The YDCE protein (PDB: 1NE8) is annotated as a conserved hypothetical protein in B. subtilis with unknown function . Structural studies indicate it belongs to a family of uncharacterized proteins, though its role in permease activity remains unverified .
Feature | Detail |
---|---|
PDB Entry | 1NE8 |
Structural Genomics | NYSGXRC (New York SGX Research Center for Structural Genomics) |
Experimental Method | X-ray crystallography (2.1 Å resolution) |
Functional Keywords | "Conserved hypothetical protein ydce", "unknown function" |
During sporulation, B. subtilis upregulates genes encoding spore proteins and enzymes. While ydzL (fold change: 5744.3) is highly expressed during sporulation , no data links ydzE to this process.
Gene | Fold Change | Description |
---|---|---|
ydzL | 5744.3 | Hypothetical protein |
sspD | 5012.5 | Small acid-soluble spore protein D |
Though ydzE is not directly studied, B. subtilis is widely used for recombinant protein expression. Key systems include:
Constitutive promoters (e.g., P43, PaprE) for high-yield secretion .
Inducible systems (e.g., Pgrac, Pglv) for precise regulation .
Promoter | Type | Recombinant Protein | Yield |
---|---|---|---|
P43 | Constitutive | Trehalose synthase (TreS) | 23,080.6 ± 1,119.4 U/L |
Pgrac | Inducible | Human epidermal growth factor | 360 ± 9.41 mg/L |
KEGG: bsu:BSU05140
STRING: 224308.Bsubs1_010100002898
YdzE is a putative permease-like protein encoded by the ydzE gene in Bacillus subtilis subsp. subtilis str. 168 (Gene ID: 938121, UniProt ID: O31493) . Based on sequence analysis and structural homology, YdzE is predicted to function as a membrane transport protein involved in the selective movement of substances across the cell membrane. As a permease, it likely participates in the uptake of specific nutrients or substrates, although its precise substrate specificity has not been fully characterized. In the context of B. subtilis membrane transport systems, permeases like YdzE are part of a complex network that allows the bacterium to adapt to changing environmental conditions and nutrient availability.
For optimal expression of recombinant YdzE in E. coli systems, researchers should consider the following methodological approach:
Vector selection: Use pET expression vectors with a His-tag for efficient purification .
E. coli strain selection: BL21(DE3) or Rosetta strains are recommended for membrane proteins.
Expression conditions:
Growth temperature: 25-30°C after induction (lower than 37°C to reduce inclusion body formation)
IPTG concentration: 0.1-0.5 mM
Induction time: 4-6 hours or overnight at lower temperatures
Buffer composition for extraction: PBS buffer with mild detergents (0.5-1% n-dodecyl β-D-maltoside) is suitable for membrane protein solubilization .
For enhanced protein stability and purity (>80% as determined by SDS-PAGE), include protease inhibitors during cell lysis and purification steps .
Confirmation of successful YdzE expression requires a multi-faceted approach:
SDS-PAGE analysis: Visualize protein bands at the expected molecular weight (~57-58 kDa with His-tag) .
Western blot analysis: Use anti-His antibodies to detect His-tagged YdzE.
Mass spectrometry: Confirm protein identity through peptide mass fingerprinting or tandem MS. Expected mass for the recombinant His-tagged YdzE protein is approximately 57-58 kDa .
Activity assays: Develop functional assays based on permeases' transport capabilities.
Circular dichroism (CD): Verify proper protein folding, particularly important for membrane proteins like YdzE.
Verification Method | Expected Result for YdzE | Advantages | Limitations |
---|---|---|---|
SDS-PAGE | Band at ~57-58 kDa | Quick, simple | Low specificity |
Western blot | Specific band with anti-His antibody | High specificity | Requires antibodies |
Mass spectrometry | Matches theoretical peptide fragments | Definitive identification | Expensive, complex |
CD spectroscopy | Characteristic α-helical signature | Confirms proper folding | Not sequence-specific |
While E. coli is commonly used for recombinant protein production, expressing YdzE in its native B. subtilis offers several methodological advantages:
Natural protein folding environment: As a Gram-positive bacterium, B. subtilis provides the native membrane environment for proper folding and insertion of YdzE, potentially enhancing functional expression .
