Recombinant Protein hokD (hokD1), partial

What is recombinant protein hokD (hokD1) and what are its characteristics?

Recombinant protein hokD (hokD1) is a partial protein derived from Shigella flexneri with the UniProt accession number Q7UCD5. It is also known as "Protein hokD" or alternatively "Protein relF" . The protein is typically produced in mammalian cell expression systems and is supplied with >85% purity as determined by SDS-PAGE analysis .

Being a partial protein means it contains select regions of the complete hokD protein, which may be advantageous for certain research applications where specific domains are of interest. The tag type is typically determined during the manufacturing process and may vary between batches, which should be considered when designing experiments that might be affected by tag interactions .

What are the recommended storage and reconstitution procedures for hokD (hokD1)?

The storage recommendations for hokD (hokD1) follow standard protocols for maintaining protein stability:

For reconstitution, follow these methodological steps:

• Briefly centrifuge the vial before 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% (recommended 50%)

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

Repeated freezing and thawing is not recommended. Working aliquots may be stored at 4°C for up to one week .

How does recombinant protein expression work, and why is it important for hokD research?

Recombinant protein expression involves introducing genetic material encoding hokD into host cells to produce the protein of interest. For hokD (hokD1), the process typically uses mammalian cell expression systems . The importance of this approach lies in:

• Ability to produce proteins not naturally abundant in source organisms

• Capacity to modify protein characteristics through genetic engineering

• Potential to scale production for research applications

• Opportunity to study protein structure-function relationships

In experimental contexts, recombinant protein expression success depends significantly on translation initiation efficiency. Research analyzing 11,430 expression experiments found that approximately 50% of recombinant proteins fail to express properly in host cells . This makes optimization of expression conditions particularly important when working with specialized proteins like hokD.

How can translation initiation site accessibility be optimized for improved hokD expression?

Translation initiation site accessibility has been identified as a critical factor in successful recombinant protein expression. A comprehensive analysis of 11,430 protein expression experiments revealed that accessibility of translation initiation sites significantly outperforms alternative features in predicting expression success .

To optimize hokD expression:

• Analyze mRNA structure around initiation sites: The stability of RNA structures around the Shine-Dalgarno sequence and translation initiation site inversely correlates with protein expression .

• Implement synonymous codon substitutions: Modify up to the first nine codons of mRNAs with synonymous substitutions using algorithms that predict unpairing probabilities across the Boltzmann's ensemble .

• Use accessibility prediction tools: Tools like TIsigner can be employed to model mRNA base-unpairing and predict expression outcomes with higher accuracy than traditional methods based solely on codon optimization .

• Consider opening energy calculations: Calculate opening energies for sub-sequences to predict expression outcomes. Sub-sequence regions with strong correlations to successful expression typically have high AUC scores (area under the receiver operating characteristic curve) .

The statistical analysis of accessibility features showed AUC scores of 0.70, significantly outperforming alternatives like minimum free energy (MFE) with 0.67, codon adaptation index (CAI) with 0.57, and tRNA adaptation index (tAI) with 0.55 .

What Design of Experiments (DoE) approach should be used to optimize hokD expression conditions?

Design of Experiments (DoE) provides a systematic approach to optimize recombinant protein expression by examining multiple variables simultaneously. For hokD expression optimization, consider this methodological framework:

• Identify critical variables: Key factors affecting hokD expression likely include pH, temperature, inducer concentration, media composition, protein concentration, and duration of expression .

• Select appropriate DoE model: Response surface methodology (RSM) allows investigation of interactions between variables affecting hokD expression .

• Design factorial experiments: A 2^n factorial design (where n is the number of variables) can efficiently evaluate main effects and interactions . For complex systems, fractional factorial designs reduce experimental load while maintaining statistical power.

• Execute and analyze: Conduct experiments according to the design matrix and analyze results using statistical software to identify optimal conditions and interactions .

One successful example employed a 2^8-4 factorial design to optimize recombinant protein expression by examining eight variables related to medium composition and induction conditions, achieving a 75% homogeneity of the target protein in its active form .

The advantage of DoE over one-factor-at-a-time approaches is the ability to detect interactions between parameters, which is particularly valuable for complex proteins like hokD .

What secretion systems could potentially improve hokD production in E. coli?

For challenging proteins like hokD, secretion-based production systems in E. coli can improve yield and simplify purification. Several systems merit consideration:

• Type I Secretion System (T1SS):

  • The HlyA T1SS from uropathogenic E. coli can be implemented in laboratory strains

  • Requires co-expression of hlyB and hlyD genes, with tolC encoded on the genome

  • For secretion, fusion to the non-toxic 50-60 amino acid HlyA C-terminal domain is essential

  • Bypasses periplasm during secretion, reducing physiological impact on cells

  • Stoichiometry between hlyA, hlyB, and hlyD transcripts significantly impacts secretion rate

• Type III Secretion System (T3SS):

  • MG1655-derived strain MKS12 with deletions in fimA-H, fliD, and fliC genes enables direct secretion to media

  • The 5' untranslated region of FliC positively impacts protein secretion

  • Has achieved secretion titers up to 4 mg/L for various proteins

• Considerations for hokD secretion:

  • Protein folding rate impacts secretion efficiency (slower folding may improve secretion)

  • Proteins are typically secreted in unfolded states

  • Efficiency depends on protein characteristics including length, folding rate, and sec-dependency

These systems should be evaluated specifically for hokD, as secretion efficiency varies significantly between proteins. Prior optimization using DoE approaches would help identify the most effective secretion strategy for this particular protein .

