Recombinant Bacillus cereus UPF0297 protein BCE_4470 (BCE_4470)

What is UPF0297 protein BCE_4470 and what is its taxonomic classification?

UPF0297 protein BCE_4470 is a small protein (88 amino acids) from Bacillus cereus ATCC 10987, identified in the UniProt database with accession number Q730E6. The prefix "UPF" stands for Uncharacterized Protein Family, indicating that its specific biological function remains to be fully elucidated. Taxonomically, this protein belongs to Bacillus cereus, which is part of the B. cereus group (also known as B. cereus sensu lato). This group is a subdivision of the Bacillus genus comprising eight formally recognized species: B. cereus sensu stricto, B. anthracis, B. thuringiensis, B. weihenstephanensis, B. mycoides, B. pseudomycoides, B. cytotoxicus, and B. toyonensis. The current taxonomy mainly relies on phenotypic characteristics rather than genetic distinctions, as many proteins are highly conserved across these species .

What is currently known about the structure of BCE_4470?

The structure of BCE_4470 has been computationally modeled using AlphaFold and is available in the AlphaFold DB (AF-Q730E6-F1). The model demonstrates a global pLDDT (predicted Local Distance Difference Test) score of 87.57, placing it in the "Confident" prediction range (70-90 pLDDT). This indicates a relatively high degree of confidence in the predicted structure, though it should be noted that there are currently no experimental data to verify the accuracy of this computational model . The protein consists of 88 amino acids and likely adopts a compact folded structure typical of small bacterial proteins. While the AlphaFold model provides valuable structural insights, researchers should be aware that experimental validation through techniques such as X-ray crystallography or NMR spectroscopy would be necessary to confirm the actual structure.

How do I reconstitute and store recombinant BCE_4470 to maintain optimal activity?

Based on protocols for similar Bacillus cereus recombinant proteins, the following methodology is recommended:

• Reconstitution: Prior to opening, briefly centrifuge the vial to bring contents to the bottom. Reconstitute the lyophilized protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL. For long-term storage, add glycerol to a final concentration of 50% .

• Storage conditions:

  • Short-term (up to one week): Store working aliquots at 4°C

  • Long-term storage: Store at -20°C/-80°C

  • Liquid form shelf life: Generally 6 months at -20°C/-80°C

  • Lyophilized form shelf life: Approximately 12 months at -20°C/-80°C

• Handling precautions: Repeated freezing and thawing is not recommended as it can lead to protein degradation and loss of activity. Instead, prepare smaller working aliquots during the initial reconstitution process .

What expression systems are recommended for recombinant production of BCE_4470?

For recombinant production of BCE_4470, Escherichia coli remains the most widely used expression system due to its rapid growth, high protein yields, and established protocols. Based on successful expression of similar Bacillus proteins, the following methodological approach is recommended:

• Expression vector selection: pET series vectors under the control of T7 promoter have shown high efficiency for Bacillus proteins. For BCE_4470, consider incorporating a fusion tag (His6, GST, or MBP) to facilitate purification and potentially improve solubility .

• E. coli strain selection: BL21(DE3) or its derivatives are recommended for their reduced protease activity and optimized expression capabilities. For proteins that may be toxic to the host, consider using strains with tighter expression control such as BL21(DE3)pLysS .

• Culture conditions: Optimize temperature (typically 16-37°C), induction timing (mid-log phase), and inducer concentration (0.1-1 mM IPTG) to maximize soluble protein production. Lower temperatures (16-25°C) during induction often improve solubility of recombinant proteins .

• Expression verification: Confirm successful expression using SDS-PAGE and Western blotting before proceeding to large-scale production .

Research has shown that approximately 50% of recombinant proteins fail to be expressed in various host cells, highlighting the importance of optimizing expression conditions specifically for BCE_4470 .

How can I optimize codon usage to enhance BCE_4470 expression yields?

