Recombinant Bacillus cereus UPF0754 membrane protein BCG9842_B4423 (BCG9842_B4423)

What is Bacillus cereus UPF0754 membrane protein BCG9842_B4423?

Bacillus cereus UPF0754 membrane protein BCG9842_B4423 is a full-length transmembrane protein consisting of 378 amino acids. It belongs to the UPF0754 protein family, which comprises uncharacterized protein family 0754, a group of proteins with currently unknown functions. The protein is encoded by the BCG9842_B4423 gene and has been identified in the membrane proteome of Bacillus cereus, a gram-positive, spore-forming bacterium known for its role as a food-borne pathogen . The protein contains several hydrophobic regions consistent with its membrane localization and is expressed in both vegetative cells and spores of B. cereus, though with differential expression patterns .

How should Recombinant BCG9842_B4423 protein be stored and reconstituted?

Proper storage and reconstitution are critical for maintaining protein activity. Based on manufacturer recommendations, the following protocol should be followed:

Storage Conditions:

• Store lyophilized protein at -20°C/-80°C upon receipt

• Aliquot the protein to avoid repeated freeze-thaw cycles

• For working aliquots, store at 4°C for up to one week

• For extended storage, conserve at -20°C or -80°C

Reconstitution Protocol:

• Briefly centrifuge the vial prior to opening to bring contents to the bottom

• Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% (50% is recommended by default)

• Aliquot for long-term storage at -20°C/-80°C

The reconstituted protein is typically stored in Tris/PBS-based buffer with 6% Trehalose at pH 8.0, which helps maintain stability .

What expression systems are used for producing Recombinant BCG9842_B4423?

Recombinant BCG9842_B4423 protein is typically produced using E. coli expression systems. The gene sequence encoding the full-length protein (1-378 amino acids) is cloned into an appropriate expression vector, which is then transformed into E. coli. The expressed protein is commonly fused with an N-terminal His tag to facilitate purification through affinity chromatography .

This in vitro E. coli expression system offers several advantages:

• High yield of recombinant protein

• Cost-effective production

• Well-established protocols for induction and purification

• Compatibility with various fusion tags for detection and purification

It's important to note that while E. coli is the most common expression system, the hydrophobic nature of membrane proteins can sometimes present challenges for proper folding and solubility .

How does the expression of BCG9842_B4423 differ between vegetative cells and spores of Bacillus cereus?

The expression of membrane proteins, including UPF0754 family proteins like BCG9842_B4423, shows significant differences between vegetative cells and spores of Bacillus cereus. Quantitative proteomics studies have revealed distinct membrane proteome profiles in these two life phases:

Comparative Expression:

Analysis of membrane proteins quantifiable in both spore inner membrane and vegetative cell membrane shows that most membrane proteins, including transporters, receptors, and proteins related to cell division and motility, have significantly higher expression levels in vegetative cell membranes compared to spore inner membranes .

Statistical Distribution:

Out of 190 predicted membrane proteins quantifiable in both phases, only 6 proteins (3.2%) had significantly elevated levels in spore inner membranes, while 63 proteins (33.2%) showed remarkably elevated levels in vegetative cell membranes .

Functional Categorization:

The proteins with higher expression in spore inner membranes were primarily metabolic enzymes and integral membrane and adhesion proteins. In contrast, proteins with increased expression in vegetative cell membranes had a broader functional scope, including transporters, cellular motility proteins, metabolic enzymes, and environmental perception proteins .

These differences reflect the distinct physiological roles of membranes in dormant spores versus actively growing vegetative cells, with spore membranes specialized for long-term survival and specific germination responses.

What methods are recommended for enrichment and analysis of BCG9842_B4423 from Bacillus cereus membranes?