GRAS status: B. subtilis has Generally Recognized As Safe status, making downstream applications more accessible for therapeutic or food-related research .
Efficient secretion systems: B. subtilis possesses well-characterized secretion pathways that can be exploited for protein export if needed .
Natural genetic competence: B. subtilis can readily take up DNA, facilitating genomic integration of expression constructs .
Absence of endotoxins: Unlike E. coli, B. subtilis does not produce endotoxins, eliminating the need for endotoxin removal steps .
Scalability: B. subtilis can be grown to high cell densities in industrial-scale fermenters, supporting large-scale protein production .
When working with YdzE in B. subtilis, researchers should utilize inducible promoter systems such as PxylA (xylose-inducible) or Pspac (IPTG-inducible) for controlled expression, and incorporate appropriate signal peptides if secretion is desired .
Optimizing membrane solubilization for functional YdzE recovery requires systematic testing of multiple parameters:
Detergent screening methodology:
Start with a panel of detergents representing different classes: maltoside (DDM, UDM), glucoside (OG), fos-choline, and CHAPS derivatives
Test detergent concentrations at 1-5× their critical micelle concentration (CMC)
Monitor protein activity after solubilization to ensure functionality is maintained
Buffer optimization:
pH range: Test buffers from pH 6.5-8.0
Salt concentration: 100-500 mM NaCl to maintain protein stability
Glycerol content: 5-15% to enhance protein stability
Additives: Consider lipids (0.01-0.1 mg/ml) from B. subtilis membranes to maintain native-like environment
Time and temperature:
Solubilization time: 1-4 hours
Temperature: 4°C is preferred to minimize protein denaturation
Functional assessment:
Develop transport assays specific to the predicted substrate of YdzE
Compare activity before and after solubilization to calculate recovery of functional protein
Based on similar membrane protein studies, a starting buffer composition of 50 mM Tris-HCl pH 7.5, 200 mM NaCl, 10% glycerol, 1% DDM, and 0.05 mg/ml B. subtilis lipid extract is recommended for initial solubilization trials .
Addressing inclusion body formation requires a systematic approach focusing on expression conditions and protein folding:
Temperature optimization:
Lower induction temperatures (16-25°C) slow protein synthesis, allowing time for proper folding
Implement a temperature gradient experiment to determine optimal conditions
Expression kinetics control:
Reduce inducer concentration (0.01-0.1 mM IPTG)
Use tunable promoter systems like the rhamnose-inducible promoter for fine control
Co-expression with chaperones:
GroEL/GroES system assists proper folding
DnaK/DnaJ/GrpE chaperone system reduces aggregation
Methodological approach: Construct co-expression vectors containing both YdzE and chaperone genes
Fusion partners:
MBP (maltose-binding protein) enhances solubility
Thioredoxin fusion promotes proper disulfide bond formation
Cell-free expression systems:
For transmembrane proteins like YdzE, cell-free systems with added lipids or detergent micelles can improve proper folding
Refolding protocols from inclusion bodies:
Solubilize inclusion bodies with 8M urea or 6M guanidine-HCl
Perform step-wise dialysis with decreasing denaturant concentrations
Add detergents during refolding to provide hydrophobic environment for transmembrane segments
The combination of lower temperature (18°C), reduced IPTG concentration (0.1 mM), and co-expression with GroEL/GroES chaperones has been particularly effective for other B. subtilis membrane proteins and may prove successful for YdzE expression .
Determining substrate specificity for YdzE requires a multi-pronged experimental approach:
In vivo transport assays:
Construct YdzE knockout and overexpression strains in B. subtilis
Screen growth phenotypes on different carbon/nitrogen sources
Measure uptake of radiolabeled or fluorescently labeled potential substrates
Monitor intracellular accumulation using HPLC or mass spectrometry
Phylogenetic analysis:
Compare YdzE with characterized permeases in other organisms
Identify conserved substrate-binding residues through multiple sequence alignment
Construct a phylogenetic tree to position YdzE within known permease families
Structural analysis:
Homology modeling based on known permease structures
Docking simulations with potential substrates
Molecular dynamics simulations to analyze substrate-protein interactions
Site-directed mutagenesis:
Identify putative substrate-binding residues
Generate point mutations and assess impact on transport activity
Create chimeric proteins with domains from characterized permeases
Proteoliposome reconstitution:
Purify YdzE and reconstitute into liposomes
Load liposomes with potential substrates
Measure substrate transport rates under controlled conditions
By integrating these approaches, researchers can narrow down potential substrates and characterize the transport kinetics of YdzE. Based on structural similarities with other B. subtilis permeases, YdzE may be involved in peptide transport or cell wall component recycling similar to the DppE system .