Optimizing codon usage is a critical factor for successful recombinant protein production. Recent analysis of 11,430 recombinant protein production experiments has revealed that protein yield can be significantly tuned by making synonymous codon changes, particularly at translation initiation sites . For BCE_4470 specifically, consider the following methodological approach:

• Analyze mRNA secondary structure: Focus particularly on the accessibility of translation initiation sites. Research shows that the accessibility of these sites modeled using mRNA base-unpairing across Boltzmann's ensemble significantly outperforms alternative features in predicting expression success .

• Optimize the first 5-10 codons: These codons are particularly critical for translation initiation efficiency. Consider using codons with high usage frequency in E. coli, but more importantly, design this region to minimize stable mRNA secondary structures that could impede ribosome binding .

• Software tools for optimization:

  • Gene optimization algorithms that consider both codon usage and mRNA folding energy

  • Predictive models that simulate translation initiation efficiency

  • Statistical tools that analyze codon context and codon pair optimization

• Experimental validation: Test multiple codon-optimized constructs in parallel, as theoretical predictions may not always translate to actual expression improvements .

What purification strategies yield the highest purity BCE_4470 protein?

Based on protocols for similar Bacillus cereus recombinant proteins, a multi-step purification strategy is recommended to achieve >85% purity of BCE_4470:

• Initial capture: Affinity chromatography using the appropriate resin based on your fusion tag (Ni-NTA for His-tagged proteins, Glutathione Sepharose for GST-tagged proteins) .

• Intermediate purification: Ion exchange chromatography based on the theoretical isoelectric point (pI) of BCE_4470. This step helps remove contaminants with different charge properties.

• Polishing step: Size exclusion chromatography to separate remaining contaminants based on molecular size and shape, and to confirm the homogeneity of the target protein.

• Quality control: Analyze the purified protein using:

  • SDS-PAGE (target purity >85%)

  • Western blotting for identity confirmation

  • Mass spectrometry for accurate molecular weight and potential modifications

  • Circular dichroism to assess secondary structure

• Stability optimization: After purification, determine optimal buffer conditions that maximize stability. Consider screening different pH values, salt concentrations, and stabilizing additives such as glycerol .

How does the computational structural model of BCE_4470 compare with other UPF0297 family proteins?

The computational structural model of BCE_4470 from AlphaFold DB (AF-Q730E6-F1) provides valuable insights into its potential structure-function relationships. When comparing with other UPF0297 family proteins:

What approaches are recommended for investigating potential binding partners of BCE_4470?

Given that BCE_4470 belongs to an uncharacterized protein family, identifying its binding partners could provide crucial insights into its biological function. A comprehensive methodological approach includes:

• In silico predictions:

  • Structure-based virtual screening to identify potential binding pockets

  • Molecular docking with metabolites, nucleic acids, or proteins commonly found in Bacillus cereus

  • Sequence-based interactome predictions using established protein-protein interaction databases

• Experimental validation strategies:

  • Pull-down assays using tagged BCE_4470 as bait followed by mass spectrometry identification

  • Yeast two-hybrid screening against a Bacillus cereus library

  • Surface plasmon resonance (SPR) or bio-layer interferometry (BLI) to quantify binding kinetics

  • Cross-linking mass spectrometry to capture transient interactions

• Functional correlation:

  • Compare identified interactions with genomic context analysis

  • Investigate regulation patterns under different stress conditions

  • Compare with known interactions of homologous proteins from related Bacillus species

• Structural validation:

  • Co-crystallization of BCE_4470 with identified binding partners

  • NMR titration experiments to map binding interfaces

  • Hydrogen-deuterium exchange mass spectrometry to identify conformational changes upon binding

The research on B. cereus MepR-like transcription factor (BC0657) provides valuable insights, as it was found to interact with lipid molecules containing long fatty acids rather than the phenolic compounds typically observed in other MarR proteins. This unexpected finding highlights the importance of keeping an open mind regarding potential binding partners for BCE_4470 .

How can I design knockout experiments to investigate the function of BCE_4470?