Membrane proteins like BCG9842_B4423 present unique challenges for isolation and analysis due to their hydrophobic nature and relatively low abundance compared to cytosolic proteins. Based on successful approaches with B. cereus membrane proteomics, the following methods are recommended:

Membrane Enrichment Protocol:

• Harvest cells or spores by centrifugation

• Disrupt cells/spores using mechanical methods (e.g., bead-beating or sonication)

• Remove debris by low-speed centrifugation

• Collect membranes by ultracentrifugation

• Wash membrane pellet to remove associated proteins

• Extract membrane proteins using appropriate detergents

Mass Spectrometry Analysis:

• Perform in-gel or in-solution tryptic digestion of membrane protein samples

• Analyze peptides using LC-MS/MS (liquid chromatography-tandem mass spectrometry)

• Identify proteins using database searching against B. cereus protein databases

• Apply bioinformatics filtering to identify true membrane proteins (using tools like TMHMM, SignalP, and LipoP)

Bioinformatics Validation:

After identification, use prediction tools to confirm membrane localization:

• TMHMM for transmembrane helix prediction

• SignalP for signal peptide prediction

• LipoP for lipoproteins

• BOMP for beta-barrel outer membrane proteins

This combined approach has successfully identified hundreds of membrane proteins from B. cereus, demonstrating its efficacy for studying proteins like BCG9842_B4423.

What structural features characterize the BCG9842_B4423 protein, and how do they relate to potential functions?

The BCG9842_B4423 protein exhibits several structural features that provide insights into its potential membrane-associated functions:

Transmembrane Topology:

Bioinformatic analysis of the amino acid sequence reveals multiple predicted transmembrane helices, consistent with its classification as an integral membrane protein. The C-terminal region particularly shows a characteristic pattern of hydrophobic residues (LLGGIIGLVQGLLLLFLR) typical of transmembrane domains .

Domain Organization:

While specific domains have not been fully characterized for this UPF0754 family protein, the sequence contains regions that suggest:

• N-terminal cytoplasmic domain (likely involved in protein-protein interactions)

• Multiple transmembrane spans (forming membrane-embedded structure)

• Intervening loop regions (potentially involved in substrate binding or signal transduction)

Structural Homology:

While direct structural data (e.g., X-ray crystallography or cryo-EM) is not reported in the provided search results, homology modeling based on related proteins might suggest a multi-pass membrane protein architecture with potential channel, transporter, or receptor functions.

Functional Implications:

The structural features suggest potential roles in:

• Small molecule or ion transport across membranes

• Sensing environmental changes (signaling)

• Maintaining membrane integrity during sporulation and germination

• Metabolite uptake during early stages of spore germination

Further structural studies, including crystallography or advanced biophysical techniques, would be valuable to fully elucidate the structure-function relationship of this protein.

How can researchers effectively analyze the role of BCG9842_B4423 in Bacillus cereus spore germination?

Investigating the role of BCG9842_B4423 in spore germination requires a multi-faceted approach combining genetic, biochemical, and physiological methods:

Genetic Approaches:

• Generate knockout or knockdown mutants using CRISPR-Cas9 or traditional homologous recombination

• Create conditional expression strains using inducible promoters

• Construct fluorescently tagged variants for localization studies

• Perform complementation studies to confirm phenotypes are due to the specific gene

Germination Assays:

• Compare germination kinetics between wild-type and mutant strains using:

  • Optical density measurements (OD600 decrease during germination)

  • Phase-contrast microscopy (loss of phase brightness)

  • Dipicolinic acid (DPA) release assays

  • Spore heat resistance tests

• Test germination in response to different germinants, as membrane proteins like BCG9842_B4423 might be involved in nutrient recognition or signaling

Protein Interaction Studies:

• Use pull-down assays with His-tagged recombinant protein to identify interaction partners

• Employ bacterial two-hybrid systems to verify protein-protein interactions

• Perform co-immunoprecipitation followed by mass spectrometry to identify complexes in vivo

Physiological Characterization:

Assess whether the protein is involved in:

• Germinant recognition (like GerA, GerB, GerK receptor families)

• Signal transduction during germination

• Metabolite transport required for outgrowth

• Membrane remodeling during the transition from dormant spore to vegetative cell

These approaches, especially when combined, can provide comprehensive insights into the functional role of BCG9842_B4423 in the complex process of spore germination.