How can protein refolding conditions be optimized for hokD recovery from inclusion bodies?

When hokD forms inclusion bodies during expression, optimization of refolding conditions becomes critical. A structured approach to this challenge involves:

• Dissolution of inclusion bodies:

  • Solubilize inclusion bodies using strong denaturants (typically 6-8M urea or guanidine hydrochloride)

  • Include reducing agents like DTT (1-5 mM) to ensure complete reduction of disulfide bonds

  • Optimize protein concentration (typically 1-2 mg/mL) to prevent aggregation during refolding

• Refolding optimization using DoE:

  • Key variables to consider: pH, redox conditions (GSH/GSSG or cysteine/cystine ratio), denaturant concentration, protein concentration, temperature, and additives

  • A successful example achieved 57% refolding efficiency using:

    • Dissolution at 2 mg/mL protein in 6M urea with 2mM DTT at pH 10.2 for 30 minutes

    • Addition of 4mM cystine prior to 10-fold dilution with buffer

    • Refolding reaction for 72h at 2-10°C

• Interaction analysis:

  • DoE approach reveals crucial interactions between parameters (e.g., between cystine and urea concentrations)

  • Creation of a process model aids in predicting outcomes of condition adjustments

For hokD specifically, considering its structure and characteristics, a systematic DoE approach examining these variables would likely yield significant improvements in recovery of correctly folded, functional protein from inclusion bodies.

What accessibility analysis tools can predict successful hokD expression?

Accessibility analysis tools for predicting recombinant protein expression success have emerged as valuable resources. For hokD expression, consider:

• TIsigner tool:

  • Uses simulated annealing to modify the first nine codons of mRNAs with synonymous substitutions

  • Optimizes accessibility of translation initiation sites

  • Available as a web application (https://tisigner.com/tisigner)[3]

• Accessibility calculation approaches:

  • Boltzmann's ensemble calculations to model mRNA base-unpairing probabilities

  • Opening energy calculations for sub-sequences around initiation sites

  • Analysis of local features (sequences surrounding translation start site) rather than global features

• Implementation methodology:

  • Calculate opening energies for all possible sub-sequences of the target protein

  • Focus on regions showing strong correlation between opening energies and expression outcomes

  • Identify sub-sequence regions with high AUC scores for prediction accuracy

These tools have demonstrated superior performance compared to traditional approaches based on codon adaptation index (CAI), minimum free energy (MFE), or tRNA adaptation index (tAI). For hokD, analyzing the accessibility of translation initiation sites could significantly improve expression outcomes by identifying optimal sequence modifications while maintaining the amino acid sequence .

How should mammalian expression systems be selected for optimal hokD production?

When selecting mammalian expression systems for hokD production, consider these methodological approaches:

• Host cell selection:

  • Different mammalian cell lines provide varying post-translational modification capabilities

  • Common options include CHO cells (high productivity), HEK293 cells (complex proteins), and NS0 cells (monoclonal antibodies)

  • Selection should consider growth characteristics, protein folding capacity, and glycosylation patterns

• Transgene delivery methods:

  • Transient transfection: Lipofection or PEI-based methods for rapid expression

  • Stable transfection: Integration into host genome for consistent long-term expression

  • Viral gene delivery: Enhanced efficiency for difficult-to-transfect cell lines

• Expression vector design:

  • Promoter selection affects expression levels (CMV provides strong constitutive expression)

  • Signal peptides direct protein to secretory pathway

  • Addition of appropriate tags facilitates purification while minimizing impact on function

Mammalian expression systems are particularly valuable for hokD when proper folding and post-translational modifications are critical for biological activity. The source listed in the product information for hokD is mammalian cells, suggesting these systems are effective for this particular protein .

What analytical methods are most appropriate for characterizing recombinant hokD?

Comprehensive characterization of recombinant hokD requires multiple analytical approaches:

• Purity assessment:

  • SDS-PAGE: Standard method confirming >85% purity for hokD preparations

  • SEC-HPLC: Evaluates size homogeneity and aggregation state

  • Mass spectrometry: Provides precise molecular weight and confirms protein identity

• Structural characterization:

  • Circular dichroism: Assesses secondary structure elements

  • Thermal shift assays: Determines protein stability and proper folding

  • Limited proteolysis: Identifies accessible regions and domain boundaries

• Functional analysis:

  • Specific binding assays: Confirms interaction with known partners

  • Activity assays: Based on known biochemical function

  • Surface plasmon resonance: Measures binding kinetics and affinity

• Stability testing:

  • Accelerated stability studies: Predicts long-term storage behavior

  • Freeze-thaw testing: Assesses resistance to handling conditions

  • pH and temperature profiles: Identifies optimal buffer conditions

These analytical methods should be selected based on the specific research objectives for hokD and the particular characteristics of interest for the study design.