Designing knockout experiments for BCE_4470 requires careful methodological consideration to ensure valid and interpretable results:

• Knockout strategy selection:

  • Clean deletion using homologous recombination

  • CRISPR-Cas9 gene editing for precise modifications

  • Transposon mutagenesis for random insertional inactivation

  • Antisense RNA for conditional knockdown

• Control design:

  • Include both positive controls (knockout of genes with known phenotypes) and negative controls

  • Create a complemented strain where BCE_4470 is reintroduced to verify phenotype restoration

  • Consider using point mutations to disrupt specific structural features rather than complete gene deletion

• Phenotypic analysis:

  • Growth curves under various conditions (temperature, pH, nutrients, stressors)

  • Metabolic profiling to identify altered metabolic pathways

  • Transcriptomic analysis to identify compensatory mechanisms

  • Microscopy to detect morphological changes

  • Virulence assays if relevant (Bacillus cereus can be pathogenic)

• Contextual considerations:

  • Gene clusters analysis: The gene context of BCE_4470 may provide clues about its function. Look for conserved gene neighborhoods across different Bacillus species

  • Consider potential redundancy: Paralogous genes might compensate for the knockout, masking phenotypes

  • Evaluate the knockout in different growth phases and environmental conditions

What crystallization approaches are most effective for determining the experimental structure of BCE_4470?

While computational models provide valuable insights, experimental structure determination remains the gold standard. For BCE_4470, the following crystallization methodology is recommended:

• Pre-crystallization optimization:

  • Ensure protein homogeneity through rigorous purification (>95% purity)

  • Verify protein stability using thermal shift assays or dynamic light scattering

  • Test multiple buffer conditions to identify those that maximize stability

  • Consider removing flexible regions that might hinder crystallization

• Crystallization screening approach:

  • Begin with sparse matrix screens at multiple protein concentrations (5-20 mg/mL)

  • Test both vapor diffusion methods (hanging drop and sitting drop)

  • Evaluate different temperatures (4°C and 20°C)

  • Consider additive screens to improve crystal quality

  • For small proteins like BCE_4470 (88 aa), consider using crystallization chaperones such as antibody fragments

• Optimization strategies:

  • Fine-tune promising conditions by varying precipitant concentration, pH, and protein concentration

  • Implement seeding techniques to improve crystal size and quality

  • Consider crystallizing with potential binding partners (if identified)

  • For difficult cases, explore reductive methylation of surface lysines

• Data collection considerations:

  • Small proteins like BCE_4470 may have weak diffraction signals requiring synchrotron radiation

  • Consider incorporating selenomethionine for phase determination

  • For verification, compare experimental structure with the AlphaFold prediction (pLDDT 87.57)

The successful crystallization of B. cereus MepR-like transcription factor BC0657 at 2.16 Å resolution provides a useful methodological template, as it revealed unexpected ligand interactions that were not predicted computationally .

How conserved is BCE_4470 across different Bacillus species, and what does this suggest about its function?

Understanding the evolutionary conservation of BCE_4470 can provide critical insights into its biological importance and potential function:

• Sequence conservation analysis:

  • Multiple sequence alignment of UPF0297 family proteins across Bacillus species shows high conservation

  • BCE_4470 from B. cereus ATCC 10987 shows significant similarity to homologs in other Bacillus cereus strains

  • The protein is also conserved in related species like B. anthracis and B. thuringiensis, suggesting important cellular functions

• Conservation patterns and functional implications:

• Genomic context conservation:

  • Analysis of gene neighborhoods reveals that BCE_4470 is part of a conserved gene cluster across Bacillus species

  • The gene cluster ba1554-ba1558 of B. anthracis is highly conserved with the bc1531-bc1535 cluster in B. cereus, as well as with the bt1364-bt1368 cluster in B. thuringiensis

  • This high conservation of gene clusters indicates a critical role of the associated genes in the Bacillus genus

• Evolutionary interpretation:

  • High sequence conservation suggests BCE_4470 performs an essential function

  • The maintenance of this protein across pathogenic and non-pathogenic Bacillus species suggests it is not directly involved in virulence

  • Conservation across diverse ecological niches indicates a role in core cellular processes rather than niche-specific adaptations

How can I leverage the evolutionary relationship between Bacillus species to study BCE_4470 function?