Understanding YdzE's interactions with other transport components requires methodical investigation:
Co-immunoprecipitation studies:
Express epitope-tagged YdzE in B. subtilis
Perform pull-down assays to identify interacting partners
Verify interactions through reverse co-IP experiments
Bacterial two-hybrid analysis:
Clone YdzE and potential partners into bacterial two-hybrid vectors
Screen for protein-protein interactions in vivo
Quantify interaction strength using β-galactosidase assays
Membrane protein complex isolation:
Use mild detergent solubilization to preserve protein complexes
Perform blue native PAGE to separate intact complexes
Identify components by mass spectrometry
Genomic context analysis:
Fluorescence microscopy:
Create fluorescent protein fusions to visualize YdzE localization
Perform co-localization studies with other transport components
Use FRET or BiFC to detect direct protein interactions in vivo
Based on analysis of other transport systems in B. subtilis, YdzE may function as part of a complex similar to the oligopeptide permease (Opp) or dipeptide permease (Dpp) systems, potentially interacting with extracellular substrate-binding proteins and cytoplasmic ATPases .
Investigating YdzE's role in sporulation and stress response requires these methodological approaches:
Sporulation efficiency analysis:
Generate ΔydzE knockout strains
Quantify sporulation efficiency under standard conditions
Analyze morphological stages using phase-contrast microscopy
Measure expression of key sporulation genes (spo0A, sigE, sigF) by qRT-PCR
Stress response characterization:
Challenge wild-type and ΔydzE strains with various stressors:
Osmotic stress (NaCl, sorbitol)
Oxidative stress (H₂O₂, paraquat)
Nutrient limitation
Antimicrobial peptides
Measure growth rates, survival, and stress-specific gene expression
Transcriptome analysis:
Perform RNA-seq comparing wild-type and ΔydzE strains
Analyze differential gene expression during vegetative growth and sporulation
Identify affected pathways using gene ontology enrichment
Metabolite transport studies:
Complementation experiments:
Reintroduce wild-type or mutant ydzE into knockout strains
Test whether sporulation and stress response phenotypes are restored
Create chimeric proteins with domains from known sporulation-related transporters
Membrane transporters in B. subtilis, including peptide permeases like Opp and Dpp, play critical roles in nutrient scavenging during stationary phase and can influence sporulation through the transport of signaling peptides . YdzE may have similar functions, potentially contributing to cell wall peptide recycling during sporulation or mediating the transport of specific signaling molecules.
Engineering YdzE for enhanced transport requires methodical protein modification strategies:
Structure-guided mutagenesis:
Identify substrate binding pocket residues through homology modeling
Design mutations to increase binding affinity or alter specificity
Create single-point mutations using site-directed mutagenesis
Test multiple mutations systematically to identify synergistic effects
Directed evolution approach:
Generate a library of randomly mutagenized ydzE genes
Develop a selection system based on substrate transport or utilization
Screen for enhanced transport properties
Characterize selected variants by sequencing and functional assays
Domain swapping:
Identify functional domains through alignment with well-characterized permeases
Create chimeric proteins with domains from high-efficiency transporters
Test transport properties of the resulting hybrid proteins
Computational design:
Use molecular dynamics simulations to identify rate-limiting steps in transport
Apply computational protein design algorithms to optimize substrate binding
Validate in silico predictions through experimental testing
Post-translational modification engineering:
Identify native modifications that affect YdzE function
Introduce or remove modification sites to enhance stability or activity
Optimize membrane insertion efficiency through signal sequence modifications
Engineering efforts should focus on maintaining protein stability while enhancing catalytic efficiency. Based on experiences with other B. subtilis permeases, substitutions in the transmembrane domains can significantly affect substrate specificity, while modifications to cytoplasmic loops may alter interactions with ATP-binding cassette components .
