| Property | Value |
|---|---|
| Amino Acid Length | 176 residues |
| Molecular Weight | ~20 kDa (calculated) |
| Sequence | MKFLFDLFPIILFFAAFKVWGIFTATAVAIVAT... |
| Tag | N-terminal His tag |
| Expression System | Escherichia coli |
| Purity | >90% (SDS-PAGE) |
| Storage | Lyophilized powder at -20°C/-80°C |
BamMC406_1828 is annotated as a probable intracellular septation protein, suggesting involvement in:
Cell Division: Mediates septum formation during bacterial replication.
Membrane Dynamics: Contains transmembrane domains (residues 1–176), indicating interactions with lipid bilayers .
Conservation: Homologs exist in other Burkholderia species, including B. cepacia and B. multivorans .
Vector: pET-based plasmid.
Induction: IPTG-driven expression in E. coli.
Buffer Composition: Tris/PBS with 6% trehalose (pH 8.0) for stability .
Phylogenetic Context: BamMC406_1828 clusters with B. ambifaria strains in core genome analyses, showing 78–84% nucleic acid identity across BCC species .
Operon Association: Co-located with genes involved in cell wall synthesis and stress response .
Pathogenicity: B. ambifaria is an opportunistic pathogen in cystic fibrosis patients, though BamMC406_1828’s direct role in virulence remains unconfirmed .
Biocontrol Potential: Environmental B. ambifaria strains (e.g., CF3) exhibit antifungal activity, suggesting septation proteins may contribute to microbial competition .
KEGG: bac:BamMC406_1828
Multiple expression systems can be employed for the recombinant production of BamMC406_1828, each with distinct advantages:
| Expression System | Advantages | Limitations |
|---|---|---|
| E. coli | High yield, rapid growth, cost-effective | Potential inclusion body formation, lack of post-translational modifications |
| Yeast | Eukaryotic modifications, good for membrane proteins | Longer expression time, complex media requirements |
| Baculovirus | High-level expression, post-translational modifications | More expensive, technically demanding |
| Mammalian cells | Native-like folding and modifications | Lowest yield, highest cost, complex protocols |
For membrane proteins like BamMC406_1828, E. coli systems often require optimization to minimize inclusion body formation. Different expression vectors incorporating various origins of replication (pMB1 or p15A) and promoters (PT7, Plac, Ptrc, Ptac, or PBAD) can be used to modulate expression levels .
When designing experiments to study BamMC406_1828 function, researchers should consider:
Expression system selection: Choose between E. coli, yeast, baculovirus, or mammalian cells based on experimental needs. For initial characterization, E. coli systems are often preferred due to simplicity and yield .
Vector design considerations:
Control experiments:
Empty vector controls to account for metabolic burden
Expression of known membrane proteins as positive controls
Non-membrane protein expression for comparison
Localization studies:
Subcellular fractionation
Fluorescent protein fusions
Immunolocalization with antibodies against tags
Functional assays:
Cell division phenotype analysis
Membrane integrity assessments
Protein-protein interaction studies
The experimental design should follow proper scientific methodology with appropriate controls, statistical analysis, and replication .
The expression system significantly impacts both yield and solubility of recombinant BamMC406_1828. Research on recombinant protein expression systems reveals several key considerations:
Impact of replication origin and promoter strength:
High-copy vectors (pMB1-derived, 500-700 copies/cell) produce higher initial protein levels but often lead to increased metabolic burden and potential aggregation
Low-copy vectors (p15A, ~10 copies/cell) may result in lower initial expression but often produce more soluble protein
Promoter selection effects:
Different promoters show varying expression patterns:
PBAD promoters require higher inducer concentrations (2 mM L-arabinose) but often show lower insoluble fraction formation
Lac-based promoters (including PT7, Ptrc, Ptac) typically require lower inducer concentrations (0.1 mM IPTG) but may produce more inclusion bodies
Growth rate and metabolic burden correlation:
Research has demonstrated an inverse relationship between growth rate and recombinant protein expression. Table below shows representative data from similar membrane protein expression:
| Vector Type | Relative Growth Rate | Relative Protein Yield | Soluble Fraction (%) |
|---|---|---|---|
| Empty strain | 1.00 | - | - |
| pMB1 origin (high-copy) | 0.65 | 100% | 45-55% |
| p15A origin (low-copy) | 0.78 | 70-80% | 60-70% |
The metabolic burden associated with transcription and translation of foreign genes involves a decrease in recombinant protein expression . For membrane proteins like BamMC406_1828, this effect is often pronounced due to additional burdens on the membrane insertion machinery.
Inclusion body formation is a common challenge when expressing membrane proteins like BamMC406_1828. Research indicates several effective troubleshooting approaches:
Optimize expression conditions:
Reduce growth temperature (18-25°C instead of 37°C)
Decrease inducer concentration (0.01-0.05 mM IPTG instead of 0.1-1 mM)
Use defined medium instead of rich medium
Implement slower induction protocols (auto-induction or gradient induction)
Modify vector design:
Switch to low-copy vectors (p15A origin) to reduce expression rate
Test weaker promoters (PBAD instead of PT7)
Add solubility-enhancing fusion partners (MBP, SUMO, Thioredoxin)
Co-express chaperones and folding modulators:
GroEL/GroES system
DnaK/DnaJ/GrpE system
Specialized membrane protein chaperones
Optimize lysis and purification:
Use mild detergents appropriate for membrane proteins
Implement step-wise solubilization protocols
Test various buffer compositions
Investigating BamMC406_1828's role in bacterial cell division requires a multi-faceted experimental approach:
Genetic manipulation studies:
Generate knockout/knockdown strains using CRISPR-Cas9 or homologous recombination
Create conditional expression systems (temperature-sensitive or inducible)
Develop point mutations in conserved domains
Implement complementation studies with wild-type and mutant variants
Microscopy-based analysis:
Phase contrast microscopy to assess cell morphology changes
Fluorescence microscopy with membrane dyes
Time-lapse imaging to observe division dynamics
Super-resolution techniques (STED, PALM, STORM) for detailed localization
Biochemical interaction studies:
Co-immunoprecipitation with known division proteins
Bacterial two-hybrid or split-GFP assays
Chemical crosslinking followed by mass spectrometry
Surface plasmon resonance or isothermal titration calorimetry
Structural studies:
Crystallography or cryo-EM (challenging for membrane proteins)
NMR for specific domains
In silico structural prediction and modeling
Cell division phenotype assessment:
Growth curve analysis under various conditions
Microscopy for cell size/shape analysis
Flow cytometry for DNA content
Specific staining of division septa
Since BamMC406_1828 is characterized as a probable intracellular septation protein, researchers should focus on its potential interactions with the divisome complex and its temporal and spatial regulation during the cell cycle .
