Recombinant Archaeoglobus fulgidus Uncharacterized protein AF_0189 (AF_0189)

What is Archaeoglobus fulgidus AF_0189 protein and why is it significant for research?

AF_0189 is an uncharacterized protein from the hyperthermophilic archaeon Archaeoglobus fulgidus (strain ATCC 49558 / VC-16 / DSM 4304 / JCM 9628 / NBRC 100126). This protein is of particular research interest because it comes from an extremophile organism that thrives in high-temperature environments. As an uncharacterized protein with UniProt accession number O30049, AF_0189 presents opportunities for novel functional discoveries in extremophile biology. The protein consists of 96 amino acids with the sequence: MPTHQCHIIRAVPVVRYVVALLHWLLWRVVVIIAISVPVFHHPFRNLRPCHFRPSWVCNRILRTSSFPMVLPSQHRALPSHQHQHYANLLPIHFTS .

What are the recommended storage and handling conditions for AF_0189 recombinant protein?

For optimal preservation of protein structure and activity, store AF_0189 recombinant protein at -20°C for regular use or -80°C for extended storage. The protein is typically provided in a Tris-based buffer with 50% glycerol to maintain stability. Avoid repeated freeze-thaw cycles, as these can degrade protein structure and function. For active research, working aliquots can be maintained at 4°C for up to one week . When designing experiments, incorporate proper controls to account for potential activity changes due to storage conditions.

How should researchers approach experimental design when working with an uncharacterized protein like AF_0189?

When designing experiments for uncharacterized proteins like AF_0189, follow a systematic approach:

• Begin with a specific research question about the protein's function, structure, or interactions

• Define your variables clearly: independent variables (experimental conditions you'll manipulate) and dependent variables (measurements you'll take)

• Develop a testable hypothesis based on bioinformatic predictions or homology with known proteins

• Design treatments to manipulate your independent variables (temperature, pH, substrates, etc.)

• Plan appropriate measurement methods for your dependent variables (activity assays, binding studies, etc.)

What bioinformatic approaches should precede experimental work with AF_0189?

Before conducting wet-lab experiments with AF_0189, researchers should implement a comprehensive bioinformatic analysis pipeline:

This systematic approach provides a foundation for hypothesis generation and experimental design. The hydrophobic character suggested by the amino acid sequence (containing multiple leucine, valine, and isoleucine residues) may indicate membrane association or involvement in protein-protein interactions, which should guide initial experimental approaches .

What are the recommended methods for expressing and purifying recombinant AF_0189 for research purposes?

For optimal expression and purification of recombinant AF_0189, consider the following methodological approach:

• Expression system selection: Since AF_0189 originates from a hyperthermophilic archaeon, consider using a thermophilic expression system or E. coli strains optimized for thermostable proteins

• Vector design: Include appropriate affinity tags that won't interfere with the protein's native structure; consider thermal stability of the tags

• Expression conditions: Test various induction temperatures (25-37°C) and IPTG concentrations to optimize soluble protein yield

• Purification strategy:

  • Initial capture: Affinity chromatography based on vector-designed tags

  • Intermediate purification: Ion exchange chromatography

  • Polishing: Size exclusion chromatography

• Quality control checks:

  • SDS-PAGE for purity assessment

  • Western blot for identity confirmation

  • Mass spectrometry for precise molecular weight determination

When reporting purification results, present both tabular yield data and representative gel images to demonstrate purity across purification steps. Tagging strategies should be carefully considered, as the tag type will be determined during the production process to optimize protein stability and function .

How can researchers effectively design experiments to determine the cellular localization of AF_0189?

To determine the cellular localization of AF_0189, implement a multi-method experimental design:

• Computational prediction:

  • Analyze sequence for signal peptides, transmembrane domains, and localization signals

  • Use tools like PSORT, SignalP, and TMHMM as preliminary guidance

• Fluorescence microscopy approaches:

  • Generate GFP-tagged AF_0189 constructs for expression in archaeal model systems

  • Use confocal microscopy to visualize cellular distribution

  • Co-localize with known compartment markers

• Subcellular fractionation:

  • Develop fractionation protocols optimized for archaeal cells

  • Analyze each fraction using Western blotting with anti-AF_0189 antibodies

  • Compare distribution patterns with known compartment markers

• Immunogold electron microscopy:

  • Use specific antibodies against AF_0189 with gold-conjugated secondary antibodies

  • Visualize precise localization at ultrastructural level

Design your experimental controls carefully to account for potential artifacts from protein tags or overexpression. When reporting results, present both visual data (microscopy images) and quantitative analysis of protein distribution across cellular compartments .