Crystallizing membrane proteins like YdzE presents several challenges that require specialized methodologies:
Protein stabilization strategies:
Identify and remove flexible regions through limited proteolysis
Create fusion constructs with crystallization chaperones (T4 lysozyme, BRIL)
Generate antibody fragments (Fab, nanobodies) to stabilize specific conformations
Use disulfide engineering to lock protein in stable conformation
Detergent optimization:
Screen detergents systematically (maltoside, glucoside, neopentyl glycol classes)
Test mixed detergent systems for improved stability
Consider detergent-lipid mixtures to maintain native-like environment
Explore novel amphipathic polymers (amphipols, SMALPs) as alternatives to detergents
Lipidic cubic phase (LCP) crystallization:
Reconstitute YdzE into monoolein-based cubic phase
Optimize LCP composition with different lipids
Screen precipitants specifically designed for LCP crystallization
Implement temperature cycling to improve crystal quality
Advanced screening approaches:
Utilize robotic systems for nanoliter-scale crystallization trials
Implement in situ diffraction screening to identify microcrystals
Use second-order nonlinear imaging of chiral crystals (SONICC) for crystal detection
Explore serial crystallography at X-ray free-electron lasers (XFELs)
Alternative structural determination methods:
Cryo-electron microscopy for single-particle analysis
Solid-state NMR for specific structural elements
Hydrogen-deuterium exchange mass spectrometry for dynamics
Based on successful crystallization of other bacterial permeases and binding proteins, promising conditions for YdzE might include LCP crystallization with 1-2% (w/v) n-dodecyl-β-D-maltopyranoside supplemented with lipids, following purification protocols similar to those used for DppE and OppA .
Molecular dynamics (MD) simulations offer powerful approaches to understanding YdzE transport mechanisms:
System preparation methodology:
Construct homology model of YdzE based on related transporters
Embed protein in explicit lipid bilayer (POPC or B. subtilis membrane composition)
Solvate system with explicit water molecules and physiological ion concentrations
Apply CHARMM36 or AMBER force fields optimized for membrane proteins
Equilibrium simulation protocols:
Perform staged equilibration with progressive release of restraints
Run production simulations for microsecond timescales to capture conformational changes
Analyze protein stability, water penetration, and lipid interactions
Advanced simulation techniques:
Umbrella sampling to calculate free energy profiles of substrate transport
Steered MD to study substrate binding/unbinding pathways
Coarse-grained simulations to access longer timescales
Ensemble simulations to improve conformational sampling
Transport mechanism investigation:
Identify key residues involved in substrate recognition
Characterize conformational changes during transport cycle
Calculate energy barriers between different states
Model coupling between substrate binding and protein conformational changes
Validation experiments:
Design mutagenesis experiments to test computational predictions
Measure transport kinetics of wild-type and mutant proteins
Compare simulated and experimental structures where available
Simulation Type | Timescale | Primary Application for YdzE |
---|---|---|
All-atom MD | 100 ns - 1 μs | Detailed substrate interactions, water dynamics |
Coarse-grained MD | 1-10 μs | Large-scale conformational changes, membrane interactions |
Enhanced sampling | Variable | Energy barriers, rare events in transport cycle |
QM/MM | ps - ns | Proton transfer mechanisms if relevant to YdzE function |
Based on simulation studies of similar permeases, YdzE likely functions through an alternating access mechanism with distinct inward-facing and outward-facing conformations, potentially utilizing a rocker-switch or elevator-like movement of transmembrane domains .