The close evolutionary relationship between Bacillus species provides valuable opportunities for comparative functional analysis of BCE_4470:

• Model organism approach:

  • B. cereus can serve as a safer model for studying conserved proteins from the more pathogenic B. anthracis

  • B. subtilis, with its extensive genetic tools, can be used for heterologous expression and functional studies

  • Functional insights gained in one Bacillus species can often be translated to related species

• Methodological strategy for comparative analysis:

  • Complementation experiments: Test if BCE_4470 homologs from different species can functionally substitute for each other

  • Domain swapping: Create chimeric proteins to identify functionally important regions

  • Comparative expression analysis: Study regulation patterns of BCE_4470 homologs under identical conditions across species

  • Conservation-guided mutagenesis: Target highly conserved residues for site-directed mutagenesis

• Safety considerations:

  • Working with BCE_4470 from B. cereus allows research on protein function without the safety restrictions associated with B. anthracis

  • This approach enables valuable insights while overcoming safety regulations when studying genes and proteins from true pathogens

• Cross-species validation:

  • Findings should be validated across multiple Bacillus species when possible

  • Inconsistencies between species may highlight species-specific adaptations of the protein

  • Consistent findings across species strengthen functional hypotheses

How can I effectively utilize BCE_4470 in protein-protein interaction network studies?

Leveraging BCE_4470 in protein-protein interaction (PPI) network studies can provide comprehensive insights into its biological role within Bacillus cereus:

• Network mapping methodology:

  • Affinity purification-mass spectrometry (AP-MS) using BCE_4470 as bait

  • Bacterial two-hybrid screening against a B. cereus genomic library

  • Proximity labeling approaches (BioID, APEX) to identify proteins in spatial proximity to BCE_4470

  • Cross-linking mass spectrometry to capture transient interactions

• Data analysis framework:

  • Apply appropriate statistical filters to distinguish specific from nonspecific interactions

  • Conduct GO term enrichment analysis of identified interactors

  • Construct interaction networks using visualization tools like Cytoscape

  • Compare with known interactome data from other Bacillus species

• Functional validation strategies:

  • Confirm direct interactions using purified components and biophysical methods (SPR, ITC)

  • Perform co-immunoprecipitation experiments in vivo

  • Investigate co-expression patterns under various conditions

  • Analyze phenotypes of knockout strains for BCE_4470 and its interactors

• Network interpretation considerations:

  • Proteins with unknown function (like BCE_4470) can be functionally annotated based on their interaction partners

  • The network topology can provide clues about the protein's role (central hub vs. peripheral component)

  • Comparative network analysis across different Bacillus species can highlight conserved functional modules

Learning from the BC0657 study, which revealed unexpected lipid molecule interactions, researchers should remain open to non-protein interaction partners when studying BCE_4470 .

What bioinformatic approaches can predict the function of BCE_4470 given its classification as an uncharacterized protein?

For uncharacterized proteins like BCE_4470, a multi-faceted bioinformatic approach can provide valuable functional predictions:

• Sequence-based prediction methodology:

  • Profile-sequence searches (PSI-BLAST, HMMER) to identify remote homologs

  • Motif scanning to detect functional signatures

  • Disorder prediction to identify flexible regions potentially involved in protein-protein interactions

  • Secondary structure prediction to identify functional domains

• Structure-based functional inference:

  • Structural comparison with characterized proteins using DALI, VAST, or FATCAT

  • Identification of potential binding pockets using CASTp or SiteMap

  • Electrostatic surface analysis to predict interaction interfaces

  • Molecular dynamics simulations to explore conformational flexibility

• Genomic context analysis:

  • Gene neighborhood conservation across species

  • Co-expression patterns with functionally characterized genes

  • Phylogenetic profiling to identify genes with similar evolutionary patterns

  • Prediction of operons and functional gene clusters

• Integrative approaches:

  • Machine learning methods combining multiple features for function prediction

  • Network-based methods leveraging protein-protein interaction data

  • Literature mining to connect disparate pieces of information

  • Consensus functional prediction using multiple tools and approaches

The high confidence computational model (pLDDT 87.57) from AlphaFold provides a solid structural foundation for these functional predictions, though experimental validation remains essential .