Studying the structure-function relationship of membrane proteins like BamMC406_1828 requires specialized analytical techniques:
Structural characterization methods:
X-ray crystallography (challenging for membrane proteins)
Cryo-electron microscopy
Nuclear magnetic resonance (NMR) for specific domains
Circular dichroism (CD) for secondary structure analysis
Fourier-transform infrared spectroscopy (FTIR)
Small-angle X-ray scattering (SAXS)
Computational structure prediction (AlphaFold2 predictions are available)
Functional assays coupled with structural data:
Site-directed mutagenesis targeting specific structural elements
Cysteine scanning mutagenesis
Domain swap experiments
Truncation analysis
Membrane interaction studies:
Lipid binding assays
Fluorescence resonance energy transfer (FRET)
Atomic force microscopy
Model membrane systems (nanodiscs, liposomes)
Dynamics assessment:
Hydrogen-deuterium exchange mass spectrometry
Molecular dynamics simulations
NMR relaxation measurements
FRET-based conformational sensors
When designing these experiments, researchers should consider the membrane environment crucial for proper folding and function. Using appropriate detergents or lipid environments during purification and analysis is essential for obtaining physiologically relevant results .
Minimizing metabolic burden is crucial for optimal expression of membrane proteins like BamMC406_1828. Research suggests several strategies:
Vector and promoter optimization:
Growth condition optimization:
Host strain selection:
Use strains with enhanced membrane protein expression capabilities
Consider strains with reduced proteolytic activity
Evaluate metabolically engineered strains
Metabolic engineering approaches:
Co-express chaperones and folding factors
Optimize codon usage for reduced translational burden
Modify central carbon metabolism genes
Balance cellular resources through integrated approaches
Research has demonstrated that growth rates can decrease by up to 35% when expressing membrane proteins with high-copy vectors, indicating significant metabolic burden. Studies show that optimizing the balance between replication origin and promoter strength can lead to 2-3 fold improvements in soluble protein yield .
Validating the cellular localization and topology of BamMC406_1828 requires multiple complementary approaches:
Subcellular fractionation techniques:
Differential centrifugation to separate membrane fractions
Sucrose gradient ultracentrifugation
Detergent-based membrane protein extraction
Analysis by Western blotting with tag-specific antibodies
Fluorescence microscopy approaches:
Fluorescent protein fusions (C-terminal and N-terminal)
Split-GFP complementation assays
Immunofluorescence with tag-specific antibodies
Co-localization with known membrane markers
Topology mapping methods:
Protease accessibility assays
Cysteine labeling of accessible residues
Reporter fusion analysis (PhoA/LacZ dual reporters)
Glycosylation mapping in eukaryotic systems
Biophysical approaches:
Atomic force microscopy
Electron microscopy with immunogold labeling
Super-resolution microscopy techniques
Computational prediction validation:
Experimental testing of predicted transmembrane domains
Analysis of charge distribution and hydrophobicity
Evolutionary conservation assessment
The amino acid sequence of BamMC406_1828 suggests multiple membrane-spanning regions, with a Kyte-Doolittle hydrophobicity value of approximately -0.733, indicating its membrane protein nature . Proper experimental validation of localization should include both biochemical and imaging-based approaches for comprehensive characterization.
Investigating protein-protein interactions involving BamMC406_1828 requires specialized approaches for membrane proteins:
In vivo interaction methods:
Bacterial two-hybrid systems adapted for membrane proteins
Split-protein complementation assays (split-GFP, DHFR, luciferase)
In vivo crosslinking followed by co-immunoprecipitation
Förster resonance energy transfer (FRET) with fluorescent protein fusions
Proximity labeling approaches (BioID, APEX)
In vitro biochemical approaches:
Co-immunoprecipitation from solubilized membranes
Pull-down assays with recombinant proteins
Surface plasmon resonance (SPR) with reconstituted proteins
Isothermal titration calorimetry (ITC)
Microscale thermophoresis
Structural biology methods:
X-ray crystallography of protein complexes
Cryo-electron microscopy
Hydrogen-deuterium exchange mass spectrometry
NMR spectroscopy for specific domains
Systems biology approaches:
Genetic interaction screening
Synthetic lethality analysis
Co-expression network analysis
Computational prediction of protein-protein interactions
Functional validation:
Mutational analysis of interaction interfaces
Competitive inhibition assays
Reconstitution studies with purified components
Given that BamMC406_1828 is a probable intracellular septation protein, researchers should focus on potential interactions with other cell division proteins, membrane organization factors, and peptidoglycan synthesis machinery. The STRING database can be used to search for predicted protein-protein interactions involving BamMC406_1828 .