What approaches should be used to investigate potential binding partners and protein-protein interactions of AF_0189?

To systematically investigate AF_0189's potential binding partners and interactions, implement a multi-layered experimental strategy:

• In silico prediction:

  • Use structure-based docking to predict interaction partners

  • Analyze protein surface for potential interaction domains

• Affinity purification coupled with mass spectrometry (AP-MS):

  • Express tagged AF_0189 in native or model organisms

  • Purify AF_0189 along with bound partners

  • Identify partners through mass spectrometry

  • Validate interactions with reciprocal pull-downs

• Yeast two-hybrid screening:

  • Use AF_0189 as bait against archaeal genomic libraries

  • Confirm positive interactions with secondary screens

• Surface plasmon resonance (SPR) or bio-layer interferometry (BLI):

  • Quantify binding kinetics of predicted interactions

  • Determine association/dissociation constants

• Proximity labeling approaches:

  • Use BioID or APEX2 fusions to identify proximal proteins in cellular context

When analyzing interaction data, create network visualization maps to identify functional clusters and apply appropriate statistical tests to distinguish significant interactions from background. The full-length protein structure should be considered when designing constructs to preserve potential binding domains .

How should researchers design experiments to investigate the effect of extreme conditions on AF_0189 structure and function?

When designing experiments to investigate how extreme conditions affect AF_0189, implement a structured approach that reflects the hyperthermophilic origin of Archaeoglobus fulgidus:

• Temperature stability studies:

  • Measure protein stability across 20-100°C range using differential scanning calorimetry

  • Assess activity retention after heat exposure

  • Compare stability with and without stabilizing agents

• pH tolerance analysis:

  • Test structural stability and activity across pH 2-10

  • Use circular dichroism to monitor secondary structure changes

  • Implement activity assays at various pH values

• Salt concentration effects:

  • Examine protein behavior in salt concentrations from 0-2M

  • Measure changes in solubility, oligomerization state, and activity

  • Use light scattering to assess aggregation tendencies

• Pressure effects:

  • If available, use specialized equipment to test function under high pressure

  • Compare with other proteins from deep-sea organisms

• Combined stress factors:

  • Design factorial experiments examining interactions between temperature, pH, and salt

  • Use response surface methodology to identify optimal and limiting conditions

Present results using heat maps or contour plots showing activity/stability across condition combinations. Include appropriate statistical analyses of variance (ANOVA) to determine significant factors affecting protein behavior. Such experiments provide valuable insights not only into AF_0189 specifically but may also reveal general principles of protein adaptation to extreme environments .

What statistical approaches should be used when analyzing experimental data from AF_0189 functional studies?

When analyzing experimental data from AF_0189 functional studies, implement rigorous statistical approaches tailored to biochemical research:

• Data preparation and screening:

  • Check for normality using Shapiro-Wilk or Kolmogorov-Smirnov tests

  • Identify and address outliers using standardized residuals

  • Transform data if necessary to meet parametric test assumptions

• Appropriate statistical tests selection:

  • For comparing two conditions: t-test (parametric) or Mann-Whitney U (non-parametric)

  • For multiple conditions: ANOVA with appropriate post-hoc tests (Tukey's HSD or Bonferroni correction)

  • For relationship analysis: correlation and regression models

• Advanced multivariate analysis:

  • Principal component analysis (PCA) for data dimensionality reduction

  • Cluster analysis to identify patterns in response profiles

  • MANOVA for experiments with multiple dependent variables

• Effect size calculation:

  • Report Cohen's d or similar metrics alongside p-values

  • Calculate confidence intervals to indicate precision of estimates

• Power analysis:

  • Determine appropriate sample sizes for experimental design

  • Report achieved power for non-significant results

Statistical software packages like jamovi or SPSS can facilitate these analyses. When reporting results, include both descriptive statistics (mean, standard deviation) and inferential statistics (test statistic, degrees of freedom, p-value, effect size). This comprehensive approach ensures reliable interpretation of AF_0189 functional data .

