantitative readouts

  • Temporal analysis across growth phases and developmental transitions

• In situ approaches:

  • CRISPR-dCas9 based transcriptional modulation for tunable expression

  • Optogenetic control of YdfB activity for temporal studies

  • Single-cell analysis to capture heterogeneity in YdfB function

  • Subcellular localization studies using fluorescent protein fusions

• Evolutionary perspectives:

  • Comparative genomics across Bacillus species

  • Experimental evolution under selective pressures

  • Phylogenetic analysis of YdfB conservation and variation

  • Investigation of horizontal gene transfer patterns

• Systems integration:

  • Multi-omics analysis integrating transcriptomics, proteomics, and metabolomics

  • Flux balance analysis incorporating YdfB activity

  • Mathematical modeling of YdfB-related pathways

  • Network-based approaches to identify functional modules

These approaches could benefit from integration with studies on iron homeostasis, given the potential connections to iron acquisition systems in B. subtilis .

How can advanced structural biology techniques be applied to understand YdfB mechanism and specificity?

Several cutting-edge structural approaches can provide mechanistic insights:

• Cryo-electron microscopy:

  • Single-particle analysis for high-resolution structure determination

  • Time-resolved studies to capture catalytic intermediates

  • Visualization of YdfB in complex with substrates or interacting partners

• Integrated structural approaches:

  • Combining X-ray crystallography, NMR, and computational modeling

  • Hydrogen-deuterium exchange mass spectrometry (HDX-MS) for conformational dynamics

  • Cross-linking mass spectrometry (XL-MS) for interaction mapping

  • Small-angle X-ray scattering (SAXS) for solution-state conformations

• Structure-guided methodologies:

  • Activity-based probes designed based on structural information

  • Rational engineering of catalytic residues and substrate binding regions

  • Design of specific inhibitors as chemical probes

  • Structure-based computational screening for substrates

• In silico approaches:

  • Molecular dynamics simulations to study conformational changes

  • Quantum mechanics/molecular mechanics (QM/MM) for reaction mechanism

  • Machine learning for prediction of substrate specificity

  • Integrative modeling combining experimental data with computational prediction

These approaches could reveal how YdfB binds and positions substrates for catalysis, informing hypotheses about its physiological function.

What potential biotechnological applications could emerge from detailed characterization of YdfB?

Understanding YdfB could lead to several applications:

• Enzyme engineering applications:

  • Development of YdfB variants with altered substrate specificity

  • Creation of biosensors for metabolite detection

  • Design of enzymatic cascades for biocatalysis

  • Incorporation into cell-free synthetic biology platforms

• B. subtilis chassis development:

  • Integration of YdfB into metabolic engineering strategies

  • Enhancement of chassis strain robustness through YdfB modulation

  • Development of tunable acetylation systems for protein regulation

  • Improvement of industrial strain performance based on YdfB function

• Therapeutic potential:

  • YdfB as a target for antimicrobial development

  • Engineering B. subtilis probiotics with modified YdfB function

  • Development of YdfB-based delivery systems for bioactive compounds

  • Exploitation of YdfB pathways for antibiotic production

• Analytical applications:

  • YdfB-based assays for metabolite detection

  • Diagnostic tools for bacterial identification

  • Environmental monitoring systems

  • Research tools for studying protein acetylation

These applications could build upon the demonstrated use of B. subtilis as a chassis for various biotechnological processes, including enzyme production and transformations of toxic substrates .