Recombinant Aquifex aeolicus Uncharacterized protein aq_2118 (aq_2118)

What expression systems have been successful for recombinant production of aq_2118?

The recombinant aq_2118 protein has been successfully expressed in E. coli expression systems with an N-terminal His-tag for purification purposes. This approach enables efficient isolation through nickel affinity chromatography. The commercially available recombinant protein is supplied as a lyophilized powder with greater than 90% purity as determined by SDS-PAGE.

The expression in E. coli represents a standard approach for thermophilic proteins, though researchers should consider that:

• The native host Aquifex aeolicus grows at extremely high temperatures (optimally at 85-95°C)

• Codon optimization may be necessary for efficient expression

• Alternative expression systems (such as thermophilic hosts) might provide proteins with more native-like properties

What are the optimal storage and handling conditions for the recombinant aq_2118 protein?

Based on manufacturer recommendations, the recombinant aq_2118 protein should be:

• Initially stored at -20°C/-80°C upon receipt

• Aliquoted to avoid repeated freeze-thaw cycles, which can compromise protein integrity

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

• Supplemented with 5-50% glycerol (final concentration) for long-term storage

• Working aliquots can be stored at 4°C for up to one week

These conditions are designed to maintain protein stability and activity. The Tris/PBS-based buffer with 6% trehalose at pH 8.0 used for storage helps preserve the protein's native conformation during the freeze-thaw process.

How can structure-based function prediction be applied to uncharacterized proteins like aq_2118?

Structure-based function prediction represents a powerful approach for uncharacterized proteins when sequence-based methods yield limited insights. This methodology involves several key steps:

• Structural determination or prediction: Using X-ray crystallography, NMR, or increasingly accurate prediction algorithms like AlphaFold

• Binding site identification: Computational analysis to identify potential binding pockets

• Structural comparison with characterized proteins: Comparing predicted binding sites to libraries of known structures

This approach has proven successful for other uncharacterized proteins. For example, researchers identified the function of Tm1631 protein from Thermotoga maritima (another thermophilic bacterium) by comparing its predicted binding site to a library containing thousands of candidate structures, revealing similarities with nucleotide binding sites, particularly the DNA-binding site of endonuclease IV.

For aq_2118 specifically, researchers could:

• Generate a high-quality structural model using AlphaFold or similar tools

• Use computational tools to predict binding sites

• Compare these binding sites against structural libraries

• Validate predictions through molecular dynamics simulations

• Design experimental validation studies based on computational results

What experimental approaches can validate predicted functions of aq_2118?

Validating computational predictions requires a multi-faceted experimental approach:

• Binding assays: If structural predictions suggest nucleotide binding (as with Tm1631), techniques such as isothermal titration calorimetry (ITC), surface plasmon resonance (SPR), or fluorescence-based assays can quantify binding affinities and specificities.

• Activity assays: Based on binding predictions, develop specific enzymatic assays to test for predicted activities.

• Molecular dynamics validation: As demonstrated with Tm1631, molecular dynamics simulations can validate the stability and interactions predicted by computational models. Interactions predicted in the model should correspond to known important interactions in characterized proteins, and binding free energies should be in close agreement.

• Mutational analysis: Targeted mutations of predicted key residues can confirm their importance for binding or catalysis.

• Structural studies: X-ray crystallography or cryo-EM studies of aq_2118 with potential ligands can provide definitive evidence of binding modes.

This systematic approach bridges computational predictions and experimental validation, significantly increasing the likelihood of accurate functional assignment.

What approaches can identify potential binding partners of aq_2118 in its native context?

Identifying physiological binding partners represents a critical step in functional characterization. Several approaches can be employed:

• Pull-down assays with thermophilic lysates: Using His-tagged aq_2118 as bait to identify interacting proteins from Aquifex aeolicus lysates.

• Bacterial two-hybrid systems: Modified for thermophilic conditions to identify protein-protein interactions.

• Cross-linking mass spectrometry (XL-MS): To capture transient protein-protein interactions that might be disrupted during conventional pull-down experiments.

• Proximity labeling: Techniques like BioID or APEX2 could be adapted to thermophilic conditions to identify proximal proteins in vivo.

• Co-expression analysis: Examining genomic context and co-expression patterns of aq_2118 with other Aquifex aeolicus genes to identify potential functional relationships.

When designing these experiments, researchers must consider the thermophilic nature of Aquifex aeolicus, which may require modifications to standard protocols to accommodate high-temperature conditions or the use of thermostable reagents.