What are the best practices for presenting complex experimental data from AF_0189 research?

When presenting complex experimental data from AF_0189 research, follow these structured guidelines:

• Organize data from general to specific:

  • Begin with an overview of experimental parameters and conditions

  • Present baseline characteristics before specific findings

  • Ensure data directly addresses the research questions

• Choose appropriate presentation formats:

  • Text: Use for interpretations and highlighting key findings

  • Tables: Present precise numerical values and statistical comparisons

  • Figures: Illustrate trends, relationships, and structural data

• Design effective figures:

  • Use consistent formatting and clear labeling

  • Choose appropriate visualization types (bar charts for comparisons, line graphs for trends, heat maps for multi-parameter data)

  • Include error bars and statistical significance indicators

• Create informative tables:

  • Use clear, concise titles that summarize content

  • Organize similar data in columns for easier comparison

  • Include footnotes for methodological details rather than cluttering the main table

• Follow scientific writing best practices:

  • Write in past tense when describing results

  • Present data with their interpretation, not just raw values

  • Avoid redundancy between text, tables, and figures

When reporting AF_0189 experimental results, ensure all figures and tables are self-explanatory with appropriate titles, labels, and legends. Use consistent units throughout, and provide details on statistical tests applied. This approach ensures clarity and enables readers to fully understand the significance of your findings .

How should contradictory results in AF_0189 research be analyzed and presented?

When faced with contradictory results in AF_0189 research, implement this systematic approach for analysis and presentation:

• Verification steps:

  • Repeat experiments with identical conditions to confirm reproducibility

  • Review all experimental protocols for potential methodological differences

  • Check reagent quality, including protein batch variation

• Exploration of contradictions:

  • Design controlled experiments specifically targeting the contradictory variables

  • Systematically modify one parameter at a time to identify critical factors

  • Consider environmental variables (temperature, pH, buffer composition)

• Statistical analysis of contradictions:

  • Apply meta-analysis techniques when comparing across studies

  • Use Bayesian approaches to incorporate prior knowledge

  • Calculate confidence intervals to assess overlap between contradictory results

• Presentation framework:

  • Present contradictory data side by side in tables or figures for direct comparison

  • Use clear visual distinctions between different experimental conditions

  • Include a comprehensive methods section detailing all relevant variables

• Interpretation guidelines:

  • Consider multiple working hypotheses that could explain contradictions

  • Discuss implications of each potential explanation

  • Propose specific experiments to resolve contradictions

When reporting contradictory results, maintain objectivity and avoid dismissing unexpected findings. Present a balanced view of all data and acknowledge limitations. This approach not only demonstrates scientific integrity but may lead to novel insights about AF_0189's behavior under varying conditions .

What ethical considerations should researchers address when studying proteins from extremophile organisms like Archaeoglobus fulgidus?

When studying proteins from extremophile organisms like Archaeoglobus fulgidus, researchers should address several key ethical considerations:

• Biodiversity and conservation:

  • Ensure sampling methods from extreme environments are sustainable

  • Obtain appropriate permits for collection from protected habitats

  • Consider impact on microbial ecosystem balance

• Responsible resource sharing:

  • Deposit sequence data in public databases with complete metadata

  • Share recombinant constructs with the scientific community

  • Provide detailed methodologies to enable reproducibility

• Intellectual property and indigenous knowledge:

  • Acknowledge indigenous knowledge about extremophile habitats

  • Develop fair benefit-sharing agreements when applicable

  • Navigate patenting issues with transparency

• Laboratory safety considerations:

  • Implement appropriate biosafety measures, even for non-pathogenic organisms

  • Assess environmental risks of genetically modified extremophile proteins

  • Establish protocols for safe disposal of experimental materials

• Research integrity:

  • Maintain detailed records of all experimental procedures

  • Report all results, not just those supporting hypotheses

  • Acknowledge limitations of experimental approaches

When planning research involving AF_0189 or other extremophile proteins, incorporate these ethical considerations into your experimental design from the earliest stages. This ensures not only regulatory compliance but also promotes sustainable and equitable scientific advancement in this specialized field .