What are the optimal conditions for assaying BCG9842_B4423 protein activity?

Assaying the activity of membrane proteins like BCG9842_B4423 presents unique challenges due to their hydrophobic nature and requirement for a lipid environment. While specific activity assays for this uncharacterized protein are not detailed in the search results, general methodological principles can be applied:

Buffer Conditions:

• pH: Test a range from 6.0-8.0, with emphasis on physiological pH 7.0-7.5

• Ionic strength: 100-300 mM NaCl or KCl

• Divalent cations: Include 1-5 mM MgCl₂ and/or CaCl₂

• Reducing agents: 0.5-2 mM DTT or β-mercaptoethanol to maintain cysteine residues

• Glycerol: 5-10% to enhance stability

Membrane Mimetic Systems:

• Detergent micelles: Use mild detergents like DDM, LMNG, or CHAPS

• Proteoliposomes: Reconstitute protein into liposomes composed of E. coli lipids or synthetic mixtures

• Nanodiscs: Incorporate protein into nanodiscs with MSP proteins and appropriate lipids

• GUVs (Giant Unilamellar Vesicles): For functional studies requiring larger membrane systems

Activity Measurement Approaches:

Since the specific function of BCG9842_B4423 is not well-characterized, consider multiple approaches:

• Transport assays (if it functions as a transporter)

• Binding assays with potential ligands

• ATPase or GTPase activity (if it has associated enzymatic functions)

• Conformational change assays (fluorescence-based or using EPR)

Quality Control:

• Circular dichroism to confirm proper folding

• Size-exclusion chromatography to verify monodispersity

• Western blotting to confirm protein integrity

These approaches provide a framework for developing specific activity assays once the functional characteristics of BCG9842_B4423 become better understood through comparative genomics and initial experimental characterization.

How should researchers present and analyze data when comparing BCG9842_B4423 expression across different experimental conditions?

Proper data presentation and analysis are crucial for meaningful interpretation of BCG9842_B4423 expression studies. Following standardized approaches enhances clarity and facilitates comparison between different experimental conditions:

Data Collection and Organization:

• Experimental Design Considerations:

  • Include appropriate biological and technical replicates (minimum n=3)

  • Incorporate relevant controls (positive, negative, loading controls)

  • Use standardized protocols for protein extraction and quantification

• Quantification Methods:

  • For Western blot: Densitometry with normalization to loading controls

  • For qPCR: Relative quantification with reference genes

  • For proteomics: Label-free quantification or isotope labeling approaches

Data Presentation:

• Tables for Numerical Data:
  Create tables that include:

  • Mean expression values with standard deviations/standard errors

  • Statistical significance indicators (p-values)

  • Fold-change values relative to control conditions

  Experimental Condition	Mean Expression Level	Standard Deviation	Fold Change vs Control	p-value
  Control	1.00	±0.12	1.00	--
  Condition A	2.45	±0.31	2.45	0.002
  Condition B	0.63	±0.09	0.63	0.018
  Condition C	3.17	±0.42	3.17	<0.001

• Bar Charts for Visual Comparison:

  • Use grouped bar charts for multiple conditions

  • Include error bars representing standard deviation or standard error

  • Indicate statistical significance with asterisks or letters

  • Use consistent color coding across related figures

  • Clearly label axes and include appropriate units

• Heat Maps for Multi-Condition Comparisons:

  • Use color intensity to represent expression levels

  • Organize conditions and related proteins logically

  • Include dendrograms if performing hierarchical clustering

Statistical Analysis:

• Appropriate Statistical Tests:

  • For two-group comparisons: t-test (paired or unpaired)

  • For multiple groups: ANOVA with post-hoc tests (Tukey, Bonferroni)

  • For non-normally distributed data: Non-parametric alternatives (Mann-Whitney, Kruskal-Wallis)

• Correlation Analysis:

  • When analyzing relationships between BCG9842_B4423 and other proteins

  • Use Pearson's or Spearman's correlation coefficients as appropriate

• Multiple Testing Correction:

  • Apply FDR (False Discovery Rate) or Bonferroni correction when performing multiple comparisons

By following these guidelines, researchers can ensure that data on BCG9842_B4423 expression is presented clearly, analyzed rigorously, and interpreted accurately, facilitating communication within the scientific community.