What are the unique challenges in working with proteins from hyperthermophiles like Aquifex aeolicus?

Aquifex aeolicus is a hyperthermophilic bacterium that grows optimally at temperatures between 85-95°C, presenting several methodological challenges:

• Expression challenges: Recombinant expression in mesophilic hosts like E. coli may result in improperly folded proteins or inclusion bodies.

• Structural considerations: Proteins from hyperthermophiles often have:

  • Higher proportion of charged residues

  • Increased number of salt bridges

  • More compact hydrophobic cores

  • Shorter surface loops

• Functional assays: Standard enzymatic assays may need modification for:

  • Higher temperature conditions

  • Thermostable substrates and reagents

  • Specialized equipment for high-temperature reactions

• Physiological context: The physiological conditions of Aquifex aeolicus (95°C, slightly alkaline pH) differ substantially from standard laboratory conditions, potentially affecting protein behavior and interactions.

• Crystallization challenges: Hyperthermophilic proteins often require specialized crystallization conditions and may behave differently than mesophilic counterparts.

Researchers should consider performing assays at both standard and elevated temperatures to understand the protein's behavior across conditions.

How can molecular cloning techniques be optimized for studying aq_2118?

Efficient molecular cloning is essential for detailed characterization studies. Based on successful approaches with other challenging proteins, researchers should consider:

• Codon optimization: Adjust codon usage to match the expression host (typically E. coli) while maintaining key structural elements.

• Expression vector selection: Vectors with tightly regulated promoters (like pET series) can prevent toxic effects during expression.

• Fusion tags: Beyond the standard His-tag for purification, consider:

  • Solubility-enhancing tags (MBP, SUMO, or TrxA)

  • Fluorescent protein fusions for localization studies

  • Cleavable tags with recognition sites for precision tag removal

• Expression conditions optimization:

  • Induction temperature (often lower temperatures for thermophilic proteins)

  • Inducer concentration

  • Expression duration

  • Media composition

• Site-directed mutagenesis: For structure-function studies, design an efficient mutagenesis strategy focusing on:

  • Conserved residues identified through multiple sequence alignment

  • Predicted active site residues

  • Surface-exposed residues potentially involved in protein-protein interactions

Drawing from techniques used in virus characterization, researchers might consider inserting reporter genes (like GFP) to track expression and localization, similar to the approach used for tracking DWV-B viruses.

What crystallization approaches are most suitable for structural studies of aq_2118?

Structural determination is critical for understanding function. For aq_2118, consider:

How can researchers employ mass spectrometry to characterize potential post-translational modifications of aq_2118?

Mass spectrometry offers powerful approaches for characterizing post-translational modifications (PTMs), which could be critical for aq_2118 function:

• Sample preparation workflows:

  • In-solution digestion with multiple proteases (trypsin, chymotrypsin, etc.)

  • Enrichment strategies for specific PTMs (phosphopeptides, glycopeptides)

  • Native MS approaches to preserve non-covalent interactions

• MS techniques for comprehensive analysis:

  • Liquid chromatography-tandem mass spectrometry (LC-MS/MS)

  • Electron transfer dissociation (ETD) for labile modifications

  • Top-down proteomics for intact protein analysis

• Data analysis strategies:

  • Open search algorithms to identify unexpected modifications

  • Site-specific quantification of modification stoichiometry

  • Correlation of modifications with functional states

• Comparative analysis:

  • PTM profiles under different growth conditions

  • Comparison between recombinant and native protein if available

While no specific PTMs have been documented for aq_2118, its sequence contains potential sites for phosphorylation, acetylation, and other modifications that might regulate function or localization.

What bioinformatic approaches can predict functional networks involving aq_2118?

Computational approaches can provide crucial insights into potential functions by examining:

• Genomic context analysis:

  • Operon structure and co-transcribed genes

  • Conserved gene neighborhoods across related species

  • Functional enrichment of proximal genes

• Protein-protein interaction prediction:

  • Sequence-based interaction site prediction

  • Structural docking with potential partners

  • Co-evolution analysis to identify interacting partners

• Phylogenetic profiling:

  • Correlation of presence/absence patterns across species

  • Identification of proteins with similar evolutionary histories

• Metabolic pathway mapping:

  • Integration into known Aquifex metabolic pathways

  • Gap-filling analyses to identify potential enzymatic roles

• Expression correlation networks:

  • Analysis of transcriptomic data to identify co-regulated genes

  • Identification of shared regulatory elements

These computational predictions can guide targeted experimental design to validate potential functional associations.