When facing low expression yields of recombinant YdzE, implement this systematic troubleshooting approach:
Expression vector optimization:
Evaluate codon optimization for the expression host
Test different promoter strengths (T7, tac, ara)
Compare various fusion tags (His, MBP, SUMO) for impact on expression
Verify plasmid stability and copy number
Host strain selection:
Growth and induction conditions:
Optimize induction timing (early, mid, or late log phase)
Test range of inducer concentrations
Evaluate growth media (LB, TB, auto-induction media)
Adjust post-induction incubation temperature and duration
Protein toxicity mitigation:
Use tightly regulated expression systems
Test glucose repression for leaky promoters
Consider growth in the presence of osmolytes (betaine, sorbitol)
Evaluate co-expression with toxicity-mitigating factors
Membrane protein-specific strategies:
Add specific lipids to growth media
Include chemical chaperones (DMSO, glycerol) in culture
Test membrane-targeted expression enhancers
Consider cell-free expression systems with supplied membranes
Parameter | Initial Setting | Optimization Range | Monitoring Method |
---|---|---|---|
Induction OD₆₀₀ | 0.6 | 0.3-1.0 | Growth curves |
IPTG concentration | 0.5 mM | 0.01-1.0 mM | SDS-PAGE, Western blot |
Post-induction temperature | 37°C | 16-30°C | Protein yield, activity |
Media composition | LB | TB, 2×YT, M9 | Biomass, protein yield |
For transmembrane proteins like YdzE, successful expression often requires reducing expression rate and temperature to allow proper membrane insertion and folding. Based on experiences with similar permeases, induction at OD₆₀₀ 0.6-0.8 with 0.1 mM IPTG followed by overnight expression at 18°C often yields the best results .
Addressing inconsistent functional assay results requires meticulous attention to experimental variables:
Protein quality assessment:
Verify protein purity by SDS-PAGE and size exclusion chromatography
Confirm proper folding using circular dichroism
Assess oligomeric state with native PAGE or analytical ultracentrifugation
Examine batch-to-batch variation with activity benchmarking
Assay standardization:
Develop detailed standard operating procedures
Establish positive and negative controls for each experiment
Use internal standards to normalize between experiments
Implement statistical quality control measures
Buffer and reagent controls:
Prepare fresh buffers and substrates for each experiment
Verify pH and ionic strength before each assay
Test reagent stability over time
Use controlled storage conditions for all components
Technical parameter optimization:
Evaluate temperature dependence of the assay
Determine optimal protein concentration range
Assess time-dependence of measurements
Identify potential interfering compounds
Reconstitution consistency:
For liposome-based assays, standardize liposome preparation
Control lipid composition and protein:lipid ratios
Verify reconstitution efficiency between experiments
Assess orientation of YdzE in reconstituted systems
For membrane transport assays specifically, controlling the electrochemical gradient and membrane integrity is critical. Establishing a rigorous protocol for preparation of proteoliposomes with consistent size distribution (measured by dynamic light scattering) and internal volume can significantly reduce variability in transport measurements.
Distinguishing YdzE activity from other permeases requires sophisticated experimental design:
Genetic manipulation approaches:
Generate single and multiple permease knockout strains
Create complementation strains with controlled expression levels
Develop inducible expression systems for temporal control
Design permease-specific mutations that alter substrate specificity
Biochemical inhibition strategies:
Identify selective inhibitors through structure-based design
Develop antibodies or nanobodies specific to YdzE
Use competitive substrates to block specific transporters
Apply energy coupling inhibitors selectively
Substrate modification techniques:
Design fluorescent or radioactive substrates with specificity for YdzE
Create substrate analogs that are recognized by YdzE but not other permeases
Utilize photo-affinity labeling to identify specific binding
Develop FRET-based transport assays for real-time monitoring
Reconstitution experiments:
Purify YdzE and reconstitute into proteoliposomes
Perform transport assays with defined lipid composition
Compare activity with other purified permeases under identical conditions
Create co-reconstituted systems to study interactions between transporters
Advanced analytical methods:
Use mass spectrometry to track isotope-labeled substrates
Apply microfluidics for single-cell transport analysis
Develop biosensors for real-time detection of substrate uptake
Utilize electrophysiology for direct measurement of transport activity
B. subtilis transport systems often show functional redundancy, as observed with oligopeptide permeases (Opp), dipeptide permeases (Dpp), and other peptide transporters . By systematically varying substrate structure (size, charge, hydrophobicity) and comparing transport kinetics between wild-type and knockout strains, researchers can create substrate specificity profiles to distinguish YdzE activity from other transporters.