What experimental controls should be included when studying BCG9842_B4423 localization and function?

Robust experimental controls are essential for reliable interpretation of results when investigating membrane protein localization and function. For studies involving BCG9842_B4423, the following controls should be incorporated:

Localization Studies:

• Positive Controls:

  • Well-characterized membrane proteins with known localization patterns (e.g., ATP synthase for inner membrane)

  • Proteins from the same family with established localization

  • Membrane-specific dyes or markers that co-localize with the target protein

• Negative Controls:

  • Cytoplasmic proteins known not to associate with membranes

  • Empty vector controls for recombinant expression systems

  • Peptides with scrambled transmembrane domains

• Specificity Controls:

  • Secondary antibody-only controls for immunofluorescence

  • Pre-immune serum controls

  • Peptide competition assays to confirm antibody specificity

Functional Assays:

• Genetic Controls:

  • Knockout/knockdown strains to confirm loss of function

  • Complemented strains to verify phenotype rescue

  • Point mutants affecting key residues to identify critical functional domains

  • Overexpression strains to assess dose-dependent effects

• Biochemical Controls:

  • Heat-inactivated protein preparations

  • Competing substrates or inhibitors

  • Proteins with similar structure but different function

  • Detergent controls when working with solubilized membrane proteins

Physiological Studies:

• Environmental Controls:

  • Different growth phases and conditions

  • Stress responses (temperature, pH, osmolarity)

  • Wild-type responses to various germinants (for spore studies)

  • Time course experiments to capture dynamic processes

• Cross-Species Controls:

  • Homologous proteins from related Bacillus species

  • Heterologous expression in model organisms

Technical Controls:

• Fractionation Quality Controls:

  • Measure levels of known markers for different cellular compartments:

    • Membrane markers (e.g., other integral membrane proteins)

    • Cytoplasmic markers (e.g., housekeeping enzymes)

    • Spore coat markers (for spore preparations)

• Recombinant Protein Controls:

  • Empty tag control (His-tag only)

  • Unrelated protein with similar size/charge

  • Multiple purification methods to ensure consistent results

Incorporating these comprehensive controls ensures experimental rigor and facilitates distinguishing true biological phenomena from technical artifacts or non-specific effects.

How can researchers analyze membrane proteome data to contextualize BCG9842_B4423 function within Bacillus cereus biology?

Contextualizing BCG9842_B4423 within the broader membrane proteome requires sophisticated data analysis approaches that integrate multiple data types and biological knowledge:

Comparative Proteomics Analysis:

• Differential Expression Analysis:

  • Compare protein abundance across different conditions:

    • Vegetative cells vs. spores

    • Different growth phases

    • Various stress conditions

  • Use statistical methods to identify significantly changing proteins

  • Create volcano plots showing fold-change vs. statistical significance

• Co-expression Network Analysis:

  • Build correlation networks based on protein expression patterns

  • Identify proteins with expression profiles similar to BCG9842_B4423

  • Apply clustering algorithms to find functional modules

  • Use graph theory metrics to identify hub proteins and network structure

Functional Contextualization:

• Gene Ontology Enrichment:

  • Categorize co-expressed proteins by biological process, molecular function, and cellular component

  • Perform statistical enrichment analysis to identify overrepresented functions

  • Create functional annotation clusters to reveal biological themes

• Pathway Mapping:

  • Map identified proteins to known metabolic and signaling pathways

  • Identify pathway gaps that BCG9842_B4423 might fill

  • Overlay expression data on pathway maps to visualize system-level changes

Phylogenetic Analysis:

• Homology-Based Function Prediction:

  • Identify homologs of BCG9842_B4423 in related species

  • Compare conservation patterns across Bacillus species and beyond

  • Analyze synteny (gene neighborhood conservation) for functional insights

  • Examine evolutionary rate to assess selective pressure

• Domain-Based Analysis:

  • Identify conserved domains and motifs within the protein sequence

  • Compare with functionally characterized domains in other proteins

  • Predict functional sites based on conservation patterns

Integrated Multi-omics Approach:

• Integration with Transcriptomics:

  • Correlate protein abundance with mRNA levels

  • Identify post-transcriptional regulation

  • Analyze promoter regions for regulatory elements

• Integration with Metabolomics:

  • Correlate membrane protein expression with metabolite profiles

  • Identify potential transport substrates or signaling molecules

  • Develop testable hypotheses about protein function

• Integration with Phenotypic Data:

  • Connect expression patterns with phenotypic characteristics

  • Link to spore resistance, germination efficiency, or stress response

By integrating these analytical approaches, researchers can generate hypotheses about the functional role of BCG9842_B4423 within the complex biology of Bacillus cereus, guiding further targeted experimental investigations.

What bioinformatic tools are most effective for predicting BCG9842_B4423 structure and function?

Predicting the structure and function of membrane proteins like BCG9842_B4423 requires specialized bioinformatic tools that account for their unique characteristics. The following tools and approaches are particularly effective:

Sequence-Based Analysis:

• Transmembrane Topology Prediction:

  • TMHMM: Predicts transmembrane helices using hidden Markov models

  • TOPCONS: Consensus prediction from multiple algorithms

  • MEMSAT: Combines multiple sequence alignments with neural networks

  • CCTOP: Constrained consensus topology prediction

• Signal Peptide and Membrane Targeting:

  • SignalP: Predicts signal peptides for protein secretion

  • LipoP: Identifies lipoproteins and signal peptides

  • PrediSi: Predicts signal peptides with high accuracy

• Functional Domain Identification:

  • InterProScan: Integrated search against multiple domain databases

  • SMART: Simple Modular Architecture Research Tool

  • Pfam: Protein family database for domain annotation

  • CDD: Conserved Domain Database search

Structural Prediction:

• 3D Structure Prediction:

  • AlphaFold2: Deep learning-based protein structure prediction

  • RoseTTAFold: Neural network for protein structure prediction

  • I-TASSER: Iterative threading assembly refinement

  • SWISS-MODEL: Homology modeling based on template structures

• Membrane Protein-Specific Tools:

  • MEMOIR: Membrane protein modeling with implicit representation

  • MEDELLER: Homology modeling for membrane proteins

  • OPM: Orientation of Proteins in Membranes database

Functional Prediction:

• Protein-Protein Interaction:

  • STRING: Database of known and predicted protein interactions

  • STITCH: Chemical-protein interaction networks

  • InterPreTS: Prediction of protein interaction sites

• Ligand Binding Site Prediction:

  • FTSite: Identification of ligand binding sites

  • PocketQuery: Detection of potential binding pockets

  • SiteMap: Evaluation of potential binding sites

• Function Annotation Tools:

  • BLAST2GO: Functional annotation of sequences

  • eggNOG-mapper: Fast functional annotation

  • DeepGOPlus: Deep learning-based GO term prediction

Integrated Analysis Pipelines:

• Comprehensive Annotation:

  • Prokka: Rapid prokaryotic genome annotation

  • InterProScan: Integrated protein signature recognition

• Comparative Genomics:

  • OrthoFinder: Phylogenetic orthology inference

  • KEGG Mapper: Mapping genes to pathways

  • BRITE: Functional hierarchies

By combining multiple bioinformatic approaches and tools, researchers can generate comprehensive predictions about BCG9842_B4423 structure and function, which can then guide experimental design for functional validation.

What are the key research gaps in our understanding of Bacillus cereus UPF0754 membrane proteins?