How can researchers develop reliable controls for experiments with uncharacterized proteins like AF_0189?

Developing reliable controls for experiments with uncharacterized proteins like AF_0189 requires a systematic approach:

• Negative controls:

  • Buffer-only conditions matching the protein storage medium

  • Heat-denatured protein samples to control for non-specific effects

  • Unrelated proteins of similar size/structure to detect non-specific interactions

• Positive controls:

  • Well-characterized proteins from the same organism or family

  • Synthetic peptides corresponding to predicted active domains

  • Known activities expected based on bioinformatic predictions

• Internal controls:

  • Multiple protein concentrations to establish dose-dependency

  • Time-course measurements to confirm kinetic expectations

  • Replicates across different protein preparations

• Methodological controls:

  • Site-directed mutants targeting predicted functional residues

  • Tagged vs. untagged protein comparisons to assess tag interference

  • Alternative methods measuring the same parameter

• Experimental design considerations:

  • Randomization of sample processing order

  • Blinding of sample identity during analysis when possible

  • Inclusion of internal standards for quantitative measurements

What are the recommended approaches for developing antibodies against AF_0189 for research applications?

To develop effective antibodies against AF_0189 for research applications, implement this comprehensive strategy:

• Epitope selection:

  • Analyze protein sequence for antigenic regions using prediction algorithms

  • Consider accessibility based on predicted structural models

  • Select multiple epitopes from different regions to increase success probability

• Antibody production strategies:

  • Polyclonal antibodies: Immunize rabbits or other suitable animals with purified recombinant AF_0189

  • Monoclonal antibodies: Implement hybridoma technology using immunized mice

  • Recombinant antibodies: Generate phage display libraries and screen against AF_0189

• Validation protocols:

  • Western blotting against purified protein and cellular extracts

  • Immunoprecipitation efficiency testing

  • Immunofluorescence specificity confirmation

  • Cross-reactivity assessment against related proteins

• Optimization guidelines:

  • Test different blocking agents to minimize background

  • Determine optimal antibody concentrations through titration

  • Evaluate various fixation methods for immunocytochemistry

• Quality control measures:

  • Implement lot-to-lot consistency testing

  • Assess stability under various storage conditions

  • Document specificity with knockout/knockdown controls when possible

When reporting antibody development, include detailed methods covering immunization protocols, screening procedures, and validation results. Present data showing antibody specificity and sensitivity, including appropriate positive and negative controls. This systematic approach ensures the generation of reliable research tools for studying the uncharacterized AF_0189 protein .

What computational modeling approaches are most appropriate for predicting the structure and function of AF_0189?

For predicting the structure and function of an uncharacterized protein like AF_0189, implement these computational modeling approaches:

• Sequence-based analysis:

  • Profile-based methods (PSI-BLAST, HHpred) to detect remote homologs

  • Conservation analysis to identify functionally important residues

  • Disorder prediction to identify flexible regions

• Ab initio structure prediction:

  • AlphaFold2 or RoseTTAFold for highly accurate structure prediction

  • Model quality assessment using metrics like pLDDT scores

  • Ensemble modeling to capture conformational diversity

• Structure-based function prediction:

  • 3D template matching against function-annotated structure databases

  • Active site prediction using CASTp, POCASA, or similar tools

  • Electrostatic surface analysis for interaction potential

• Molecular dynamics simulations:

  • Stability assessment under different temperature conditions

  • Conformational sampling to identify potential functional states

  • Solvent accessibility analysis

• Integrated approaches:

  • Combined sequence-structure-function workflow

  • Consensus predictions from multiple methods

  • Experimental validation of key predictions

When implementing these approaches, consider that AF_0189 comes from a hyperthermophilic organism, which may require specialized force fields or parameters for accurate modeling. Present computational results with appropriate validation metrics and highlight the confidence level of various predictions. Use visualization techniques that clearly communicate structural features and potential functional sites. This comprehensive computational analysis provides a foundation for subsequent experimental characterization of this uncharacterized protein .