Leveraging YdzE in synthetic biology requires creative engineering approaches:
Biosensor development:
Engineer YdzE to transport reporter molecules upon substrate binding
Couple transport activity to transcription factor activation
Create whole-cell biosensors for environmental monitoring
Develop FRET-based sensors for real-time detection
Metabolic engineering applications:
Enhance nutrient uptake capabilities in production strains
Engineer substrate specificity for efficient transport of non-native precursors
Create synthetic transportomes with complementary specificity
Develop feedback-regulated transport systems
Protein production platforms:
Utilize YdzE secretion mechanisms for protein export
Engineer YdzE-based protein display systems
Develop self-inducing expression systems based on transport triggers
Create cell-density sensing modules based on transporter activity
Drug delivery applications:
Orthogonal communication systems:
Engineer YdzE to transport synthetic signaling molecules
Create microbial consortia with specialized communication channels
Develop cell-to-cell contact-dependent transport systems
Build cellular computing systems based on molecular transport logic
B. subtilis spores have already demonstrated value for delivering immunodominant antigens like those from Mycobacterium tuberculosis . By engineering YdzE and related transport systems, researchers could develop sophisticated cellular devices with controllable uptake and release properties for biotechnology and biomedical applications.
Computational prediction of permease specificity employs multiple bioinformatic approaches:
Sequence-based methods:
Position-specific scoring matrices from known transporters
Hidden Markov Models trained on characterized permease families
Support Vector Machines using amino acid composition features
Deep learning approaches trained on transporter-substrate pairs
Structure-based analysis:
Homology modeling using related transporters as templates
Binding site identification through conservation analysis
Molecular docking of potential substrates
Molecular dynamics simulations of substrate interaction
Genomic context analysis:
Co-occurrence patterns with substrate utilization genes
Regulon analysis to identify co-regulated genes
Phylogenetic profiling across bacterial species
Metabolic network reconstruction to predict transport requirements
Machine learning integration:
Random forest classifiers combining multiple feature types
Neural networks trained on transport assay data
Transfer learning from well-characterized transport systems
Active learning protocols to guide experimental validation
Available software and databases:
TransportDB for transporter annotation
TCDB (Transporter Classification Database) for classification
COACH-D for substrate binding site prediction
BioTransporters for specificity prediction
Computational Method | Strengths | Limitations | Validation Approach |
---|---|---|---|
Sequence homology | Simple, fast | Limited to known families | Experimental testing of top hits |
Structural modeling | Provides mechanistic insights | Depends on template quality | Site-directed mutagenesis |
Genomic context | Captures biological relevance | Incomplete for orphan transporters | Gene cluster analysis |
Machine learning | Integrates diverse data types | Requires large training sets | Cross-validation |
Based on the analysis of other B. subtilis permeases like DppE (which transports murein tripeptides ), combining structural modeling with genomic context analysis provides the most reliable predictions for substrate specificity of uncharacterized permeases like YdzE.
Comparative analysis of YdzE homologs requires an evolutionary and functional approach:
Phylogenetic analysis methodology:
Identify homologs through BLAST searches against bacterial genomes
Perform multiple sequence alignment using MUSCLE or MAFFT
Construct maximum likelihood phylogenetic trees
Map functional data onto the phylogenetic tree to identify patterns
Structural comparison approaches:
Generate homology models of YdzE homologs
Compare substrate binding pockets and transport pathways
Identify conserved and variable regions across species
Correlate structural features with substrate preferences
Experimental cross-species validation:
Express homologs in the same host for direct comparison
Perform substrate specificity profiling across homologs
Test complementation of ydzE knockouts with homologs
Develop chimeric proteins to map functional domains
Genomic context examination:
Compare operonic structures across species
Identify co-evolved transport components
Analyze associated metabolic pathways
Evaluate regulatory elements controlling expression
Environmental adaptation analysis:
Correlate transporter differences with ecological niches
Analyze selection pressures on transporter genes
Investigate horizontal gene transfer events
Examine host-pathogen interaction contexts
Permease functions can vary significantly between species based on evolutionary pressures and metabolic requirements. For example, while B. subtilis uses multiple peptide transport systems (Opp, Dpp, App) with complementary specificities for nutrient acquisition and signaling , homologous systems in pathogens may be specialized for host interaction or virulence. Similarly, the substrate specificity of DppE in B. subtilis for murein tripeptides suggests a role in cell wall recycling , which may be conserved or modified in YdzE homologs depending on cell wall composition differences between species.