Despite advances in membrane proteomics, significant knowledge gaps remain in our understanding of Bacillus cereus UPF0754 membrane proteins like BCG9842_B4423. These research gaps represent important opportunities for future investigation:

Structural Characterization:

• Lack of high-resolution structures for any UPF0754 family members

• Incomplete understanding of transmembrane topology and domain organization

• Limited information on oligomerization states and structural dynamics

• Absence of structural data on protein-ligand interactions

Functional Annotation:

• Unknown biochemical functions for most UPF0754 family proteins

• Unclear physiological roles in vegetative cells versus spores

• Limited understanding of potential transport substrates or signaling partners

• Undefined connections to known cellular processes or stress responses

Regulatory Mechanisms:

• Poor characterization of transcriptional and translational regulation

• Unknown post-translational modifications affecting protein function

• Limited understanding of protein turnover and membrane insertion mechanisms

• Unclear regulatory relationships within membrane protein networks

Evolutionary Context:

• Incomplete phylogenetic analysis across bacterial species

• Limited understanding of selective pressures maintaining these proteins

• Unknown evolutionary relationships to functionally characterized protein families

• Unclear patterns of gene duplication and specialization

Technological Limitations:

• Challenges in membrane protein solubilization and purification

• Difficulties in developing specific activity assays for uncharacterized proteins

• Limitations in membrane protein crystallization for structural studies

• Challenges in analyzing protein-lipid interactions that may be functionally important

Addressing these research gaps will require interdisciplinary approaches combining advanced structural biology techniques, functional genomics, systems biology, and evolutionary analysis. Focused studies on BCG9842_B4423 could serve as a model for understanding this enigmatic protein family and its roles in bacterial physiology.

How might future research directions advance our understanding of BCG9842_B4423 and related membrane proteins?

Future research on BCG9842_B4423 and related UPF0754 membrane proteins should employ multidisciplinary approaches to address current knowledge gaps and advance understanding of their biological significance:

Advanced Structural Biology:

• Cryo-EM Studies:

  • Determine high-resolution structures in different functional states

  • Visualize the protein in native-like membrane environments

  • Identify conformational changes associated with potential functions

• Integrative Structural Approaches:

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

  • Use hydrogen-deuterium exchange mass spectrometry to identify dynamic regions

  • Apply cross-linking mass spectrometry to determine domain interactions

Functional Genomics:

• CRISPR-Cas9 Genome Editing:

  • Generate knockout mutants in various Bacillus species

  • Create point mutations in conserved residues

  • Develop conditional expression systems to study essential functions

• Transcriptomics and Proteomics:

  • Perform RNA-Seq on knockout strains to identify affected pathways

  • Use quantitative proteomics to assess system-wide effects

  • Apply ribosome profiling to study translational regulation

Systems Biology:

• Protein Interaction Mapping:

  • Use proximity labeling (BioID, APEX) to identify neighboring proteins

  • Perform co-immunoprecipitation coupled with mass spectrometry

  • Apply bacterial two-hybrid screening for direct interactors

• Metabolomics Integration:

  • Compare metabolite profiles between wild-type and mutant strains

  • Identify potential transport substrates or metabolic pathways affected

  • Develop flux analysis to track metabolite movement

Specialized Techniques for Membrane Proteins:

• Nanodiscs and Lipidomics:

  • Study protein function in defined lipid environments

  • Identify specific lipid requirements for activity

  • Analyze lipid composition changes in knockout strains

• Single-Molecule Techniques:

  • Apply single-molecule FRET to study conformational dynamics

  • Use atomic force microscopy to measure membrane topography

  • Employ optical tweezers to study potential mechanical functions

Translational Applications:

• Antimicrobial Development:

  • Assess BCG9842_B4423 as a potential drug target

  • Screen for specific inhibitors targeting this membrane protein

  • Develop peptides that disrupt essential protein-protein interactions

• Biotechnological Applications:

  • Engineer the protein for biosensor development

  • Exploit spore properties for bioremediation applications

  • Design protein variants with enhanced stability or activity

By pursuing these research directions, scientists can significantly advance our understanding of BCG9842_B4423 and the broader UPF0754 protein family, potentially revealing novel biological functions and applications in biotechnology or medicine.